IROS 2014 Conference Digest
IEEE/RSJ International Conference on Intelligent Robots and Systems September 14-18, 2014 Palmer House Hilton Hotel Chicago, Illinois, USA www.iros2014.org
IROS 2014 Program Summary
Track&1 Track&2 Track&3 Interactive& Crystal& Exhibit& Grand&Ballroom State&Ballroom Red&Lacquer&Room Salons Room Hall
Sunday%September%14 8:30F17:00 Workshops&and&Tutorials Setup 18:00F19:30 Welcome%Reception
Monday%September%15 8:00F8:20 Conference&Welcome 8:20F9:10 Plenary&I:&&Peter&Corke 9:20F10:40 MoA1 MoA2 MoA3 10:40F11:10 Coffee%Break 11:10F12:30 MoB1 MoB2 MoB3 MoA&Talks Exhibits 12:30F13:50 Lunch;%RSJ%Power%Lunch 13:50F15:10 MoC1 MoC2 MoC3 MoB&Talks Government& 15:20F16:40 MoD1 MoD2 MoD3 MoC&Talks Forum Evening Explore(Chicago%Social%Events
Tuesday%September%16 8:00F8:50 Plenary&II:&&Todd&Kuiken 9:00F10:20 TuA1 TuA2 TuA3 MoD&Talks 10:20F10:50 Coffee%Break Industry& 10:50F12:10 TuB1 TuB2 TuB3 TuA&Talks Forum:&& Perspectives& 12:10F13:30 Lunch;%IEEE%RAS%Women%in%Engineering%Lunch on&EntrepreF Exhibits 13:30F14:50 TuC1 TuC2 TuC3 TuB&Talks neurship&in& 15:00F16:20 TuD1 TuD2 TuD3 TuC&Talks Robotics&and& 16:20F16:50 Coffee%Break Automation 16:50F17:55 TuE1 TuE2 TuE3 TuD&Talks 18:30F21:30 Banquet%at%the%Art%Institute%of%Chicago,%111%S%Michigan%Ave
Wednesday%September%17 8:00F8:50 Plenary&III:&&Andrew&Davison 9:00F10:20 WeA1 WeA2 WeA3 TuE&Talks 10:20F10:50 Coffee%Break 10:50F12:10 WeB1 WeB2 WeB3 WeA&Talks Exhibits 12:10F13:10 Lunch;%IEEE%RAS%Young%Professional%Lunch%and%Lunch%with%Leaders 13:10F13:50 Awards&Ceremony 14:00F15:20 WeC1 WeC2 WeC3 WeB&Talks 15:20F15:50 Coffee%Break 15:50F17:10 WeD1 WeD2 WeD3 WeC&Talks 17:20F19:00 Farewell%Party%and%WeD%Interactives%in%the%Interactive%Salons
Thursday%September%18 Navigation& 8:30F17:00 Workshops&and&Tutorials Contest
oral sessions up from exhibits to ballrooms
down to 3rd foor
oral sessions, plenaries
Palmer House exhibits 4th Floor Note that the ballroom section of the hotel is 1/2 foor higher than the Exhibit Hall, but oral sessions, both are called the plenaries Fourth Floor.
3rd Floor Interactive Salons Note that the Crystal Room section of the hotel is 1/2 foor higher than the Interactive Salons, but both up to are called the Third Floor. Crystal Lower-numbered papers in an oral session can be Ashland Room, Track 1, Grand, Salons 1-3 found in lower-numbered speaker prep salons during the up to 4th foor subsequent interactive forums sessions. For example, papers 2 and 3 in Track 3 (Red Lacquer Room) can be found in Salon 7, while papers 19 and 20 can be found in Salon 12. Track 2, State, Salons 4-6, 8, 9
Track 3, Red Lacquer, Salons 7, 10, 12
Table of Contents
Welcome from the General and Program Chairs 1
IROS 2014 Organizing Committee 3
IROS Advisory Council and Steering Committee 4
IROS Conference Paper Review Board 5
Venue 8
Transportation 10
Social Events 12
Explore Chicago Social Events 14
Nearby Dining 17
Sponsors 19
Exhibitors 20
Plenaries 23
Special Events 27
Paper Awards 30
Workshops and Tutorials 34
Oral and Interactive Sessions 50
Program at-a-Glance 53
Summary Slides 81
Author Index 241
ICRA 2015 264
Welcome from the General and Program Chairs
Dear IROS 2014 Attendees,
Welcome to Chicago! We are honored to host you at the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. We hope you enjoy the technical excellence and innovation on display at IROS 2014.
We received over 1600 paper submissions and nearly 50 workshop and tutorial submissions. Ultimately 750 papers and 27 workshops and tutorials were selected for the final program, with authors from nearly 50 countries from around the world.
This year, for the first time, IROS is experimenting with a new format, where each paper is assigned a 3-minute oral presentation and an 80-minute interactive presentation. Each oral session consists of up to 20 3-minute presentations along with one session keynote. In the session immediately following an oral presentation, the presenter presents the work in an interactive session, with the aid of their laptop and an LCD screen, to any attendee whose interest was piqued by the oral presentation. This format allows the number of parallel oral sessions to be shrunk to three, potentially providing larger audiences for the oral presentation, while creating an opportunity for more significant interaction with attendees with related interests.
This "pitch plus interactive" format has been used with success in the smaller, single- track RSS conference. It was also experimented with for a subset of papers at IROS 2011. At ICRA 2012 and ICRA 2013, some papers were chosen for purely interactive presentations (no oral presentations) while others were purely oral presentations. As the robotics community continues to experiment with formats to best serve conference- goers, we decided to try the experiment of treating all papers identically, as "pitch plus interactive." This contrasts with ICRA 2014, which used up to 19 parallel sessions in the "traditional" format. Feedback on the merits of these approaches will be sought from the robotics community, and this feedback will influence future conference organization.
Potential benefits of the "pitch plus interactive" format include a conference that is more physically compact and easier to navigate; potentially wider exposure for presenters' work; encouraging concise and effective presentations; a possibility to see a wider cross-section of current work in robotics; and greater opportunity for significant interaction and networking, particularly for more junior researchers. It also allows each paper to be treated identically, instead of some papers being selected for interactive presentations and some for oral presentations. Challenges include greater A/V support and technical and timing requirements; less in-depth technical presentations on topics that are of interest to you; moving between rooms during talks; and predicting attendance at oral vs. interactive presentations.
In addition to the new conference format, IROS 2014 features 39 session keynotes by leaders in the field; three plenary speeches; a vibrant industrial exhibition and talks from sponsors; special forums and panels on industry and entrepreneurship and government policy as it relates to robotics; and a number of other special events including lunches sponsored by the Robotics Society of Japan and the IEEE Robotics and Automation Society.
Time to socialize with colleagues and potential collaborators is also vital to a good conference, and IROS 2014 provides plenty of opportunities. In addition to the welcome
1 and farewell receptions, the coffee breaks in the Exhibit Hall, and the banquet at the Art Institute of Chicago, the Monday night Explore Chicago social events allow attendees to customize their Chicago experience to their own interests. You can experience one of a variety of uniquely Chicago events: a river and lake architecture cruise, a Chicago Cubs baseball game, a show at the Second City Comedy Club, a blues show at Buddy Guy's Legends, or a bicycle ride along the Chicago lakefront, among others.
Putting together an event like this requires a tremendous amount of volunteer effort. We are fortunate to have an outstanding Organizing Committee. If you see one of them, please thank them for their effort!
Special recognition must go to the Conference Paper Review Board, which handled over 5000 reviews of the submitted papers and helped the Senior Program Committee pick the very best contributions for IROS 2014. The technical expertise of the CPRB was invaluable. Our deepest gratitude goes to Wolfram Burgard, the Editor-in-Chief of the CPRB, for his ethical, efficient, and professional handling of the entire review process.
Again, welcome to Chicago. We hope you find IROS 2014 both professionally and personally rewarding!
Kevin Lynch Lynne Parker Northwestern University University of Tennessee IROS 2014 General Chair IROS 2014 Program Chair
2 IROS 2014 Organizing Committee
General Chair Publications Kevin Lynch (Northwestern U) Nikos Papanikolopoulos (U Minn)
Program Chair Finance Lynne Parker (U Tennessee) Venkat Krovi (SUNY Buffalo)
Program Co-Chairs Awards Seth Hutchinson (UIUC) Oussama Khatib (Stanford U) Jose Neira (U Zaragoza) Brad Nelson (ETH Zurich) Dong Sun (City U Hong Kong) Kazuhito Yokoi (AIST)
Conference Paper Review Board Publicity and Media Wolfram Burgard, EiC (U Freiburg) Richard Voyles (Purdue U) Howie Choset (CMU) Workshops and Tutorials Tim Bretl (UIUC) Competitions Daniel Lee (U Penn) Interactive Sessions Ani Hsieh (Drexel U) Local Arrangements Todd Murphey (Northwestern U) Speaking Sessions Brenna Argall (Northwestern U) Siddhartha Srinivasa (CMU) Matthew Spenko (Illinois Inst Tech) Paul Umbanhowar (Northwestern U) Exhibits Chair Martin Buehler (Covidien) Senior Program Committee Bill Hamel (U Tennessee) Exhibits Co-Chairs Ayanna Howard (Georgia Tech) Raj Madhavan (U Maryland) Seth Hutchinson (UIUC) Xiaorui Zhu (Harbin Inst of Tech) Oussama Khatib (Stanford U) Nobuto Matsuhira (Shibaura Inst Tech) Vijay Kumar (U Penn) Tamás Haidegger (Óbuda University) George Lee (Purdue U) Tamim Asfour (KIT) Matt Mason (CMU) Nicola Tomatis (BlueBotics) Jose Neira (U Zaragoza) Nick Gans (U Texas at Dallas) Brad Nelson (ETH Zurich) Aaron King (DTI Robotics) Paul Oh (UNLV) Dong Sun (City U Hong Kong) Information Technology Satoshi Tadokoro (Tohoku U) Torsten Kroeger (Google) Richard Vaughan (Simon Fraser U) Jing Xiao (UNC Charlotte) Social Media Kazuhito Yokoi (AIST) Andrea Zanchettin (Poli. di Milano) Jianwei Zhang (U Hamburg)
Conference Management Staff Davin Kim (Northwestern U) Debra Venedam (IEEE) Alicia Zupeck (IEEE)
3
IROS Advisory Council and Steering Committee
Advisory Council Honorary Founding Chair Fumio Harashima, Tokyo Metropolitan University, Japan
Advisory Council Founding Chair Toshio Fukuda, Meijo University, Japan (1988 GC)
Advisory Council Founding Vice Chair Hideki Hashimoto, Chuo University, Japan (1988 VC) Shin'ichi Yuta, Shibaura Institute of Technology, Japan (1988 GC)
Steering Committee Past Chair Tzyh-Jong Tarn, Washington University, U.S.A. (2001 GC)
Steering Committee Chair C.S. George Lee, Purdue University, U.S.A. (1998 PC, 2003 GC)
Steering Committee Awards Chair Shigeki Sugano, Waseda University, Japan (2013 GC)
Steering Committee Members Yasushi Nakauchi (Secretary) William R. Hamel (2009 PC) Masakatsu Fujie (1990 GC) Oussama Khatib (2011 GC) Fumio Miyazaki (1991 GC) Gaurav Sukhatme (2011 PC) Ren C. Luo (1992 GC, 2010 GC) Urbano Nunes (2012 co-GC) Volker Graefe (1994 GC) Anibal T. de Almeida (2012 GC) Katsu Ikeuchi (1995 GC) Eugenio Guglielmelli (2012 PC) Minoru Asada (1996 GC) Makoto Kaneko (2013 PC) Tamio Arai (1996 PC) Kevin Lynch (2014 GC) Christian Laugier (1997 GC, 2002, 2008 PC) Lynne E. Parker (2014 PC) Hyung Suck Cho (1999 GC) Jianwei Zhang (2015 GC) Roland Siegwart (2002 GC) Alois Knoll (2015 PC) Junku Yuh (2003 PC) Il Hong Suh (2016 GC) Kazuhiro Kosuge (2004 GC) Dong-Soo Kwon (2016 PC) Hajime Asama (2004 PC, 2010 PC) Norio Kodaira, President of RSJ Max Meng (2005 GC) Ryuichi Nakata, President of SICE Hong Zhang (2005 PC, 2017 GC) Masaya Nakamura, NTF Yunhui Liu (2006 GC) Hirofumi Tashiro, NTF Ning Xi (2006 PC) John Hung, President of IEEE IES Thomas C. Henderson (2007 PC) Raja Chatila, President of IEEE RAS Raja Chatila (2008 GC) Wolfram Burgard, EiC of CPRB Jean-Pierre Merlet (2008 Co-Chair)
4 IROS Conference Paper Review Board
Editor-in-Chief Wolfram Burgard, University of Freiburg
Editors Fumihito Arai, Nagoya University Tatsuo Arai, Osaka University Maren Bennewitz, University of Freiburg Timothy Bretl, University of Illinois at Urbana-Champaign Jose A. Castellanos, University of Zaragoza Maria Gini, University of Minnesota Shinichi Hirai, Ritsumeikan Univ. Alois Knoll, TU Munich Danica Kragic, KTH Simon Lacroix, LAAS/CNRS Jean-Pierre Merlet, INRIA Sang-Rok Oh, KIST Giuseppe Oriolo, University of Rome La Sapienza Jan Peters, Technische Universität Darmstadt Dezhen Song, Texas A&M University Matthew Spenko, Illinois Institute of Technology Siddhartha Srinivasa, Carnegie Mellon University Adriana Tapus, ENSTA-ParisTech Jing Xiao, UNC Charlotte Eiichi Yoshida, AIST
Associate Editors Dino Accoto Yasuhiro Akiyama Rachid Alami Peter Allen Ron Alterovitz Kaspar Althoefer Francesco Amigoni Yacine Amirat Mehdi Ammi Monica Anderson Juan Andrade-Cetto Henrik Andreasson Hirohiko Arai Brenna Argall Tamim Asfour Daniel Asmar Nora Ayanian Paolo Barattini Sven Behnke Kostas E. Bekris Nicola Bellotto Heni Ben Amor Dmitry Berenson Alexandre Bernardino Karsten Berns Sourabh Bhattacharya Philippe Bidaud Stan Birchfield Mårten Björkman Jeannette Bohg Ilian Bonev Julia Borras Sol Abdeslam Boularias Timothy Bretl Darius Burschka Pablo Bustos Katie Byl Maya Cakmak Raffaella Carloni Stephane Caro Stefano Carpin Juan A. Carretero Marco Carricato Filippo Cavallo Heping Chen Andrea Cherubini Kyu-Jin Cho Hyouk Ryeol Choi Howie Choset David Johan Christensen Timothy H. Chung Wan Kyun Chung Woojin Chung Matei Ciocarlie Javier Civera Nikolaus Correll Vincent CREUZE Amir Degani Renaud Detry Laurence Devillers Jorge Dias Isabelle Fantoni David Feil-Seifer Silvia Ferrari Antoine Ferreira Fanny Ficuciello David Filliat Fabrizio Flacco John Folkesson Thierry Fraichard Antonio Franchi Edwardo F. Fukushima
5 Jaime Gallardo-Alvarado Jacques Gangloff Nicholas (Nick) Gans Michael Gauthier Giuseppina Gini Grigore Gogu Marc Gouttefarde Christophe Grand Roderich Gross Yisheng Guan Jose Guivant Yi Guo Stephen J. Guy Hirotaka Hachiya Dan Halperin Kensuke Harada Kris Hauser Jean-Bernard Hayet Mitsuru Higashimori Geoffrey Hollinger Mark Hoogendoorn Shoudong Huang Gilgueng Hwang Fumiya Iida Ryojun Ikeura Luca Iocchi Volkan Isler Serena Ivaldi Hiroyasu Iwata Yan-Bin Jia Michael Kaess Takefumi Kanda Sertac Karaman Sadao Kawamura Ryo Kikuuwe Jinhyun Kim Keehoon Kim Hitoshi Kino Hedvig Kjellstrom Alexander Kleiner Ross A Knepper Jens Kober George Dimitri Konidaris Kurt Konolige Masashi Konyo Petar Kormushev Jana Kosecka Mirko Kovac Noriho Koyachi Jeffrey Krichmar Torsten Kroeger Volker Krueger Konrad Kulakowski Dana Kulic Andras Kupcsik Daisuke Kurabayashi Hanna Kurniawati In So Kweon Dong-Soo Kwon Ville Kyrki Cecilia Laschi Christian Laugier Dongjun Lee Sungon Lee Roland Lenain Guangyong Li Jyh-Ming Lien Achim J. Lilienthal Pedro Lima Lantao Liu Gonzalo Lopez-Nicolas Shugen Ma Bruce MacDonald Guilherme Jorge Maeda Yusuke Maeda Martin Magnusson Ruben Martinez-Cantin Nobuto Matsuhira Emanuele Menegatti Luis Merino Francois Michaud Mark Minor Nicole Mirnig Michael Mistry Katja Mombaur Luis Montesano Antonio Morales Jun Morimoto Alejandro R. Mosteo Giovanni Muscato Kazuhiro Nakadai Masahiro Nakajima Taro Nakamura Akio Namiki Gerhard Neumann Shun Nishide Leila Notash Andreas Nuechter Jason O'Kane Kenichi Ohara Kohtaro Ohba Kei Okada Hiroshi G. Okuno Edwin Olson Koichi Osuka Hisashi Osumi Ryuta Ozawa Erhan Oztop Vincent Padois Maurice Pagnucco Lucia Pallottino Dimitra Panagou Dejan Pangercic Wooram Park Sachin Patil Joshua Peschel Thierry Peynot Justus Piater Charles Pinto Erion Plaku Robert Platt Dan Popa Josep M Porta Andreas Pott Cedric Pradalier Domenico Prattichizzo Ananth Ranganathan Ioannis Rekleitis Cameron N. Riviere Javier Romero Selma Sabanovic Carlos Sagues Ashutosh Saxena Davide Scaramuzza James Schmiedeler J.M. Selig Luis Sentis Dylan Shell Weihua Sheng Anton Shiriaev Joshua R. Smith Joan Solà Jae-Bok Song Luciano Spinello Cyrill Stachniss Olivier Stasse Paolo Stegagno Gerald Steinbauer Mike Stilman Peter Sturm Tomomichi Sugihara Dong Sun Kenji Tahara Wataru Takano Mehdi Tale Masouleh Tamio Tanikawa
6 Lydia Tapia Matthew Taylor Stefanie Tellex Gian Diego Tipaldi Bertrand Tondu Chia-Hung Dylan Tsai Yuichi Tsumaki Costas S. Tzafestas Ales Ude James Patrick Underwood Nikolaus Vahrenkamp Bram Vanderborght Richard Vaughan Manuela Veloso Gentiane Venture Zhongkui Wang Keigo Watanabe Jizhong Xiao Yiliang Xu Yasushi Yagi Akio Yamamoto Motoji Yamamoto Katsu Yamane Jingang Yi Andrea Maria Zanchettin John S. Zelek Jianwei Zhang Brian Ziebart Michael Zillich Matthew Zucker
7 IROS 2014 Venue
Chicago Chicago was founded in 1837 at the geographically important location between the navigable waterways of the Great Lakes (Lake Michigan) and the Mississippi River. After its founding, it was the fastest growing city in the world for several decades due in large part to its location. The Chicago flag, four stars between two blue stripes, reflects the importance of Chicago's location: the stars represent important events in Chicago’s history and the two blue stripes represent the Great Lakes and the Mississippi River.
The Great Chicago Fire broke out in 1871 destroying an area of about 12 square kilometers, a major percentage of the city at the time. The fire gave birth to an urban architectural renewal that included legendary architects such as Daniel Burnham, Louis Sullivan, Frank Lloyd Wright, and Ludwig Mies van der Rohe. The first skyscrapers in the world, built using steel-skeleton construction, also appeared in Chicago soon after the fire. Chicago is now an architectural mecca and boasts the tallest building in the US not counting spires (the Willis Tower) and four of the seven tallest in the US (Trump Tower, Aon Center, and the John Hancock Center). The world's tallest building, the Burj Khalifa, was designed by the Chicago firm of Skidmore, Owings, and Merrill.
In 1893, Chicago hosted the World's Columbian Exposition (the "White City"), where the first Ferris wheel was unveiled. The Chicago Museum of Science and Industry is the only major building remaining from the Columbian Exposition. The University of Chicago is built largely on the site of the Exposition.
The Chicago River, which runs through the center of downtown Chicago, originally flowed into Lake Michigan. Pollution from the city found its way to water intakes in Lake Michigan, fouling the drinking water for Chicagoans. In 1900 a major public works project was completed to reverse the flow of the Chicago River using a series of locks. The river now flows from Lake Michigan toward the Mississippi River. This achievement was named a "Civil Engineering Monument of the Millennium" by the American Society of Civil Engineers.
Today, Chicago is the third largest city in the US, after New York and Los Angeles, with 2.7 million people in the city itself and nearly 10 million in the surrounding "Chicagoland" area. O'Hare International Airport is the second busiest in the world. Chicago is home to several major universities, including Northwestern University, the University of Chicago, the University of Illinois at Chicago, and the Illinois Institute of Technology. It is home to a thriving sports, arts, theater, improvisational comedy, and music scene. Chicago's
8 nicknames include the “Second City” (due to its relationship to New York City; this nickname was also adopted by the famed comedy troupe), the “Windy City” (thought to be due to the weather or perhaps the windbag politicians), and the “City of Big Shoulders” (from a poem by Carl Sandburg).
The Palmer House Hilton The first Palmer House, known simply as "The Palmer," was built as a wedding present from Potter Palmer to his wife Bertha Honore Palmer. It opened on September 26, 1871, but burned down just 13 days later in the Great Chicago Fire.
Potter Palmer began construction on the second Palmer House immediately after, completing the seven-story building in 1875. It was one of the most lavish hotels in the world at the time.
As business in Chicago continued to boom, supporting a larger hotel, a third Palmer House was built on the site of the second. It was built in stages so that the hotel was never closed. Construction of the 25-floor building was completed in 1925. In 1945 the Palmer House was acquired by Conrad Hilton, becoming the Palmer House Hilton. Today the Palmer House Hilton is well known for its prime location in the Chicago Loop and its extravagant Beaux Arts ceiling mural in the lobby.
The Loop "The Loop" refers to the central business and arts district of Chicago where the Palmer House Hilton is located. It is believed that the name of "the Loop" derives from the fact that Chicago L trains (elevated trains) run in a loop around this area.
Things to Do For information on things to do in Chicago, check out the conference website www.iros2014.org, the Choose Chicago website http://www.choosechicago.com/, or tripadvisor.com. The Palmer House Hilton is in a prime location for many Chicago attractions. Attractions within walking distance or a short taxi ride include the Art Institute of Chicago, the Field Museum of Natural History, the Shedd Aquarium, the Adler Planetarium, Navy Pier, the Cloud Gate sculpture (affectionately known as "the Bean") at Millennium Park, shopping on State Street or the Magnificent Mile (North Michigan Avenue), many theaters, the Lyric Opera, the Chicago Symphony Orchestra, the Chicago Cultural Center, boat cruises of the river and lake, and famous architecture such as the Willis Tower, John Hancock Center, the Tribune Tower, the Trump Tower, the Wrigley Building, and the Rookery.
Safety The area around the Palmer House Hilton is popular with tourists and is safe to walk at all hours. You may encounter panhandlers requesting coins, but they should not be aggressive.
9 Transportation
By Air Chicago is served by two major airports, O'Hare International Airport (ORD) and Midway International Airport (MDW). O'Hare is the second-busiest airport in the world with direct connections to many cities nationally and internationally. To get from the airport to the Palmer House, you can take a taxi or the less-expensive Chicago train system (the 'L'). See more information below.
By Taxi Taxis are available at almost any time at almost any location in the downtown Chicago area. Simply raise your hand to hail a taxi. It is customary to tip the taxi driver 10-20% of the fare for good service.
At O'Hare and Midway, follow the signs from the baggage claim area to the taxi stand. Never accept a ride from a taxi that has not been selected for you by the person working at the taxi stand. A taxi from O'Hare to the Palmer House, 17 East Monroe St, Chicago, costs $40-50 and can take 30 minutes in light traffic and up to 90 minutes in heavy traffic, such as rush hour. A taxi from Midway costs $30-40 and takes 20 minutes to an hour depending on traffic.
Taxis in Chicago are required to accept credit cards in addition to cash.
By the CTA Elevated Train (the 'L') The Chicago Transit Authority (CTA) operates buses and trains. The most convenient is the elevated train system, or 'L.' The L train system serves both major airports and has stops very close to the Palmer House. At the airports, follow the signs for trains to the city. From O'Hare, take the Blue Line 18 stops (about 41 minutes) to the Monroe (Blue Line) station. Walk one block east on Monroe St to the Palmer House. From Midway, take the Orange Line 8 stops (about 24 minutes) to the Harold Washington Library station. Walk three blocks north on State St and turn right (east) on Monroe St to reach the Palmer House.
ALERT: The Blue Line between O'Hare and Monroe is experiencing occasional periods of construction. You may have to transfer to a bus for part of the ride, then get back on the train to complete your trip. The transfer is free (you just need to use your card again), but this may add 10-20 minutes to your trip. You can check the CTA website as to whether any construction will be occurring when you arrive. If you prefer to avoid the hassle, take a taxi.
To ride the L, buy a single-ride ticket at a machine at the L station by paying $3.00 (or $5.00 from O'Hare). When you enter the gates to reach the platform, touch your ticket to the card reader. You don't need the card at the exit. The L is an inexpensive alternative to taxis. You can find the L system map and other information at the Chicago Transit Authority website http://www.transitchicago.com/maps.
Walking The conference location (17 E Monroe St) is in a busy financial, shopping, and arts district, and is in easy walking distance of many attractions and restaurants. Most Chicago streets run east-west or north-south and use a coordinate system, with State St (a north-south street) serving as the zero axis for east-west, and Madison St (an east-
10 west street) serving as the zero axis for north-south. Addresses that differ numerically by 800 in the east-west direction or north-south direction are 1 mile (1.6 km) apart; for example, 800 N Michigan Ave and 400 S Michigan Ave are separated by 1.5 miles (2.4 km). See the coordinate grid below.
N
W E (0, 0)
S
Venue
Bicycling Chicago is a bike-friendly city. The easiest biking is along the Lakefront Trail, which runs 18 miles (29 km) along Lake Michigan from the north end of the city to the south end. This is also the best way to see the city. There are also numerous bike lanes within the downtown area. The closest place to rent a bike for an extended bike ride is at the Millennium Park location of Bike and Roll, 239 E Randolph St. For shorter rides, the Chicago Divvy bike system allows you to pay $7.00 for 24-hour use of bikes at convenient locations across the city. As these bikes are intended for transportation from one site to another, each ride must be less than 30 minutes to avoid incurring extra charges. Learn more at the Divvy website.
11 Social Events
Welcome Reception Sunday September 14, 18:00-19:30 Grand/State Ballrooms Meet some friends, have a drink, and kickoff IROS 2014 in style.
Coffee Breaks Most coffee breaks will take place in the Exhibit Hall. Thanks to SCHUNK for their sponsorship of the coffee breaks.
RSJ Power Lunch Monday September 15 Grand, State, and Red Lacquer Rooms Hear about new technologies and products from representatives of IROS 2014 exhibitors and sponsors while you eat lunch. Lunch is complimentary but first-come first- served. Limited quantities are available.
Explore Chicago Social Events Monday evening September 15 More information on the Monday night Explore Chicago social events can be found on subsequent pages.
IEEE RAS Women in Engineering (WiE) Luncheon Tuesday September 16 Chicago Room, 5th Floor The WiE luncheon provides an opportunity for all female and male professionals who are interested to discuss the subjects of women’s engineering education, career path, career/family choices, and other topics. $5 USD registration required; see http://www.iros2014.org/program/luncheons.
Conference Banquet Tuesday September 16, 18:30-21:30 Art Institute of Chicago, 111 S Michigan Ave The world-famous collection of the Art Institute of Chicago is just a two-block walk from the Palmer House Hilton. Several galleries will be open for viewing, and there will be multiple indoor and outdoor food and drink stations.
IEEE RAS Lunch with Leaders (LwL) – Student Luncheon Wednesday September 17 Crystal Room Lunch with Leaders (LwL) offers IEEE student members an opportunity to network with RAS leaders and get advice and mentoring on their career and research. $5 USD registration required; see http://www.iros2014.org/program/luncheons.
12 IEEE RAS Young Professionals Lunch Wednesday September 17 Chicago Room, 5th Floor This luncheon is open to recent IEEE graduates, so that they can network with peers and find out more about the benefits of RAS. $5 USD registration required; see http://www.iros2014.org/program/luncheons.
Farewell Party Wednesday September 17, 17:20-19:00 Interactive Salons The Farewell Party will be in conjunction with the final interactive session. Robots, beer, and wine, not bad!
Hops ‘n Bots at the Adler Planetarium Thursday September 18, 18:30-22:30 Adler Planetarium, 1300 S Lake Shore Drive In honor of IROS 2014, the Adler Planetarium will be holding an after-hours robot- themed craft beer party on Thursday night. This is part of the Adler After Dark series, a monthly social event popular with young Chicagoans. See the planetarium, listen to bands, try the featured craft beers, and get the best views of the Chicago skyline, while members of the IROS community participate in a panel discussion and other events. The Adler Planetarium sits on the easternmost point of the Museum Campus, right on Lake Michigan, and is a pleasant 3 km walk from the Palmer House through Grant Park. Tickets are $20 at the door. You can find more information at the Adler’s website http://www.adlerplanetarium.org/adler-after-dark/ .
13 Explore Chicago Social Events Monday September 15
On Monday night, eight social events will be held at various spots around Chicago. Each conference registration comes with a ticket to one event. All transit to the social events will be by walking or public transportation (the L). To take the L, use a single-ride ticket when you enter (available for purchase at all stations for $3 if you don’t have one); it’s not needed at the exit.
It is highly recommended that you meet your group in the Palmer House lobby or near the registration desks at the times indicated below. Further information on the social event locations is given below in case you get separated from your group. Remember the Palmer House is at 17 E Monroe St, at the corner of Monroe St and Wabash Ave.
Bicycling the Lakefront Trail (meet at 5:00 PM in lobby): This is the best way to see the Chicago skyline and lakefront, and to get a little exercise at the same time. The IROS group will be led by several tourguides on a bicycling tour of the city's lakefront.
Bicycles will be leaving from the Bike and Roll storefront at 239 E Randolph St in Millennium Park. This is a 1 km walk from the Palmer House. Go east on Monroe St to Michigan Ave, north on Michigan Ave to Randolph St, and east on Randolph St to 239 E Randolph.
Blues Show at Buddy Guy’s Legends (meet at 7:00 PM at the registration desks): Chicago is famous for the blues, the precursor of rock and roll. Buddy Guy, a Chicago blues legend and winner of the National Medal of Arts and the Kennedy Center Honors, runs Buddy Guy's Legends, just down the road from the Palmer House. You will have dinner and enjoy a show at this iconic Chicago club.
Buddy Guy’s is at 700 S Wabash Ave, a 1 km walk from the Palmer House. Walk south on Wabash Ave. Dinner will be provided at the show.
Chicago Cubs Baseball Game at Wrigley Field (meet at 5:50 PM in lobby): Wrigley Field is the 100-year-old home of the Chicago Cubs. You will experience the excitement and party atmosphere of Wrigleyville and a game against the Cincinnati Reds. This is recommended for people who like rowdy fun crowds, big outdoor parties, or just want to learn a bit about baseball.
Wrigley Field is a 20-minute ride on the CTA L Red Line (10 km by taxi). Take the Red Line toward Howard from the Monroe station at the corner of State St and Monroe St (½ block west of the Palmer House) and get off at the Addison stop. To return, you can take the Red Line back from Addison, but the station may be very crowded at the end of the game. In that case, it is recommended you make a group of three or four people and take a taxi back to the Palmer House (approximately $20). You may need to walk east on Addison a couple of blocks to get away from the crowds to find an open taxi. Alternatively, leave before the end of the game or hit a Wrigleyville bar after the game until the crowds dissipate. Bars on Clark St are especially popular.
Chicago River and Lake Michigan Cruise (meet at 5:30 PM in lobby): Have a drink, relax, and enjoy the architecture of Chicago at sunset on this cruise of the Chicago River, through the lock, and out to Lake Michigan.
14 The cruise boats will leave from the dock east of the Trump Tower north of the Chicago River. It is a 1 km walk north on Wabash Ave. After crossing the river, go down to the walkway along the river and go east to the Wendella dock. Drinks will be provided on the boat, but no food.
Chocolate Tasting Tour of Chicago (meet at 5:10 PM in lobby): Take a fun and informative guided walking and tasting tour of Chicago chocolate shops, from secret treasures to famous favorites. The sweetest tour in town!
The tour will start at the Visitor Information Center in the lower level of the Macy’s building at 111 N State St. Walk west a half block and then north on State St (less than ½ km).
Goose Island Brew Pub and Brewery Tour (meet at 6:20 PM in lobby): Chicago's original microbrewery. Enjoy some pub fare, a tasting of several of Goose Island's beers, and a tour of the brewery.
Goose Island is at 1800 N Clybourn Ave, 5 km from the Palmer House. To get there, take the CTA L Red Line toward Howard from the Monroe station at the corner of State St and Monroe St (½ block west of the Palmer House) and get off at the North/Clybourn stop. Walk ½ km northwest on Clybourn. Reverse the directions to get back.
Observation Deck at the Willis Tower (meet at 5:30 PM at the registration desks): The Willis Tower (formerly the Sears Tower) is the tallest building in the US (not counting spires) with the highest observation deck, and from the Ledge on the Skydeck you will get great views of Chicago and learn a bit about Chicago's history.
Enter the Willis Tower for the Skydeck on Jackson Ave between Franklin St and Wacker Dr, a 1 km walk. Go west on Monroe St to Franklin St, south on Franklin St, then west on Jackson Ave.
Second City Comedy Show (meet at 6:45 PM in lobby): The Second City Comedy Club is the legendary birthplace of comedians such as Bill Murray, John Belushi, Tina Fey, and Stephen Colbert. You will see a revue of the Best of Second City at a show reserved for IROS attendees.
Second City is at 1616 N Wells St, 4.5 km from the Palmer House. Take the CTA L Brown Line toward Kimball from the Madison/Wabash station (1 block north on Wabash) to the Sedgwick station. Then walk 1 block north to North Ave, east on North Ave to Wells St, then north on Wells St (about a ½ km walk). To go back to the Palmer House, you can take the Brown Line in the other direction, but it will loop around the downtown Loop before returning to Madison/Wabash, adding 5 minutes to your trip.
15
river and lake cruise
bicycling
chocolate tour
L to Second City Comedy
L to baseball, brewpub Palmer House banquet
Willis Tower
Buddy Guy’s
16
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17 Restaurant Name Price Style Address Website Phone Number Lockwood (Palmer House) $$$ American (New) 17 East Monroe Street www.lockwoodrestaurant.com (312) 917-3404 1 Which Wich $ Sandwiches 108 North State Street #002 www.whichwich.com (312) 658-0030 2 Heaven on Seven $$ Southern, Cajun/Creole 111 North Wabash Avenue www.heavenonseven.com (312) 263-6443 3 Atwood $$$ American (New) 1 West Washington Street www.atwoodcafe.com (312) 368-1900 4 Pittsfield Cafe $ Diner, Brunch 55 East Washington Street www.pittsfield55.com (312) 641-1806 5 Oasis Cafe $ Mediterranean 21 North Wabash Avenue #11 www.oasiscafeone.com (312) 443-9534 6 Park Grill $$ American (New) 11 North Michigan Avenue www.parkgrillchicago.com (312) 521-7275 7 Rosebud Theater District $$ Italian 70 West Madison Street www.rosebudrestaurants.com (312) 332-9500 8 Trattoria No. 10 $$$ Italian 10 North Dearborn Street #1 www.trattoriaten.com (312) 984-1718 9 Jimmy John's $ Sandwiches, Deli 6 East Madison Street www.jimmyjohns.com (312) 368-4444 10 Chipotle $ Mexican, Fast Food 8 East Madison Street www.chipotle.com (312) 629-3662 11 Rosebud Prime $$$ Steakhouse 1 South Dearborn Street www.rosebudrestaurants.com (312) 384-1900 12 Pizano's Pizza & Pasta $$ Pizza, Italian 61 East Madison Street www.pizanoschicago.com (312) 236-1777 13 Popeye's $ Fast Food, Chicken 17 South Wabash Avenue www.popeyes.com (312) 372-8855 14 Henri $$$ French 18 South Michigan Avenue www.henrichicago.com (312) 578-0763 15 The Gage $$$ American (New), Gastropub 24 South Michigan Avenue www.thegagechicago.com (312) 372-4243 16 Hot Woks Cool Sushi $$ Japanese, Chinese, Thai 30 South Michigan Avenue www.hotwokscoolsushi.com (312) 345-1234 17 Flat Top Stir-Fry Grill $$ Asian Fusion, Grill 30 South Wabash Avenue www.flattopgrill.com (312) 726-8400
18 18 I Dream of Falafel $ Middle Eastern 112 West Monroe Street www.idreamoffalafel.com (312) 263-4363 19 Pret A Manger $ Cafe, Sandwiches 73 West Monroe Street www.pret.com (312) 260-4301 20 Potbelly Sandwich Shop $ Sandwiches, Deli 55 West Monroe Street www.potbelly.com (312) 577-0070 21 The Grillroom $$ Steakhouse 33 West Monroe Street www.grillroom-chicago.com (312) 960-0000 22 Corner Bakery Cafe $ Cafe, Bakery 35 East Monroe Street www.cornerbakerycafe.com (312) 372-0072 23 Freshii Palmer House $$ Vegetarian, American (New) 17 East Monroe Street #10 www.freshii.com (312) 419-1777 24 Beef and Brandy $$ American (Traditional) 127 South State Street www.beefbrandy.net (312) 372-3451 25 Miller's Pub $$ Pub, American (Traditional) 134 South Wabash Avenue www.millerspub.com (312) 263-4988 26 Max's Take Out $ Fast Food 20 East Adams Street www.maxstakeoutchicago.com (312) 553-0170 27 McDonalds $ Fast Food 144 South Wabash Avenue www.mcdonalds.com (773) 218-8516 28 Zoup! $ Cafe, Sandwiches 62 West Adams Street www.zoup.com (312) 470-9797 29 Berghoff Restaurant $$ German 17 West Adams Street www.theberghoff.com (312) 427-3170 30 America's Dog $ Hot Dogs, Fast Food 21 East Adams Street www.americasdog.com (312) 786-0100 31 Halo Asian Mix $ Asian Fusion 29 East Adams Street www.haloasianmix.com (312) 360-1111 32 Panda Express $ Chinese, Fast Food 77 East Adams Street www.pandaexpress.com (312) 986-1043 33 Russian Tea Time $$$ Russian 77 East Adams Street www.russianteatime.com (312) 360-0000 34 Native Foods Cafe $$ Vegetarian 218 South Clark Street www.nativefoods.com (312) 332-6332 35 Exchequer $$ Pub, Pizza, Steakhouse 226 South Wabash Avenue www.exchequerpub.com (312) 939-5633 36 Abou Andre $ Middle Eastern, Mediterranean 60 East Jackson Boulevard www.abouandre.com (312) 386-1300 37 Pazzo's Cucina Italiana $$ Italian 23 East Jackson Boulevard www.pazzoscucina.com (312) 386-9400 38 Osaka Express $ Japanese 400 South Michigan Avenue www.osaka2go.com (312) 566-0118 IROS 2014 Sponsors
19 IROS 2014 Exhibitors
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20
Technical Program
21 22 Plenary I
The Quest for Robotic Vision Peter Corke Queensland University of Technology, Australia Monday September 15, 8:20-9:10 Grand/State Ballroom
Abstract The technologies of robotics and computer vision are each over 50 years old. Once upon a time they were closely related and investigated, separately and together, in AI labs around the world. Vision has always been a hard problem, and early roboticists struggled to make vision work using the slow computers of the day — particularly for metric problems like understanding the geometry of the world. In the 1990s affordable laser rangefinders entered the scene and roboticists adopted them with enthusiasm, delighted with the metric information they could provide. Since that time laser-based perception has come to dominate robotics, while processing images from databases, not from robots, has come to dominate computer vision. What happened to that early partnership between robotics and vision? Is it forever broken, or is now the time to reconsider vision as an effective sensor for robotics? This talk will trace the history of robotics and vision, examine the state of the art and discuss what may happen in the future.
Biography Peter Corke is Professor of Robotics and Control at Queensland University of Technology, and Director of the Australian Centre of Excellence for Robotic Vision. His research spans topics including visual servoing, high-speed hardware for machine vision, field robotics, particularly for mining and environmental monitoring, and sensor networks. He has written two books: “Robotics, Vision & Control” (2011) and “Visual Control of Robots” (1997); developed the Robotics and Machine Vision Toolboxes for MATLAB; was Editor-in-Chief of the IEEE Robotics and Automation magazine (2010- 13); was a founding editor of the Journal of Field Robotics; is a member of the editorial boards of the International Journal of Robotics Research and the Springer STAR series; and is a Fellow of the IEEE. He received a Bachelor of Engineering (Electrical), Masters and PhD all from the University of Melbourne.
23 Plenary II
Development of Neural Interfaces for Robotic Prosthetic Limbs Todd Kuiken Rehabilitation Inst of Chicago and Northwestern University Tuesday September 16, 8:00-8:50 Grand/State Ballroom
Abstract The ability to control complex robot prostheses is evolving quickly. I will describe research at the Center for Bionic Medicine/Rehabilitation Institute of Chicago and Northwestern University to develop a neural-machine interface to improve the function of artificial limbs. We have developed a surgical technique called Targeted Reinnervation to use nerve transfers for improvement of robotic arm control and to provide sensation of the missing hand. By transferring the residual arm nerves in an upper limb amputee to spare regions of muscle it is possible to make new electromyographic (EMG) signals for the control of robotic arms. These signals are directly related to the original function of the lost limb and allow simultaneous control of multiple joints in a natural way. This work has now been extended by the use of pattern recognition algorithms that decode the user’s intent, enabling the intuitive control of many more functions of the prostheses. Similarly, hand sensation nerves can be made to grow into spare skin on the residual limb so that when this skin is touched, the amputee feels like their missing hand is being touched. This is a potential port to providing physiologically correct sensory feedback to amputees. Our team is now also developing a neural interface for powered leg prostheses that enables intuitive mobility based on a fusion of residual limb EMG and sensors in the robotic leg.
Biography Todd A. Kuiken received a B.S. degree in biomedical engineering from Duke University (1983), a Ph.D. in biomedical engineering from Northwestern University in Evanston, Illinois (1989) and an M.D. from Northwestern University Medical School (1990). He is a board-certified physiatrist at the Rehabilitation Institute of Chicago. He is the Director of the Center for Bionic Medicine at the Rehabilitation Institute of Chicago and a Professor in the Depts. of Physical Medicine and Rehabilitation, Bioomedical Engineering, and Surgery at Northwestern University. Dr. Kuiken is an internationally respected leader in the care of people with limb loss, both as an active treating physician and as a research scientist. He developed a novel surgical technique called Targeted Reinnervation which has now been successfully performed on over 100 people with amputations worldwide. His research is broadly published in journals including the New England Journal of Medicine, JAMA, Lancet and PNAS.
24 Plenary III
From Visual SLAM to Generic Real-time 3D Scene Perception Andrew Davison Imperial College London Wednesday September 17, 8:00-8:50 Grand/State Ballroom
Abstract I will argue that a coherent stream of research in robotics and computer vision is leading us from the visual SLAM systems of the past 15+ years towards the generic real-time 3D scene understanding capabilities which will enable the next generation of smart robots and mobile devices.
SLAM is the problem of joint estimation of a robot's motion and the structure of the environment it moves through, and cameras of a variety of types are now the main outward looking sensors used to achieve this. While early visual SLAM systems concentrated on real-time localisation as their main output, the latest ones are now capable of dense and detailed 3D reconstruction and, increasingly, semantic labelling and object awareness. A crucial factor in this progress has been how continuing improvements in commodity processing performance has enabled algorithms previously considered "off-line" in computer vision research to become part of real-time systems. But we believe this is far from the whole story: when estimation of qualities such as object identity is undertaken during a real-time loop together with localisation, 3D reconstruction and possibly even interaction or manipulation, the predictions and context continuously available should make things much easier; leading to robustness and computational efficiency which feeds back and is self-reinforcing. This in our view is what keeps progress towards generic real-time scene understanding firmly in the domain of the SLAM ways of thinking, where incremental, real-time processing is used to make globally consistent scene estimates by repeatedly comparing live data against predictions and update probabilistic models accordingly.
I will describe and connect much of the research that I and others have conducted in Visual SLAM over the recent years, with examples from my own work from MonoSLAM through systems like DTAM, KinectFusion and SLAM++.
Biography Andrew Davison received the B.A. degree in physics and the D.Phil. degree in computer vision from the University of Oxford in 1994 and 1998, respectively. In his doctorate with Prof. David Murray at Oxford's Robotics Research Group he developed one of the first robot SLAM systems using vision. He spent two years as a post-doc at AIST, Tsukuba, Japan, where he continued to work on visual robot navigation. In 2000 he returned to the University of Oxford and as an EPSRC Advanced Research Fellow from 2002 he developed the well known MonoSLAM algorithm for real-time SLAM with a single camera. He joined Imperial College London as a Lecturer in 2005, held an ERC Starting Grant from 2008 to 2013 and was promoted to Professor in 2012. His Robot Vision Research Group continues to focus on advancing the basic technology of real-time
25 localisation and mapping using vision, publishing advances in particular on real-time dense reconstruction and tracking, large scale map optimisation, high speed vision and tracking, object-level mapping and the use of parallel processing in vision. He maintains a deep interest in exploring the limits of computational efficiency in real-time vision problems. In 2014 he became the founding Director of the new Dyson Robotics Laboratory at Imperial College, a lab working on the applications of computer vision to real-world domestic robots where there is much potential to open up new product categories.
26 Special Events
Conference Welcome Monday September 15, 8:00-8:20 Grand/State Ballrooms Chair: Kevin Lynch The official conference opening will precede Plenary I.
Government Forum Monday September 15, 13:50-16:40 Crystal Room Chair: Vijay Kumar, University of Pennsylvania Policy makers from government and funding agencies in Asia, North America and Europe will talk about government funding priorities and government policy as it relates to robotics, and leaders in academia will outline new opportunities for engaging with government agencies to promote robotics research and development. The forum will consist of two sessions. Each session will consist of opening statements and a moderated question and answer session in which active audience participation is encouraged.
Panelists include Herman Bruyninckx (SPARC Initiative, Europe), Greg Hager (Computing Community Consortium, USA), Juha Heikkila (European Commission), Zexiang Li (Hong Kong University of Science and Technology), Atsushi Mano (NEDO, Japan), Sang-Rok Oh (KAIST, Korea), Jeff Trinkle (National Science Foundation, USA) , Richard Voyles (White House Office of Science and Technology, USA), and Alex Zelinsky (Chief Defense Scientist, Australia).
Industry Forum Perspectives on Entrepreneurship in Robotics and Automation Tuesday September 16, 9:00-17:55 Crystal Room Chairs: Raj Madhavan, University of Maryland and Torsten Kroeger, Google This forum brings together leading robotics companies and startups to formulate an action plan on the topic of entrepreneurship. With several high-profile robotics acquisitions in the past few years, robotics and automation technologies have been thrust into the crosshairs of the tech community’s periscope.
This forum will provide a platform for stakeholders from academia, industry, government, and end-user communities to share their experiences, failures, suggestions, and wishlists. The forum will consist of 12-15 speakers, from startups, SMEs, large companies, and the venture capitalist community, followed by a panel discussion with participation from all attendees. The discussion will be captured in a white paper. The intended audience is graduate students, researchers, roboticists, and anyone interested in entrepreneurial topics in robotics and automation.
Speakers include Brandon Basso (3D Robotics, USA), Francois Boucher (Kinova, Canada), Guy Caverot (BA Systemes, France), Renaud Champion (Robolution Capital, France), Shahin Farshchi (Lux Capital, USA), Ryan Gariepy (Clearpath Robotics, Canada), SK Gupta (National Science Foundation, USA), Ayanna Howard (Zyrobotics, USA), Christopher Parlitz (SCHUNK, Germany), Michael Peshkin (Northwestern U,
27 USA), Erwin Prassler (euRobotics TG Entrepreneurship), and Shafa Wala (Tarsier Inc., USA).
Awards Ceremony Wednesday September 17, 13:10-13:50 Grand/State Ballrooms IROS 2014 will present the following awards at a ceremony after lunch on Wednesday:
• IROS Harashima Award for Innovative Technologies • NTF Award for Entertainment Robots and Systems • JTCF Novel Technology Paper Award for Amusement Culture • RoboCup Best Paper Award • CoTeSys Cognitive Robotics Best Paper Award • ICROS Best Application Paper Award • ABB Best Student Paper Award • Best Paper Award
The Harashima Award for Innovative Technologies honors Professor Fumio Harashima, the Honorary Founding Chair of IROS, by recognizing outstanding contributions of an individual of the IROS community who has pioneered activities in robotics and intelligent systems.
Paper awards are described on subsequent pages.
Kinect Autonomous Mobile Robot Navigation Contest Thursday September 18, 8:00-17:00 Exhibit Hall On Thursday September 18, the Exhibit Hall transforms into the site for this day-long mobile robot navigation contest, sponsored by Microsoft and Adept Mobile Robots. Ten pre-qualified teams will compete for navigation supremacy in a natural café-like environment.
Technical Tour Rehabilitation Institute of Chicago and Northwestern University Thursday September 18, 14:00-17:00 345 E Superior St This tour will visit robotics labs of the Rehabilitation Institute of Chicago (RIC), which is closely tied to Northwestern University and its Neuroscience and Robotics Lab (NxR).
The Rehabilitation Institute of Chicago (RIC) is the world’s leading hospital and research enterprise in physical medicine and rehabilitation, ranked #1 by World & News Report for 23 consecutive years. Our mission is rooted in our dedication to providing the highest- quality patient care and outcomes through integrated research, scientific discovery, and education. Our patients drive our passion, and motivate us to continually improve, delivering better outcomes and achieving faster recoveries. No other rehabilitation hospital in the nation carries six research designations from U.S. government agencies, including the National Institute on Disability and Rehabilitation Research and the National Institutes of Health, to develop breakthrough treatments. RIC's research discoveries set new standards and protocols in rehabilitation hospitals around the world.
28 Northwestern University was founded in 1851, and has grown into one of the nation’s premier research institutions. Two campuses are located on Lake Michigan, one in Evanston, the first suburb north of Chicago, and one in downtown Chicago. Northwestern has 12 schools and colleges, 10 of which offer graduate and professional programs, and is home to more than 8,000 full-time undergraduates and 8,000 full-time graduate students. The Neuroscience and Robotics Lab (NxR) at Northwestern University is a collaboration among faculty and students in Northwestern's Departments of Mechanical Engineering, Biomedical Engineering, Interdepartmental Neuroscience Program, and Electrical Engineering and Computer Science, as well as the Rehabilitation Institute of Chicago. Our research focuses on robotics, neuroscience, bio- inspired robotics, and robotics-inspired neuromechanics.
Tickets are purchased through the registration site.
Getting There: The tour will take place entirely at RIC (no trip to Northwestern’s main campus in Evanston). Attendees are responsible for their own transportation to RIC.
RIC is located at 345 E Superior St, 2.5 km from the Palmer House. It is easily accessible by walking, taxi, bus, or subway. Walk east from the Palmer House to Michigan Ave, 1.6 km north on Michigan Ave to Superior St, then east on Superior St to the destination.
29 Paper Awards
At the Senior Program Committee (SPC) meeting, the Awards Chairs and the SPC intersected the set of highly-reviewed papers with the criteria for each of the seven paper awards. Papers were eligible to be considered in more than one category. Based on this intersection, a set of semifinalist papers for each award was chosen. These papers were then sent to subcommittees, one for each award. These subcommittees independently reviewed the papers to arrive at a set of finalists for each award. Award winners will be chosen by the subcommittees based on the quality of the paper and the presentation at IROS 2014.
NTF Award for Entertainment Robots and Systems Finalists This award is to encourage research and development of “entertainment robots and systems” and new technologies for future entertainment. Sponsored by the New Technology Foundation.
A Gesture Recognition System for Mobile Robots that Learns Online Alan Hamlet; Emami, Patrick TuB2.2
A Solution to Pose Ambiguity of Visual Markers Using Moire Patterns Tanaka, Hideyuki; Sumi, Yasushi; Matsumoto, Yoshio TuD3.15
JTCF Novel Technology Paper Award for Amusement Culture Finalists This award recognizes practical technology contributing to toys, toy models, and amusement culture. Sponsored by the Japan Toy Culture Foundation.
Multi-arm Robotic Swimming with Octopus-inspired Compliant Web Sfakiotakis, Michael; Kazakidi, Asimina; Chatzidaki, Avgousta; Evdaimon, Theodoros; Tsakiris, Dimitris MoA3.7
Design of paper mechatronics: Towards a fully printed robot Shigemune, Hiroki; Maeda, Shingo; Hara, Yusuke; Hashimoto, Shuji MoB2.3
An Untethered Jumping Soft Robot Tolley, Michael Thomas; Shepherd, Robert; Karpelson, Michael; Bartlett, Nicholas; Galloway, Kevin; Wehner, Michael; Nunes, Rui; Whitesides, George; Wood, Robert MoB2.7
RoboCup Best Paper Award Finalists For work in localization, navigation, mobility, and teamwork technologies, with applications to areas such as team sports, search and rescue, personal and home robotics, education, and others. Sponsored by the RoboCup Federation.
Environment-independent Formation Flight for Micro Aerial Vehicles Naegeli, Tobias; Conte, Christian; domahidi, alexander; Morari, Manfred; Hilliges, Otmar MoC3.13
30
The Response Robotics Summer School 2013: Bringing Responders and Researchers Together to Advance Response Robotics Sheh, Raymond Ka-Man; Collidge, Bill; Lazarescu, Mihai; Komsuoglu, Haldun; Jacoff, Adam TuA3.2
Finding and Navigating to Household Objects with UHF RFID Tags by Optimizing RF Signal Strength Deyle, Travis; Reynolds, Matthew; Kemp, Charlie TuC2.12
CoTeSys Cognitive Robotics Best Paper Award Finalists This award is for interdisciplinary research on cognition for technical systems (CoTeSys) and advancements of cognitive robots in industry, home applications, and daily life. Sponsored by the German Cluster of Excellence CoTeSys.
Learning Haptic Representation for Manipulating Deformable Food Objects Gemici, Mevlana Celaleddin; Saxena, Ashutosh MoB2.18
Online Interactive Perception of Articulated Objects with Multi-Level Recursive Estimation Based on Task-Specific Priors Martin Martin, Roberto; Brock, Oliver TuC1.19
Combining Top-down Spatial Reasoning and Bottom-up Object Class Recognition for Scene Understanding Kunze, Lars; Burbridge, Christopher; Alberti, Marina; Thippur, Akshaya; Folkesson, John; Jensfelt, Patric; Hawes, Nick TuD2.3
ICROS Best Application Paper Award Finalists Sponsored by the Institute of Control, Robotics, and Systems (ICROS).
Workspace Characterization for Concentric Tube Continuum Robots Burgner-Kahrs, Jessica; Gilbert, Hunter B.; Granna, Josephine; Swaney, Philip J.; Webster III, Robert James MoD1.12
Toward Automated Intraocular Laser Surgery Using Handheld Micromanipulator Yang, Sungwook; MacLachlan, Robert A.; Riviere, Cameron N. MoD1.17
Study of Reconfigurable Suspended Cable-Driven Parallel Robots for Airplane Maintenance Nguyen, Dinh Quan; Gouttefarde, Marc TuA1.14
31 Preliminary Evaluation of a New Control Approach to Achieve Speed Adaptation in Robotic Transfemoral Prosthesis Lenzi, Tommaso; Hargrove, Levi; Sensinger, Jonathon TuB1.12
Soft Landing of Capsule by Casting Manipulator System Arisumi, Hitoshi; Otsuki, Masatsugu; Nishida, Shin-Ichiro TuB3.18
ABB Best Student Paper Award Finalists This award recognizes the most outstanding paper authored primarily by, and presented by, a student. Sponsored by ABB.
Visual Localization within LIDAR Maps for Automated Urban Driving Wolcott, Ryan; Eustice, Ryan MoA2.8
Non-vector Space Stochastic Control for Nano Robotic Manipulations Zhao, Jianguo; Song, Bo; Xi, Ning MoC1.11
Remote Vertical Exploration by Active Scope Camera into Collapsed Buildings Fukuda, Junichi; Konyo, Masashi; Takeuchi, Eijiro; Tadokoro, Satoshi TuA3.5
An Estimation Model for Footstep Modifications of Biped Robots Wittmann, Robert; Hildebrandt, Arne-Christoph; Ewald, Alexander; Buschmann, Thomas TuC2.11
Online Interactive Perception of Articulated Objects with Multi-Level Recursive Estimation Based on Task-Specific Priors Martin Martin, Roberto; Brock, Oliver TuC1.19
Best Paper Award Finalists This award recognizes the most outstanding paper presented at the conference.
Multi-arm Robotic Swimming with Octopus-inspired Compliant Web Sfakiotakis, Michael; Kazakidi, Asimina; Chatzidaki, Avgousta; Evdaimon, Theodoros; Tsakiris, Dimitris MoA3.7
Remote Vertical Exploration by Active Scope Camera into Collapsed Buildings Fukuda, Junichi; Konyo, Masashi; Takeuchi, Eijiro; Tadokoro, Satoshi TuA3.5
Simultaneously Powering and Controlling Many Actuators With a Clinical MRI Scanner Becker, Aaron; Felfoul, Ouajdi; Dupont, Pierre TuB1.7
32 An Estimation Model for Footstep Modifications of Biped Robots Wittmann, Robert; Hildebrandt, Arne-Christoph; Ewald, Alexander; Buschmann, Thomas TuC2.11
Online Interactive Perception of Articulated Objects with Multi-Level Recursive Estimation Based on Task-Specific Priors Martin Martin, Roberto; Brock, Oliver TuC1.19
Cogeneration of Mechanical, Electrical, and Software Designs for Printable Robots from Structural Specifications Mehta, Ankur; DelPreto, Joseph; Shaya, Benjamin; Rus, Daniela TuD1.19
33 IROS 2014 Workshops and Tutorials
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35 Sunday Workshops and Tutorials
Half-Day Tutorial: An Open-source Recipe for Teaching/Learning Robotics with a Simulator Sunday Sept 14, 8:30-12:00, Grand Ballroom
Organizers: Renaud Detry (University of Liege, Belgium), Peter Corke (Queensland University of Technology, Australia), Marc Freese (Coppelia Robotics)
Website: http://teaching-robotics.org/trs2014/
Abstract: This tutorial is organized around a cross-platform robot development and simulation environment that can be installed in five minutes and that allows students to write control, navigation, vision or manipulation algorithms in a hundred lines of Matlab or Python code. The tutorial relies on the V-REP robot simulator, and on the Matlab Robotics Toolbox (RTB). The key feature of this combination is its ease of use – both tools are trivial to install. The tutorial is intended for teachers and students. Students will install the simulation environment on their laptop and learn everything they need to know to start implementing and testing robot algorithms. Teachers will return home with a ready-to-use recipe for organizing a master-level robotics project.
Speakers: Renaud Detry (University of Liege, Belgium), Peter Corke (Queensland University of Technology, Australia), Marc Freese (Coppelia Robotics)
Half-Day Workshop: Taxonomies of Interconnected Systems: Topology in Distributed Robotics Sunday Sept 14, 8:30-12:00, State Ballroom
Organizers: R. Williams (University of Southern California), A. Gasparri (Università degli studi "Roma Tre"), and G. Sukhatme (University of Southern California)
Website: http://asimov.usc.edu/~rkwillia/ws/iros14/
Abstract: Given the fragmented nature of multi-robot research, we suggest that a taxonomic approach is necessary to study the topics that drive interconnected systems, and to identify properties that underlie crucial, and yet common, aspects of theory and application. In this first workshop of a series, we will focus on topology in distributed robotics, which dictates robotic interaction in a system. Properties such as graph connectivity and network rigidity will be highlighted, with emphasis on communicated, sensed, and physical robotic interaction. This workshop aims to identify the theoretical possibilities when topological assumptions are satisfied, the real-world barriers, and the current efforts to enforce topological properties in multi-robot theory and practice.
Speakers: Vijay Kumar (University of Pennsylvania), Gonzalo López-Nicolás (University of Zaragoza), Roberto Naldi (University of Bologna), Lorenzo Sabattini (University of Modena and Reggio Emilia), Gaurav Sukhatme (University of Southern California), and Daniel Zelazo (Technion)
36
Half-Day Tutorial: How to Use MATLAB-ROS Interface to Prototype Robotics Algorithms for ROS-powered Robots Sunday Sept 14, 13:30-17:00, Grand Ballroom
Organizers: Yanliang Zhang (MathWorks)
Website: http://www.mathworks.com/company/events/tradeshows/tradeshow93505.html
Abstract: In this workshop, we will demonstrate how MATLAB® interacts with the Robot Operating System (ROS) using a new I/O Package. The package provides an API for creating ROS nodes in MATLAB that operate and communicate based on ROS’s publisher/subscriber mechanism. The ROS I/O Package has the following key features: (1) Enable creation of ROS nodes, publishers, and subscribers directly from MATLAB; (2) Enable creation of ROS messages from MATLAB; (3) Enable publishers to publish MATLAB data to their advertised topics; (4) Enable subscribers to execute arbitrary, user-defined MATLAB functions when messages are received; (5) Enable launching of a ROS Master in MATLAB. In addition, we will also demonstrate how to develop robotics applications with TurtleBot, Husky from Clearpath Robotics and Baxter from Rethink Robotics inside MATLAB using this I/O.
Speakers: Ren Sang Nah (MathWorks), Remo Pillat (MathWorks) and Yanliang Zhang (MathWorks)
Half-Day Workshop: Aerial Open Source Robotics Sunday Sept 14, 13:30-17:00, State Ballroom
Organizers: Lorenz Meier (ETH Zurich), Markus W. Achtelik (ETH Zurich), and Brandon Basso (3D Robotics)
Website: http://pixhawk.org/iros2014/
Abstract: With ever increasing levels of autonomy and system complexity, open source collaboration has become an important factor in robotics research. Whether structured in an environment with managed software packages like ROS or shared ad-hoc, the ability to push the boundaries of autonomous robots often depends on the availability of existing work to build on. Open source robotics is by now well established in ground robotics. As aerial robotics is moving from tackling relatively self-contained navigation tasks like the flight in GPS denied environments towards addressing dynamic scenes and more challenging dynamic obstacles, open source is equally important. This workshop is providing participants a solid overview of the current state of the art in aerial robotics research. It also provides examples of open source solutions ranging from SLAM packages for onboard computers to open hardware autopilots.
Speakers: Nathan Michael (CMU), Markus W. Achtelik (ETH Zurich), Elias Mueggler (University of Zurich) and Lorenz Meier (ETH Zurich)
37 Full-Day Workshop: Human-robot collaboration in standardization and R&D activities Sunday Sept 14, 8:30-17:00, Salon 1
Organizers: GS Virk (Univ of Gävle, CLAWAR), R Bostelmann (NIST, USA), S Moon (Sejong Univ, Korea), T Haidegger (Obuda Univ, Hungary), F Bonsignorio (Heron Robots and SSSA, IT), F Vicentini (CNR, ITIA, Italy) and P Barattini (Kontor 46, Italy)
Website: http://www.clawar.org/WorkshopHRC/index.html
Abstract: The workshop aims to create closer links between robot standardization and robot R&D sectors for targeting rapid development of effective human-robot market driven solutions to meet mandatory regulations. The two communities will be brought together for fostering discussion in the context of mature robot sectors and new emerging robot domains to assist the development of definitive experimental scenarios and protocols for benchmarking the growing range of robot-human applications.
Speakers: C Heut (EC), SK Gupta (NRI, USA), T Wang (Beihang, CN), P Dario (SSSA, IT), Y Yamada (Nagoya, JP), C Han (Hanyang, KR), H Christensen (Georgia T, USA), N Elkman (F-IFF, DE), S Haddadin (Leibniz Hannover, DE), S Rhim (Kyung Hee, KR), F Bonsignorio (Heron Robots, SSSA, IT), P Davison (RIA, USA), GS Virk (CLAWAR, UK), C Herman (AAMI, USA), S Moon (Sejong, KR), W Qu (Ecovacs, CN), E Prestes (IEEE), B Matthias (ABB, DE), R Bishoff (KUKA, DE), A De Luca (Sapienza Roma, IT), F Xu (SIASUN, CN), S Park (Yujin Robot, KR), F Ferro (PAL, ES), and J Beer (Stryker, USA)
Full-Day Workshop: AI and Robotics Sunday Sept 14, 8:30-17:00, Salon 2
Organizers: Lorenzo Riano (Bosch), Alessandro Saffiotti (Örebro University), Moritz Tenorth (Universität Bremen), George Konidaris (MIT CSAIL), Nick Hawes (University of Birmingham) and Siddharth Srivastava (UC Berkeley)
Website: http://people.csail.mit.edu/gdk/iros-airob14/
Abstract: The field of AI has fragmented into many challenging subfields that require and often reward isolation and specialization. Consequently, there is a lack of mainstream AI venues for publishing integrative research that combines techniques from multiple different fields to achieve a working robot system capable of complex behavior. This workshop aims to bring together a diverse and multidisciplinary group of researchers interested in designing intelligent robotic systems. Ample time will be left in the schedule for both spontaneous and guided discussions between presentations. A final open-floor discussion will aim at summarizing the main outcomes of the workshop around those questions, and planning the next steps for widening and consolidating the community.
Speakers: Tomas Lozano Perez (MIT), Stephen Hart (NASA / General Motors), Todd Hester (Nest Labs), Alper Aydemir (JPL), Malik Ghallab (LAAS-CNRS).
38 Full-Day Workshop: Machine Learning in Planning and Control of Robot Motion Sunday Sept 14, 8:30-17:00, Salon 3
Organizers: Maria Gini (U. of Minnesota), Marco Morales (Instituto Tecnológico Autónomo de México), Angela P. Schoellig (U. of Toronto), Lydia Tapia (U. of New Mexico), Aleksandra Faust (U. of New Mexico), and Farbod Farshidian (ETH Zurich)
Website: http://www.cs.unm.edu/amprg/mlpc14Workshop/
Abstract: It is the goal of this workshop to explore methods and advancements afforded by the integration of Machine Learning for the planning and execution of robot motion. Because ML methods are often heuristic, issues such as safety and performance are critical to assess. Also, learning-based questions such as problem learnability, knowledge transfer among robots, knowledge generalization, long-term autonomy, task formulation, demonstration, role of simulation, and methods for feature selection define problem solvability. We will address these issues while discussing current and future directions for intelligent planning and execution of motions for robotics systems.
Speakers: Pieter Abbeel (UC Berkeley), Jan Peters (Technische Universitat Darmstadt), and Manuela Veloso (CMU)
Full-Day Workshop: Modular and Swarm Systems - from Nature to Robotics Sunday Sept 14, 8:30-17:00, Salon 5
Organizers: R. Gross (The University of Sheffield), R. Möckel (Maastricht University), M. Rubenstein (Harvard University), K. Stoy (IT University of Copenhagen)
Website: https://sites.google.com/site/iros2014mss/
Abstract: This full-day workshop creates a forum to discuss the highly interdisciplinary fields of modular robotics and swarm robotics. Modularity is a concept well exploited by natural systems where relatively simple modules form highly complex structures. In swarm systems, physically independent entities or modules collaborate to perform common tasks. The fields of modular and swarm robotics have shown to be ideal playgrounds to study, for instance, self-organization, self-assembly, smart materials, self-repair, adaptation, collaboration, social interaction, and distributed intelligence in robotic and natural systems. State-of-the-art modular and swarm robot systems will be presented at the workshop’s robot exhibition.
Speakers: N. Correll (University of Colorado at Boulder), D. Floreano (EPFL), S. Glotzer (University of Michigan), S. C. Goldstein (Carnegie Mellon University), D. L. Hu (Georgia Institute of Technology), M. D. Gross (Carnegie Mellon University & Modular Robotics Inc.), D. Rus (MIT), J. Werfel (Havard University), M. Yim (University of Pennsylvania)
39 Full-Day Workshop: Micro-Nano Robotic Swarms for Biomedical Applications Sunday Sept 14, 8:30-17:00, Salon 6
Organizers: Spring Berman (Arizona State U.), Sabine Hauert (U. of Bristol), Sangeeta Bhatia (MIT), Bradley Nelson (ETH Zurich), and Vijay Kumar (U. of Pennsylvania)
Website: http://nanoswarm2014.org/
Abstract: Bioengineers are currently designing micro-nano systems for the treatment and monitoring of diseases. DNA machines, synthetic bacteria, nanoparticles, and magnetic materials are now able to move, sense and interact in a controlled fashion, an affordance that has led them to be called robots. These robots will need to be deployed in large numbers and operate predictably in highly complex biological environments. The challenge is to design swarm robotic strategies that produce collective behaviors that are useful for biomedical applications. In this interdisciplinary workshop, attendees will hear from experts in medicine, bioengineering, micro-nano robotics, and swarm robotics. The workshop includes two poster sessions and a closing panel discussion.
Speakers: Guillermo Ameer (Northwestern), Aaron Becker (Harvard Medical School), Spring Berman (ASU), Sabine Hauert (UoB), Vijay Kumar (UPenn), Sylvain Martel (EPM), Bradley Nelson (ETHZ), Daniela Rus (MIT), Taher Saif (UIUC), Metin Sitti (CMU), Mike Rubenstein (Harvard), Selman Sakar (ETHZ), Rob Wood (Harvard)
Full-Day Workshop: From Active Impedance to Intrinsically Compliant and Variable Impedance Actuators: Pros, Cons and Trade-offs Sunday Sept 14, 8:30-17:00, Salon 7
Organizers: Nikos Tsagarakis (Italian Institute of Technology, IT), Luis Sentis (University of Texas at Austin, US), and Bram Vanderborght (Vrije Universiteit, BE)
Website: http://mech.vub.ac.be/IROSWSActuators/Index.htm http://www.walk-man.eu/news/events/item/iros14-ws-on-actuators.html
Abstract: Emerging robots will need to operate within unstructured environments, collaborate with humans, and physically interact with them. To deal with these new application demands, robots should exhibit Natural Motion performance characterized by enhanced power, strength, efficiency and ultimately compliant and adaptable physical interaction capability. Novel actuation technologies are therefore needed to improve the performance of existing robots. This workshop attempts to cover the recent advancements in robotic actuation from the foundation principles to the implementation, control and application requirements aiming to answer tomorrow’s needs.
Speakers: A. Bicchi (Uni. of Pisa, IT), M. Inaba (Uni. of Tokyo, JP), A. Albu. Schaeffer (DLR, DE), S. Kim (MIT, US), S. Stramigioli (Uni. of Twente, NL), J. Buchli (ETH Zurich, CH), J. Hurst (Oregon State Uni., US), Qbrobotics, IT), L. Sentis (Uni. of Texas, US), B. Vanderborght (Uni. of Vrije, Brussel, BE), N. Tsagarakis (Italian Inst. of Technology, IT)
40 Full-Day Workshop: Assistive Robotics for Individuals with Disabilities: HRI Issues and Beyond Sunday Sept 14, 8:30-17:00, Salon 8
Organizers: Hae Won Park (Georgia Tech), Momotaz Begum (UMass Lowell), and Chung Hyuk Park (NYIT)
Website: http://www.haewonpark.com/IROS2014-ARHRI/
Abstract: Assistive robots (ARs) have huge potential in serving individuals with various physical and cognitive disabilities in their everyday lives, treatments, and therapies. By bringing together robotics researchers, cognitive scientists, clinicians, and entrepreneurs working with ARs, this workshop aims at discussing the issues that arise as we move forward to making ARs more acceptable and adaptable to the target population, irrespective of the type of ARs and the form of assistance they offer.
Speakers: Takanori Shibata (AIST), James Patton (RIC), Ayanna Howard (Georgia Tech), Charlie Kemp (Georgia Tech), Holly Yanco (UMass Lowell), Maja Matarić (USC), Brian Scassellati (Yale), Wendy Rogers (Georgia Tech), John-John Cabibihan (Qatar Univ.), Andrew Fagg (Univ. of Oklahoma), Michelle Johnson (UPenn), and Ayse Saygin (UCSD)
Full-Day Workshop: Assistance and Service Robotics in a Human Environment Sunday Sept 14, 8:30-17:00, Salon 9
Organizers: Anne Spalanzani (Inria, France), David Daney (Inria, France), Yacine Amirat (LISSI-UPEC, France), Samer Mohammed (LISSI-UPEC, France), Ren Luo (National Taiwan University, Taiwan), Rachid Alami (LAAS Laboratory, France), Christian Laugier (Inria, France)
Website: http://www.lissi.fr/iros-ar2014/doku.php
Abstract: This workshop will focus on Robotics for people assistance and services, with a particular focus on frail people. The objective of the workshop is to provide a review and challenges of the relevant applications in Assistance and Service Robotics in a Human Environment. Topics related to mobility assistance, healthcare and wellbeing will be covered. Fundamental and technological research particularly related to autonomous indoors vehicles, sensor and actuators networks, wearable and ubiquitous technologies, and human-robot interaction, will be presented. This workshop will be the third edition of a series of workshops organized in this field at IROS 2012 and IROS 2013.
Speakers: Norihiro Hagita (ATR Intelligent Robotics and Communication Laboratories, Japan), Sami Haddadin (Institute of Automatic Control (IRT), University of Hanover, Germany), Ren Luo (National Taiwan University, Taiwan), Rachid Alami (LAAS Laboratory, France), Raja Chatila (ISIR Laboratory, France).
41 Full-Day Workshop: Robot Manipulation: What has been achieved and what remains to be done? Sunday Sept 14, 8:30-17:00, Salon 10
Organizers: Erol Sahin (Middle East Technical University and Carnegie Mellon University), Siddhartha Srinivasa (Carnegie Mellon University)
Website: https://personalrobotics.ri.cmu.edu/workshops/manipulation-futures/
Abstract: Research on robotic manipulation has achieved important theoretical and technical advances in the last 50 years. Robot manipulators in factories have become a key element of industrial manufacturing, and are widely considered to be a success story. However, there remain challenges in extending this success beyond factory floors. The objective of the workshop is to discuss, understand and underline the key challenges inherent in manipulation that prevented its transition towards becoming a technology. The workshop will host invited lectures that will provide a historical evolution of ideas in robot manipulation, stating what has been achieved and what remains as challenges for future research.
Speakers: Rob Howe (Harvard University), Jean-Paul Laumond (LAAS-CNRS),Tomas Lozano-Perez (MIT), Matt Mason (Carnegie Mellon University), Stefan Schaal (University of Southern California)
Full-Day Workshop: Planning, Perception and Navigation for Intelligent Vehicles Sunday Sept 14, 8:30-17:00, Salon 12
Organizers: Philippe Martinet (IRCCyN/Ecole Centrale of Nantes), Christian Laugier (Emotion/INRIA), Urbano Nunes (ISR/University of Coimbra), and Christoph Stiller (MRT/KIT)
Website: http://ppniv14.irccyn.ec-nantes.fr/
Abstract: The purpose of this workshop is to discuss topics related to the challenging problems of autonomous navigation and of driving assistance in open and dynamic environments. Technologies related to application fields such as unmanned outdoor vehicles or intelligent road vehicles will be considered from both the theoretical and technological point of views. Several research questions located on the cutting edge of the state of the art will be addressed. Among the many application areas that robotics is addressing, transportation of people and goods seem to be a domain that will dramatically benefit from intelligent automation. Fully automatic driving is emerging as the approach to dramatically improve efficiency while at the same time leading to the goal of zero fatalities.
Speakers: Fawzy Nashashibi (INRIA), Christoph Stiller (KIT), Alonzo Kelly (CMU), Danwei Wang (NTU), Javier Ibanez-Guzman (Renault), and Urbano Nunes (ISR)
42 Thursday Workshops
Half-Day Workshop: Visual Control of Mobile Robots – ViCoMoR Thursday Sept 18, 8:30-12:00, State Ballroom
Organizers: Gonzalo Lopez-Nicolas (Universidad de Zaragoza, I3A), and Youcef Mezouar (IFMA, Clermont Université, Institut Pascal)
Website: http://vicomor.unizar.es
Abstract: Among the variety of sensors available today, vision systems stand out because they provide very rich information at low cost. One of the main reasons for integrating vision in the control loop was the interest for increased flexibility of robotic systems. However, versatility of vision systems comes at the cost of higher data processing complexity. Visual control has been one of the major research issues in robotics for more than four decades. Although control theory and computer vision are both mature areas of research, important advances that bring new challenges are happening nowadays such as the advent of RGB-D cameras, the use of omnidirectional vision, or the development of robust control techniques. Topics of interest include: Autonomous navigation and visual servoing techniques, visual perception for visual control, visual sensors, visual control with constraints, or new trends in visual control.
Speakers: Philippe Martinet (IRCCYN-CNRS, Ecole Centrale de Nantes), and Peter Corke (Queensland University of Technology)
Half-Day Workshop: Standardized Knowledge Representation and Ontologies for Robotics and Automation Thursday Sept 18, 13:30-17:00, State Ballroom
Organizers: Paulo Gonçalves (IDMEC/LAETA, Portugal), Craig Schlenoff (NIST, USA), Edson Prestes (UFRGS, Brazil) and Tamás Haidegger (Obuda University, Hungary)
Website: http://www.est.ipcb.pt/laboratorios/robotica/iros-ora
Abstract: The primary goal of this workshop is to present and disseminate the current versions of standards and draft standards regarding robot interaction and knowledge sharing. The forum will provide a platform for the deeply affected community to exchange experiences. The robotics, automation, and ontology communities at large are encouraged to attend in order to discuss and improve the outcome of the IEEE-RAS Working Group entitled “Ontologies for Robotics and Automation” (IEEE WG ORA).
Speakers: Craig Schlenoff, (NIST, USA), Wonpil Yu (ETRI, Korea), Gurvinder Virk (ISO/IEC Convenor), Edson Prestes (UFRGS, Brazil), Stephen Balakirsky (Georgia Tech, USA), Paulo Gonçalves (IDMEC/LAETA, Universidade de Lisboa, Portugal), Tamás Haidegger (Óbuda University, Hungary)
43 Full-Day Workshop: Rehabilitation and Assistive Robotics: Bridging the Gap Between Clinicians and Roboticists Thursday Sept 18, 8:30-17:00, Grand Ballroom
Organizers: Brenna Argall (Northwestern University, Rehabilitation Institute of Chicago), and Siddhartha Srinivasa (Carnegie Mellon University)
Website: http://www.eecs.northwestern.edu/~argall/14rar
Abstract: Rehabilitation and assistive technologies have the potential to change lives. Clinicians have successfully used therapy machines that physically assist a patient in performing rehabilitation exercises and activities of daily living. However, these machines can be more than just passive physical assistants. With tools from robotic perception, machine learning, and manipulation, these machines can be active, intelligent, and autonomous robots. This workshop aims to bring together clinicians and roboticists to identify the key challenges in rehabilitation and assistive robotics, collaborations for funding opportunities, and benchmarks and challenge problems for the field. We are particularly excited to leverage the close proximity of the Rehabilitation Institute of Chicago (RIC), the nation's top hospital for rehabilitation and assistance, to the conference venue and will be organizing an entire session at the RIC with lab tours.
Speakers: Yasin Dhaher (Northwestern University, RIC), Todd Kuiken (Northwestern University, RIC), Ben Kuipers (University of Michigan), and Jessica Pederson (RIC).
Full-Day Workshop: Towards Horizon 2020: Trends and challenges in micro/nanorobotics Thursday Sept 18, 8:30-17:00, Salon 1
Organizers: Michaël Gauthier (FEMTO-ST, France), Fumihito ARAI (Nagoya University, Japan), Metin Sitti (CMU, USA), Brad Nelson (ETHZ, Switzerland).
Website: http://events.femto-st.fr/trendsnanorobots/
Abstract: The objective of this workshop is to define the future trend and issues in micro-nanorobotics. The workshop will be organised in two phases (two half days). First, short presentations on the future challenges of micro-nano-robotics (10 minutes) are going to be done by key-scientists in this field. The second step consists in two to four parallel workshops in front of a paper board to establish and to synthesise keypoints of four to eight major challenges.
Speakers: B. Nelson (ETHZ, Switzerland), N. Andreff (FEMTO-ST, France), F. Arai (Nagoya Univ., Japan), T. Arai (Osaka Univ., Japan), T. Fukuda (Nagoya, Univ. Japan), M. Sitti (CMU, USA), A. Ferreira (INSA, Bourges, France), S. Martel (Polytechnique Montréal, Canada), M. Gauthier (FEMTO-ST, France), Q. Zhou (AALTO, Finland), D. Popa (Univ. Texas, USA), D. Cappelleri (Purdue Univ., USA), P. Kalio (Tampere Univ., Finland), C. Diederichs (UNIOL, Germany), C. Huet (European Commission, Brussels, Belgium, EU).
44 Full-Day Workshop: Real-time Motion Generation & Control - Constraint- based Robot Programming Thursday Sept 18, 8:30-17:00, Salon 2
Organizers: Gianni Borghesan (KU Leuven), Torsten Kroeger (Google), and Andrea Maria Zanchettin (Politecnico di Milano)
Website: http://cs.stanford.edu/people/tkr/iros2014
Abstract: The new generation of robots (redundant and/or mobile manipulators, humanoids, etc.) is challenging the robotics community to provide robust, reliable and fast motion planning and control algorithms allowing such robots to promptly react to unpredictable events, as we, humans, do. A new and lively research trend for such robotic systems relies on declarative and constraint-based task and motion specification. This workshop intends to encourage discussion between researchers working in constraint-based motion planning and control, covering various aspects of this problem.
Speakers: Oliver Brock (TU Berlin), Fabrizio Flacco (University of Rome), Kris Hauser (University of Indiana), Erwin Aertbelien (KU Leuven), Luis Sentis (University of Texas), and others.
Full-Day Workshop: Robots in Clutter: Perception and Interaction in Clutter Thursday Sept 18, 8:30-17:00, Salon 3
Organizers: Michael Zillich (Vienna University of Technology), Dejan Pangercic (Robert Bosch LLC), Maren Bennewitz (University of Freiburg), Justus Piater (University of Innsbruck), Maria Fox (King's College London)
Website: http://workshops.acin.tuwien.ac.at/clutter2014
Abstract: Complex and cluttered environments continue to present challenging problems to many aspects of robotics research. Vision faces the problem of segmenting or recognising objects amidst clutter and occlusions. Unexpected scene changes pose challenges for maintaining valid and tractable scene representations for navigation, especially in highly dynamic scenes as encountered in self-driving cars. Manipulation cannot expect precise pose knowledge of all objects in a pile, let alone contact relations. All these problems will become increasingly manifest as robots move into unstructured domestic, industrial or outdoor settings. What is meant by “robust to clutter”', however, is difficult to define and adequate metrics and benchmarks are still missing. This workshop discusses experiences and ideas for handling various problems induced by clutter, and to advance theoretically founded and system-wide approaches of handling clutter.
Speakers: Oliver Brock (TU Berlin), Franceso Ferro (PAL Robotics), Tucker Hermans (to be confirmed) (Georgia Tech), Chris Mansley (Robert Bosch LLC)
45 Full-Day Workshop: Community Consensus Benchmarks and Systems for Clinical Translation of Medical Robots Thursday Sept 18, 8:30-17:00, Salon 4
Organizers: Nabil Simaan (Vanderbilt University), Venkat Krovi (SUNY Buffalo), Peter Kazanzides (Johns Hopkins University), Simon DiMaio (Intuitive Surgical, Inc.)
Website: https://sites.google.com/site/ieeerasmedicalrobotics/
Abstract: The past decade has witnessed accelerated growth of medical robotics and computer-assisted medical technologies due to the significant practical utility, economic value, and diversity of applications benefiting patients, providers and healthcare systems. However, several challenges arise from the complexities engendered within the human body and the diverse sets of multi-disciplinary knowledge that need to be merged to create these system-level solutions and to successfully bring them to the market. We believe that there is a need for the robotics and medical device community to initiate a discussion on several issues that could benefit academia and industry in their shared pursuit of improved patient care. We therefore propose to initiate the first of a series of workshops at the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) in Chicago.
Speakers: Peter Kazanzides (JHU), Nabil Simaan (Vanderbilt), Jaydev Desai (Maryland), Kevin Cleary (Sheikh Zayed Childrens Hospital), Simon DiMaio (Intuitive Surgical), Venkat Krovi (SUNY Buffalo), Blake Hannaford (U Washington), Dennis Fowler (Columbia U), Gregory Hager (JHU), Pankaj Singhal (SUNY Buffalo & Kaleida Health), Cameron Riviere (CMU), John Tomaszewski (SUNY Buffalo), Toshio Fukuda (Meijo U), Yo Kobayashi (Waseda U), Howie Choset (CMU), Russell Taylor (JHU), Tim Salcudean (U British Columbia), Guang-Zhong Yang (Imperial College London)
Full-Day Workshop: The role of human sensorimotor control in surgical robotics Thursday Sept 18, 8:30-17:00, Salon 5
Organizers: Ilana Nisky (Ben-Gurion University), Anthony Jarc (Intuitive Surgical)
Website: http://www.stanford.edu/~inisky/Motor_Control_RAMIS_workshop.htm
Abstract: Surgery is a highly complex task requiring surgeons to precisely control instruments to operate on patients. A comprehensive understanding of surgeon sensorimotor control is fundamental to continuing improvements of teleoperated robot- assisted minimally invasive surgery platforms. Such platforms may also enable exciting findings in basic human sensorimotor control. To advance this new interdisciplinary research direction, we seek to foster a dialogue between the fields of: (1) human motor control and learning; (2) human-robot interaction, teleoperation, and surgical robotics; and (3) surgical training and skill assessment.
Speakers: Cenk Cavusoglu (Case Western Reserve University), Antonio Gangemi (University of Illinois at Chicago), Greg Hager (Johns Hopkins University), Katherine Kuchenbecker (University of Pennsylvania), Konrad Kording (Rehabilitation Institute of Chicago), Sandro Mussa-Ivaldi (Rehabilitation Institute of Chicago), Allison Okamura (Stanford University), Sam Vine (Exeter University), Guang-Zhong Yang (Imperial College of London)
46 Full-Day Workshop: Telerobotics for Real-Life Applications: Opportunities, Challenges, and New Developments Thursday Sept 18, 8:30-17:00, Salon 6
Organizers: Dongjun Lee (Seoul National University), Jordi Artigas Esclusa (DLR), Seiichiro Katsura (Keio University), Shahin Sirouspour (McMaster University)
Website: http://inrol.snu.ac.kr/telewc2014
Abstract: Being one of the oldest subjects in robotics, telerobotics has enjoyed exciting theoretical advances and significant practical impacts in many applications. Even so, how to engineer a telerobotic system, which is complex enough to be truly useful in practice, yet, still easy to operate even with limited information-exchange and/or imperfect communication, has been a formidable challenge for the telerobotics community. The main aim of this 3rd Telerobotics Workshop is to provide a forum for exchange of ideas among the users and researchers, to discuss challenges and barriers to real-life applications of telerobotics systems and to explore innovative/promising solutions to these problems
Speakers: Simon DiMaio (Intuitive Surgical), Hyoung Il Son (Samsung Heavy Industries), Eric Martin (Canadian Space Agency), Jordi Artigas-Esclusa (DLR), Robin Murphy (Texas A&M Univ.), Philippe Garrec (CEA-LIST)
Full-Day Workshop: Compliant Manipulation: Challenges in Learning and Control Thursday Sept 18, 8:30-17:00, Salon 7
Organizers: Klas Kronander (EPFL), Aude Billard (EPFL), Etienne Burdet (Imperial College London) and Jonas Buchli (ETHZ)
Website: http://lasa.epfl.ch/workshopIROS14/
Abstract: Robust and versatile compliant manipulation skills are a necessity for robots interacting with the real world. Despite significant progress in design of passively compliant mechanisms and active compliance control algorithms, today's best robots are still far behind humans in terms of manipulation performance and versatility. This workshop will identify current challenges in compliant manipulation problems and will address how recent advances in learning and control can be leveraged to advance the state of the art in this area of research.
Speakers: Neville Hogan (M.I.T), Jonas Buchli (ETHZ), Yoshihiko Nakamura (University of Tokyo), Sylvain Calinon (Idiap Research Institute), Etienne Burdet (Imperial College) and Matthew Howard (King’s College)
47 Full-Day Workshop: Active Touch Sensing in Robots and Animals Thursday Sept 18, 8:30-17:00, Salon 8
Organizers: Yon Visell (Drexel University), Vincent Hayward (Université Pierre et Marie Curie), Mitra Hartmann (Northwestern University), Nathan Lepora, (University of Bristol)
Website: http://re-touch-lab.com/iros2014/
Abstract: This workshop addresses the challenges posed by actively sensing and interacting with the world through the sense of touch, whether the latter is implemented through a technological or biological system. Active touch sensing is recovering information about the world by ‘touching’ rather than ‘being touched’ – by interpreting signals from sensors whose motion is deliberately controlled to facilitate information gain. The workshop is sponsored by the IEEE RAS Technical Committee on Haptics and will be associated with a special issue of IEEE Transactions on Haptics.
Speakers: Vincent Hayward (UPMC), James Tangorra (Drexel Univ.), Jeremy Fishel (Syntouch LLC), Mitra Hartmann (Northwestern Univ.), Melina Hale (Univ. Chicago), Katherine Kuchenbecker (Univ. Pennsylvania), Michael Wiertlewski (Northwestern Univ.), Yon Visell (Drexel Univ.), Others TBD Full-Day Workshop: The future of multiple-robot research and its multiple identities Thursday Sept 18, 8:30-17:00, Salon 10
Organizers: Nora Ayanian (USC, USA), Antonio Franchi (LAAS-CNRS, France), Lorenzo Sabattini (UNIMORE, Italy) and Dylan Shell (TAMU, USA)
Website: http://www.arscontrol.unimore.it/mrsiros14/
Abstract: The objective of this workshop is to assess the degree to which multi-robot systems is a distinct research sub-area within the robotics community rather than a topic that cuts-across each of the other sub-areas and topics. We wish to explore the degree to which core elements of multi-robot systems research (e.g., distributed algorithms, decentralized planning, etc.) span existing areas and to anticipate the degree to which these elements will in the future. This workshop aims at promoting a discussion to identify and define the overarching ideas that can tie together different research direction in multi-robot systems, and lead to the definition of common practices and standards.
Speakers: R. Alami (CNRS, France), C. Belta (BU, USA), N. Y. Chong (JAIST, Japan), M. Egerstedt (GATech, USA), R. Freeman (NWU, USA), V. Kumar (UPenn, USA), J. P. How (MIT, USA), A. Hsieh (Drexel, USA), V. Isler (UMN, USA), K. Lynch (NWU, USA), L. Parker (UTK, USA), D. Rus (MIT, USA), M. Schwager (BU, USA), K. Sekiyama (Nagoya Univ., Japan), G. Sukhatme (USC, USA)
48 Full-Day Workshop: Whole-Body Control for Robots in the Real World Thursday Sept 18, 8:30-17:00, Salon 12
Organizers: Federico L. Moro (IIT), Michael Gienger (Honda RI), Oussama Khatib (Stanford), and Eiichi Yoshida (AIST)
Website: http://www.walk-man.eu/news/events/item/iros14-ws-ijhr-si-on-whole-body- control-for-robots-in-the-real-world.html
Abstract: Whole-Body Control aims to fill the gap between robots and humans performing multiple complex actions in compliant interaction with a dynamic environment. With the recent development of fully torque-controlled robots, theory can be put into practice. The main aim of this workshop is to bring together leading researchers in the field of WBC i) to paint a clear picture of the fast evolving state-of-the- art, ii) to encourage discussions on the current limitations, and on the future research directions, and iii) to develop new research collaborations to speed up the creation of reliable real world WBC Systems. Emphasis will be placed on the application of such systems on real robots performing tasks in the real world, and the speakers will be invited to share their hands-on experience.
Speakers: A. Del Prete (LAAS-CNRS), S. Feng (CMU), M. Morisawa (AIST), F.L. Moro (IIT), Y. Nakamura (Univ. of Tokyo), F. Nori (IIT), C. Ott (DLR), L. Righetti (MPI), L. Sentis (UT Austin), R. Tedrake (MIT), and P.M. Wensing and D.E. Orin (OSU)
49 Oral and Interactive Sessions
IROS 2014 has only three parallel oral tracks, and each paper is assigned a 3-minute oral presentation as well as an 80-minute interactive presentation. After giving the oral presentation in one session, the speaker moves to the Interactive Salons during the next session to talk in more detail with anyone who would like to learn more. Some oral sessions also feature talks by industrial sponsors.
Speaker Instructions
Your presentation has two components: a three-minute pitch and an 80-minute interactive presentation. This will afford you the opportunity to present your work to a large audience (there are only three parallel speaking sessions) and to interact more deeply with those who are interested to learn more.
The Pitch Setup For the speaking sessions, you will come to the front of the room at the beginning of the session. Speakers with odd-numbered talks (talks 1, 3, 5, etc.) speak from the left podium from the audience’s viewpoint, while speakers with even-numbered talks (2, 4, 6, etc.) speak from the right podium.
While the speaker before you is speaking, you will have three minutes to set up your laptop. (VGA connection will be provided.) There will be a volunteer at the podium to help you if you need it. There will be a local monitor on the podium that shows what will project from your laptop to the screen, so you can be sure that the audience will see what you see on the monitor. There will be no audio hookup for your computer.
When the previous speaker finishes, their microphone will go dead, yours will become live, your monitor will be projected to the main screen, and the spotlight will shift to you. Your three minutes starts right then and you can begin your talk.
If you fail to connect during your three-minute setup time (which should be very rare), a secondary screen will always project the summary slide you submitted including the title of your paper and the authors' names with the speaker underlined. Again, your three minutes starts right then and you should complete your talk within the allotted time, only referring to this summary slide.
Speakers can test their laptops on a simulated setup in the Ashland Room (see the hotel map) to make sure everything is working properly.
Presenting You will have only three minutes, but there will be no changeover time and no questions, so you should be able to get your message across so the audience will know if they want to learn more and visit your display during the interactive session. Use the time wisely! Questions and discussions will happen during the interactive sessions.
Rules 1. You must finish in three (3) minutes! Plan on 2:50 to be safe. After three minutes, your microphone will go dead and your laptop will no longer be projected, and you will get the figurative (maybe literal) hook!
50 2. Your talk will be video-recorded.
Suggestions 1. PRACTICE! This is a new format for many of us, and you will need to practice a number of times to get your message across effectively in only three minutes. 2. You will not be introduced. Give your name and the title of your paper. 3. Your presentation is an advertisement for your paper, so focus on insights rather than details. 4. Avoid spending too much time on related work. 5. Consider giving an application/motivation of your work, the main result, and one piece of technical “meat” (e.g., a theorem, a design principle, an equation, etc.) that will help the audience understand the methodology and the depth of the work, understanding that there will not be time for all the details.
The Interactive Session After your speaking session, in the next session you will move to the Interactive Salons, where attendees can ask you questions and engage in discussion in an 80-minute interactive session. You will have a 42” LED 1920x1080 display to project your laptop (VGA connection provided). There will also be a fixed sign with the title and authors of your paper so attendees can find you easily.
Guidelines 1. If you have more than one author for your paper, we recommend you have two authors at your interactive station. This allows one author to walk around and talk to other authors of thematically-related papers while the second author presents the work. 2. If there are people waiting to talk to you, limit your discussion with any one attendee. Schedule a time later to get together to discuss in more detail. 3. You should have several slides prepared that get into the details, but do not plan to give full 15-minute one-way talks. The format of the interactive session should encourage lively discussions between paper authors and audience members. The format of the interactive session is not to repeat the same 15-min one-way talk over and over until the end of the session.
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53 Monday Session A, 09:20 - 10:40 Grand Ballroom State Ballroom Red Lacquer Room MoA1 MoA2 MoA3 Manipulation and Grasping I & Localization and Mapping I & Bioinspired Robots I & Robust and Optimal Control Motion and Path Planning I Multi-Robot Coordination
Chair Khatib, Oussama (Stanford University) Oriolo, Giuseppe (Sapienza University of Rome) Gini, Maria (University of Minnesota)
# Time Session Keynote Session Keynote Session Keynote
09:20- Keynote: What is Manipulation? Keynote: Dense, Object-based 3D SLAM Keynote: Bio-inspired Multi-modal Flying Robots 1 09:40 Mason, Matthew T. Leonard, John Floreano, Dario Carnegie Mellon University MIT EPFL
Manipulation and Grasping I Localization and Mapping I Bioinspired Robots I
Modeling of Underwater Snake Robots Moving in a 09:40- Robotic Manipulation in Object Composition Space Mining Visual Phrases for Long-Term Visual SLAM Vertical Plane in 3D 2 09:43 Pajarinen, Joni; Kyrki, Ville Tanaka, Kanji; chokushi, yuuto; ando, masatoshi Kelasidi, Eleni; Pettersen, Kristin Y.; Gravdahl, Jan Tommy
6D Proximity Servoing for Preshaping and Haptic Towards Indoor Localization Using Visible Light Actuation Strategy for Underactuated 09:43- Exploration Using Capacitive Tactile Proximity Sensors Communication for Consumer Electronic Devices Anthropomorphic Hands 3 09:46 Escaida Navarro, Stefan; Schonert, Martin; Hein, Liu, Ming; Qiu, Kejie; Che, Fengyu; Li, Shaohua; Tavakoli, Mahmoud; Enes, Baptiste; Marques, Lino; de Björn; Woern, Heinz Hussain, Babar; Wu, Liang; Yue, C. Patrick Almeida, Anibal
Network Localization from Relative Bearing New Rolling and Crawling Gaits for Snake-Like 09:46- Multi-Joint Gripper with Differential Gear System Measurements Robots 4 09:49 Tamamoto, Takumi; Sayama, Kazuhiro; Koganezawa, Kennedy, Ryan; Taylor, Camillo Jose Primerano, Richard; Wolfe, Stephen Koichi
2D-3D Camera Fusion for Visual Odometry in Outdoor iSplash-MICRO: A 50mm Robotic Fish Generating the 09:49- Artificial Hand with Stiffness Adjuster Environments Maximum Velocity of Real Fish 5 09:52 Koganezawa, Koichi; Ito, Akira Paudel, Danda Pani; Demonceaux, Cédric; Habed, Clapham, Richard James; Hu, Huosheng Adlane; Vasseur, Pascal; Kweon, In So
Design and Implementation of a Low-Cost and Position Control of a Robot End-Effector Based on Mamba - A Waterproof Snake Robot with Tactile 09:52- Lightweight Inflatable Robot Finger Synthetic Aperture Wireless Localization Sensing 6 09:55 QI, Ronghuai; Lam, Tin Lun; Xu, Yangsheng Vossiek, Martin; Konigorski, Ulrich; Marschall, Albert; Liljebäck, Pål; Stavdahl, Øyvind; Pettersen, Kristin Y.; Li, Gang; Voigt, Thorsten Gravdahl, Jan Tommy
Design of Hands for Aerial Manipulation: Actuator Static forces weighted Jacobian motion models for Multi-Arm Robotic Swimming with Octopus-Inspired 09:55- Number and Routing for Grasping and Perching improved Odometry Compliant Web 7 09:58 Backus, Spencer; Odhner, Lael; Dollar, Aaron Hidalgo-Carrio, Javier; Babu, Ajish; Kirchner, Frank Sfakiotakis, Michael; Kazakidi, Asimina; Chatzidaki, Avgousta; Evdaimon, Theodoros; Tsakiris, Dimitris
Robust Model Free Control of Robotic Manipulators with Prescribed Transient and Steady State Visual Localization within LIDAR Maps for Automated 09:58- Performance Urban Driving ReBiS - Reconfigurable Bipedal Snake Robot 8 10:01 Bechlioulis, Charalampos; Liarokapis, Minas; Wolcott, Ryan; Eustice, Ryan Thakker, Rohan; Kamat, Ajinkya; Bharambe, Sachin; Kyriakopoulos, Kostas Chiddarwar, Shital; BHURCHANDI, KISHOR
Dual Execution of Optimized Contact Interaction Decentralized Cooperative Trajectory Estimation for Role of Compliant Leg in the Flea-Inspired Jumping 10:01- Trajectories Autonomous Underwater Vehicles Robot 9 10:04 Toussaint, Marc; Ratliff, Nathan; Bohg, Jeannette; Paull, Liam; Seto, Mae; Leonard, John Jung, Gwang-Pil; Kim, Ji-Suk; Koh, Je-Sung; Jung, Righetti, Ludovic; Englert, Peter; Schaal, Stefan Sunpill; Cho, Kyu-Jin
Quasi-Static Manipulation of a Planar Elastic Rod Vision Based Robot Localization by Ground to Optimal Dynamic Force Mapping for Obstacle-Aided 10:04- Using Multiple Robotic Grippers Satellite Matching in GPS-Denied Situations Locomotion in 2D Snake Robots 10 10:07 Mukadam, Mustafa; Borum, Andy; Bretl, Timothy Viswanathan, Anirudh; Pires, Bernardo; Huber, Daniel Holden, Christian; Stavdahl, Øyvind; Gravdahl, Jan Tommy
Hybridization of Monte Carlo and Set-Membership Garment Perception and its Folding Using a Dual-arm Methods for the Global Localization of Underwater Empirical Investigation of Closed-Loop Control of 10:07- Robot Robots Extensible Continuum Manipulators 11 10:10 Stria, Jan; Prusa, Daniel; Hlavac, Vaclav; Wagner, Neuland, Renata; Nicola, Jeremy; Maffei, Renan; Kapadia, Apoorva; Fry, Katelyn; Walker, Ian Libor; Petrík, Vladimír; Krsek, Pavel; Smutny, Vladimir Jaulin, Luc; Prestes, Edson; Kolberg, Mariana
54 Monday Session A, 09:20 - 10:40 (Continued) Grand Ballroom State Ballroom Red Lacquer Room MoA1 MoA2 MoA3
# Time Robust and Optimal Control Motion and Path Planning I Multi-Robot Coordination
Numerical Approximation for Visibility Based Pursuit A Novel RRT Extend Function for Efficient and Smooth Reactive Switching Protocols for Multi-Robot High- 10:10- Evasion Game Mobile Robot Motion Planning Level Tasks 12 10:13 Bhattacharya, Sourabh; Basar, Tamer; Falcone, Palmieri, Luigi; Arras, Kai Oliver Raman, Vasumathi Maurizio
Guiding Sampling-Based Tree Search for Motion Correlated Orienteering Problem and Its Application to Visibility-Based Motion Planning for Active Target Planning with Dynamics Via Probabilistic Roadmap Informative Path Planning for Persistent Monitoring 10:13- Tracking and Localization Abstractions Tasks 13 10:16 Wei, Hongchuan; Lu, Wenjie; Zhu, Pingping; Huang, Le, Duong; Plaku, Erion Yu, Jingjin; Schwager, Mac; Rus, Daniela Guoquan; Leonard, John; Ferrari, Silvia
Planning Agile Motions for Quadrotors in Constrained Cooperative Control of a Heterogeneous Multi-Robot 10:16- Pursuit-Evasion Game for Normal Distributions Environments System based on Relative Localization 14 10:19 Jun, Chanyoung; Bhattacharya, Subhrajit; Ghrist, Boeuf, Alexandre; Cortes, Juan; Alami, Rachid; Cognetti, Marco; Oriolo, Giuseppe; Peliti, Pietro; Rosa, Robert Simeon, Thierry Lorenzo; Stegagno, Paolo
Optimal control for robot-hand manipulation of an Optimal Navigation Functions for Nonlinear Stochastic Three-Dimensional Multirobot Formation Control for 10:19- object using dynamic visual servoing Systems Target Enclosing 15 10:22 Jara, Carlos; Pomares, Jorge; Candelas Herías, Horowitz, Matanya; Burdick, Joel Aranda, Miguel; Lopez-Nicolas, Gonzalo; Sagues, Francisco Andrés; Torres, Fernando Carlos; Zavlanos, Michael M.
Camera Control for Learning Nonlinear Target Dynamics Via Bayesian Nonparametric Dirichlet- A Lattice-Based Approach to Multi-Robot Motion Finding Optimal Routes for Multi-Robot Patrolling in 10:22- Process Gaussian-Process (DP-GP) Models Planning for Non-Holonomic Vehicles Generic Graphs 16 10:25 Wei, Hongchuan; Lu, Wenjie; Zhu, Pingping; Ferrari, Cirillo, Marcello; uras, tansel; Koenig, Sven Portugal, David; Pippin, Charles; Rocha, Rui P.; Silvia; Klein, Robert H; Omidshafiei, Shayegan; How, Christensen, Henrik Iskov Jonathan Patrick
Remote Operated Vehicle Tether Disturbances Fleet Size of Multi-Robot Systems for Exploration of 10:25- Analysis and Target Tracking Control Multi-Cost Robotic Motion Planning under Uncertainty Structured Environments 17 10:28 Huang, hai; sheng, ming-wei; Li, Yue-ming; Wan, Lei; Simpson, Richard; Revell, James; Johansson, Anders; Cabrera-Mora, Flavio; Xiao, Jizhong Pang, Yongjie; di, wang Richards, Arthur
Reactive Phase and Task Space Adaptation for Constrained Path Optimization with Bezier Curve Stable Formation of Groups of Robots Via 10:28- Robust Motion Execution Primitives Synchronization 18 10:31 Englert, Peter; Toussaint, Marc Choi, Ji-wung; Huhtala, Kalevi Valbuena, Luis; Cruz, Patricio; Figueroa, Rafael; Sorrentino, Francesco; Fierro, Rafael
Synchronization and Consensus of a Robot Network Distance Metric Approximation for State-Space RRTs The RoboCup 2013 Drop-In Player Challenges: 10:31- on an Underactuated Dynamic Platform Using Supervised Learning Experiments in Ad Hoc Teamwork 19 10:34 Nguyen, Kim Doang; Dankowicz, Harry Bharatheesha, Mukunda; Caarls, Wouter; Wolfslag, MacAlpine, Patrick; Genter, Katie; Barrett, Samuel; Wouter; Wisse, Martijn Stone, Peter
Robust Fixed Point Transformation Based Design for State Lattice with Controllers: Augmenting Lattice- Model Reference Adaptive Control of a Modified TORA Based Path Planning with Controller-Based Motion Aligning Coordinate Frames in Multi-Robot Systems 10:34- System Primitives with Relative Sensing Information 20 10:37 Tar, József Kázmér; Várkonyi, Teréz Anna; Kovács, Butzke, Jonathan; Sapkota, Krishna; Prasad, Kush; Nagavalli, Sasanka; Lybarger, Andrew; Luo, Lingzhi; Levente; Rudas, Imre J.; Haidegger, Tamas MacAllister, Brian; Likhachev, Maxim Chakraborty, Nilanjan; Sycara, Katia
Receding Horizon Optimization of Robot Motions Sponsor Talk: Motion Planning for Collaborative A Mathematical Programming Approach to 10:37- Generated by Hierarchical Movement Primitives Robots Collaborative Missions with Heterogeneous Teams 21 10:40 Mühlig, Manuel; Hayashi, Akinobu; Gienger, Michael; Barry, Jennifer FEO, EDUARDO; Gambardella, Luca; Di Caro, Gianni Iba, Soshi; Yoshiike, Takahide Rethink Robotics A.
55 Monday Session B, 11:10 - 12:30 Grand Ballroom State Ballroom Red Lacquer Room MoB1 MoB2 MoB3 Calibration and Identification & Soft-Bodied Robotics & Navigation & Kinematics and Mechanism Design I Robot Learning I Visual Servoing
Chair Maciejewski, Anthony A. (Colorado State University) Paik, Jamie (EPFL) Hutchinson, Seth (University of Illinois)
# Time Session Keynote Session Keynote Session Keynote Keynote: Innovative Mechanical Systems to Address 11:10- Current Robotics Challenges Keynote: Soft Robotics Keynote: From Robotics to VR and Back 1 11:30 Gosselin, Clement Laschi, Cecilia LaValle, Steven M Laval University Scuola Superiore Sant'Anna di Pisa University of Illinois
Calibration and Identification Soft-Bodied Robotics Navigation A New Coefficient-Adaptive Orthonormal Basis Locally-Weighted Homographies for Calibration of Function Model Structure for Identifying a Class of Environment-Based Trajectory Clustering to Extract 11:30- Imaging Systems Pneumatic Soft Actuators Principal Directions for Autonomous Vehicles 2 11:33 Ranganathan, Pradeep; Olson, Edwin Wang, Xiaochen; Geng, Tao; Elsayed, Yahya; Tanzmeister, Georg; Wollherr, Dirk; Buss, Martin Ranzani, Tommaso; Saaj, Chakravarthini; Lekakou, Constantina
Towards Simultaneous Coordinate Calibrations for Design of paper mechatronics: Towards a fully printed Wide-Field Optical Flow Aided Inertial Navigation for 11:33- Cooperative Multiple Robots robot Unmanned Aerial Vehicles 3 11:36 Wang, Jiaole; Wu, Liao; Meng, Max Q.-H.; Ren, Shigemune, Hiroki; Maeda, Shingo; Hara, Yusuke; Rhudy, Matthew; Chao, Haiyang; Gu, Yu Hongliang Hashimoto, Shuji
Force Calibration of the the KUKA Lightweight Robot Including Embedded Joint Torque Sensors and Robot Development of a Meal Assistive Exoskeleton Made of Experimental Study of Odometry Estimation Methods 11:36- Structure Soft Materials Using RGB-D Cameras 4 11:39 Gautier, Maxime; Jubien, Anthony Koo, Inwook; Yun, Chang-ho; Viana de Oliveira e fang, zheng; Scherer, Sebastian Costa, Mateus; Scognamiglio, Joao; Yangali, Teodoro Andree; Park, Daegeun; Cho, Kyu-Jin
Calibrating a Pair of Inertial Sensors at Opposite Ends 11:39- of an Imperfect Kinematic Chain Spatial Parallel Soft Robotic Architectures Precise Vision-Aided Aerial Navigation 5 11:42 Birbach, Oliver; Bäuml, Berthold Rivera, Jordan; Kim, Charles Chiu, Han-Pang; Das, Aveek; Miller, Philip; Samarasekera, Supun; Kumar, Rakesh
Extrinsic calibration of a set of range cameras in 5 Whole Arm Planning for a Soft and Highly Compliant Real-Time Autonomous 3D Navigation for Tracked 11:42- seconds without any pattern 2D Robotic Manipulator Vehicles in Rescue Environments 6 11:45 Fernández-Moral, Eduardo; González-Jiménez, Marchese, Andrew; Katzschmann, Robert; Rus, Menna, Matteo; Gianni, Mario; Ferri, Federico; Pirri, Javier; Rives, Patrick; Arevalo, Vicente Daniela Fiora
Extrinsic Calibration of Non-Overlapping Camera- Interactive Navigation of Humans from a Game Laser System Using Structured Environment An Untethered Jumping Soft Robot Theoretic Perspective 11:45- 7 Bok, Yunsu; Choi, Dong - Geol; Vasseur, Pascal; Tolley, Michael Thomas; Shepherd, Robert; Karpelson, Turnwald, Annemarie; Olszowy, Wiktor; Wollherr, Dirk; 11:48 Kweon, In So Michael; Bartlett, Nicholas; Galloway, Kevin; Wehner, Buss, Martin Michael; Nunes, Rui; Whitesides, George; Wood, Robert Magnetometer Bias Calibration Based on Relative Angular Position: Theory and Experimental Motion Pattern Discrimination for Soft Robots with 11:48- Comparative Evaluation Morphologically Flexible Sensors Layered Costmaps for Context-Sensitive Navigation 8 11:51 Troni, Giancarlo; Eustice, Ryan Culha, Utku; Wani, Umar; Nurzaman, Surya G.; Lu, David V.; Hershberger, Dave; Smart, William Clemens, Frank; Iida, Fumiya
An Active Compliant Control Mode for Interaction with Omnidirectional 3D Reconstruction in Augmented 11:51- Automatic Calibration of RGBD and Thermal Cameras a Pneumatic Soft Robot Manhattan Worlds 9 11:54 Lussier, Jake; Thrun, Sebastian Queisser, Jeffrey; Neumann, Klaus; Rolf, Matthias; Schönbein, Miriam; Geiger, Andreas Reinhart, Rene Felix; Steil, Jochen J.
Spatio-Temporal Laser to Visual/Inertial Calibration Conformable Actuation and Sensing with Robotic Semantic Mapping for Object Category and Structural 11:54- with Applications to Hand-Held, Large Scale Scanning Fabric Class 10 11:57 Rehder, Joern; Furgale, Paul Timothy; Beardsley, Yuen, Michelle; Cherian, Arun; Case, Jennifer; Seipel, Zhao, Zhe; Chen, Xiaoping Paul; Siegwart, Roland Justin; Kramer, Rebecca
Kinematics of a New Class of Smart Actuators for Soft Robots Based on Generalized Pneumatic Artificial Anytime Navigation with Progressive Hindsight 11:57- A Catadioptric Extension for RGB-D Cameras Muscles Optimization 11 12:00 Endres, Felix; Sprunk, Christoph; Kuemmerle, Rainer; Krishnan, Girish Godoy, Julio; Karamouzas, Ioannis; Guy, Stephen J.; Burgard, Wolfram Gini, Maria
56 Monday Session B, 11:10 - 12:30 (Continued) Grand Ballroom State Ballroom Red Lacquer Room MoB1 MoB2 MoB3
# Time Kinematics and Mechanism Design I Robot Learning I Visual Servoing
A Dual-Motor Robot Joint Mechanism with Epicyclic Unsupervised and Online Non-Stationary Obstacle 6D Image-Based Visual Servoing for Robot 12:00- Gear Train Discovery and Modeling Using a Laser Range Finder Manipulators with uncalibrated Stereo Cameras 12 12:03 Babin, Vincent; Gosselin, Clement; Allan, Jean- Duceux, Guillaume; Filliat, David Cai, Caixia; Dean Leon, Emmanuel; Somani, Nikhil; Francois Knoll, Alois
Kinematic Design and Analysis for a Macaque Upper- Mutual Learning of an Object Concept and Language Weakly Calibrated Stereoscopic Visual Servoing for 12:03- Limb Exoskeleton with Shoulder Joint Alignment Model Based on MLDA and NPYLM Laser Steering: Application to Microphonosurgery 13 12:06 Haninger, Kevin; Lu, Junkai; Chen, Wenjie; Tomizuka, Nakamura, Tomoaki; Nagai, Takayuki; Funakoshi, TAMADAZTE, Brahim; Andreff, Nicolas Masayoshi Kotaro; Nagasaka, Shogo; Taniguchi, Tadahiro; Iwahashi, Naoto
Object Manifold Learning with Action Features for Novel Two-Stage Control Scheme for Robust 12:06- An Alternative Approach to Robot Safety Active Tactile Object Recognition Constrained Visual Servoing 14 12:09 Parmiggiani, Alberto; Randazzo, Marco; Natale, Tanaka, Daisuke; Matsubara, Takamitsu; Ichien, Assa, Akbar; Janabi-Sharifi, Farrokh Lorenzo; Metta, Giorgio Kentaro; Sugimoto, Kenji
On the Performance Evaluation and Analysis of Entropy Based Strategies for Physical Exploration of Lyapunov-Stable Eye-In-Hand Kinematic Visual 12:09- General Robots with Mixed DoFs the Environment's Degrees of Freedom Servoing with Unstructured Static Feature Points 15 12:12 SHAYYA, Samah; Krut, Sebastien; Company, Olivier; Otte, Stefan; Kulick, Johannes; Toussaint, Marc; Navarro-Alarcon, David; Liu, Yunhui Baradat, Cédric; Pierrot, François Brock, Oliver
Closed-Loop Inverse Kinematics under Inequality Constraints: Application to Concentric-Tube Knowledge Propagation and Relation Learning for A Sequence of Micro-Assembly for Irregular Objects 12:12- Manipulators Predicting Action Effects Based on a Multiple Manipulator Platform 16 12:15 Azimian, Hamidreza; Looi, Thomas; Drake, James Szedmak, Sandor; Ugur, Emre; Piater, Justus Xing, Dengpeng; Xu, De; Li, Hai peng
Novel Three-DOF Ankle Mechanisms for Lower-Limb Visual Servoing Based Trajectory Tracking of Exoskeleton: Kinematic Analysis and Design of Learning to Reach into the Unknown: Selecting Initial Underactuated Water Surface Robots without Direct 12:15- Passive-Type Ankle Module Conditions When Reaching in Clutter Position Measurement 17 12:18 Hong, Man Bok; Shin, Young June; Wang, Ji-Hyeun PARK, DAEHYUNG; Kapusta, Ariel; Kim, You Keun; WANG, Kai; Liu, Yunhui; Li, Luyang Rehg, James; Kemp, Charlie
Robust Solution of Prioritized Inverse Kinematics Learning Haptic Representation for Manipulating Image Jacobian Estimation Using Structure from 12:18- Based on Hestenes-Powell Multiplier Method Deformable Food Objects Motion on a Centralized Point 18 12:21 Sugihara, Tomomichi Gemici, Mevlana Celaleddin; Saxena, Ashutosh Nevarez, Victor; Lumia, Ron
Analytical Inverse Kinematic Solution for Modularized A Neural Dynamics Architecture for Grasping That 7-DoF Redundant Manipulators with Offsets at Integrates Perception and Movement Generation and 12:21- Shoulder and Wrist Enables On-Line Updating Vision Guided Robotic Block Stacking 19 12:24 Luo, Ren; Lin, Tsung-Wei; Tsai, Yun-Hsuan Knips, Guido; Zibner, Stephan Klaus Ulrich; Reimann, Macias, Nate; Wen, John Hendrik; Popova, Irina; Schöner, Gregor
A Flexible and Robust Robotic Arm Design and Skill Control in the Reliable Region of a Statistical Model 12:24- Learning by Using Recurrent Neural Networks with Gaussian Process Regression A Two Phase RGB-D Visual Servoing Controller 20 12:27 Tan, Boon Hwa; Tang, Huajin; Yan, Rui; Tani, Jun Yun, Youngmok; Deshpande, Ashish Hojaij, Abdullah; Zelek, John S.; Asmar, Daniel
Confidence-Based Roadmap Using Gaussian Process 12:27- Sponsor Talk: The da Vinci Xi Surgical System Regression for a Robot Control Pose Error Correction For Visual Features Prediction 21 12:30 DiMaio, Simon P. Okadome, Yuya; Nakamura, Yutaka; URAI, Kenji; Cazy, Nicolas; Dune, Claire; Wieber, Pierre-Brice; Intuitive Surgical Nakata, Yoshihiro; Ishiguro, Hiroshi Robuffo Giordano, Paolo; Chaumette, Francois
57 Monday Session C, 13:50 - 15:10 Grand Ballroom State Ballroom Red Lacquer Room MoC1 MoC2 MoC3 Micro-Nano Robots I & Humanoids and Bipeds I & Bioinspired Robots II & Manipulation and Grasping II Computer Vision I Distributed Robotics
Chair Brock, Oliver (TU Berlin) Dillmann, Rüdiger (Karlsruhe Institute of Technology) Hsieh, M. Ani (Drexel University)
# Time Session Keynote Session Keynote Session Keynote Keynote: Micro and Nano Robotics for Biomedical 13:50- Innovations Keynote: What is a humanoid robot good for? Keynote: From Biology to Robot and Back 1 14:10 Arai, Fumihito Yokoi, Kazuhito Choset, Howie Nagoya University AIST Carnegie Mellon University
Micro-Nano Robots I Humanoids and Bipeds I Bioinspired Robots II
Three Dimensional Multi-Cell Spheroids Assembly Compliance Computation for Continuum Types of 14:10- Using Thermoresponsive Gel Probe Identification of HRP-2 Foot's Dynamics Robots 2 14:13 Takeuchi, Masaru; Nakajima, Masahiro; Fukuda, Mikami, Yuya; Moulard, Thomas; Yoshida, Eiichi; Smoljkic, Gabrijel; Reynaerts, Dominiek; Vander Toshio; Hasegawa, Yasuhisa Venture, Gentiane Sloten, Jos; Vander Poorten, Emmanuel B
Construction of Vascular-like Microtubes via Fluidic Axis-translation Self-assembly based on Multiple Integration of Non-Inclusive Contacts in Posture Multiport Modeling of Force and Displacement in 14:13- Hydrogels Generation Elastic Transmissions for Underactuated Hands 3 14:16 Yue, Tao; Nakajima, Masahiro; Takeuchi, Masaru; Brossette, Stanislas; Escande, Adrien; Vaillant, Joris; Martell, Michael; Schultz, Joshua Huang, Qiang; Fukuda, Toshio Keith, François; Moulard, Thomas; Kheddar, Abderrahmane
Magnetic Actuation of Ultra-Compliant Micro Robotic 3D Dynamics of Bipedal Running: Effects of Step iSplash-II: Realizing Fast Carangiform Swimming to 14:16- Mechanisms Width on an Amputee-Inspired Robot Outperform a Real Fish 4 14:19 Vogtmann, Dana; Bergbreiter, Sarah Sullivan, Timothy; Seipel, Justin Clapham, Richard James; Hu, Huosheng
Selective and Rapid Cell Injection of Fluorescence Sensor Encapsulated in Liposome Using Optical Control of Zeta Potential and Local Vibration Stimulus Lyapunov Stability Margins for Humanoid Robot Multi-Functional Bio-Inspired Leg for Underwater 14:19- 5 by Optical Tweezers Balancing Robots 14:22 Maruyama, Hisataka; Masuda, Taisuke; Ryu, heng Spyrakos-Papastavridis, Emmanouil; Perrin, Nicolas Kim, Hee Joong; Jun, Bong Huan; Lee, Jihong jun; Arai, Fumihito Yves; Tsagarakis, Nikolaos; Dai, Jian; Caldwell, Darwin G.
Real-Time LOC-based Morphological Cell Analysis 14:22- System Using High-Speed Vision State Estimation for a Humanoid Robot Torque Control Strategies for Snake Robots 6 14:25 Gu, Qingyi; Aoyama, Tadayoshi; Takaki, Takeshi; Ishii, Rotella, Nicholas; Bloesch, Michael; Righetti, Ludovic; Rollinson, David; Alwala, Kalyan Vasudev; Zevallos, Idaku; Takemoto, Ayumi; Sakamoto, Naoaki Schaal, Stefan Nico; Choset, Howie
Noncontact Fine Alignment for Multiple Microcontact Sideward Locomotion Control of Biped Robots Based 14:25- Printing on Dynamics Morphing A 3D Motion Planning Framework for Snake Robots 7 14:28 Tanaka, Nobuyuki; Ota, Hiroki; Fukumori, Kazuhiro; Atsuta, Hiroshi; Sugihara, Tomomichi Liljebäck, Pål; Pettersen, Kristin Y.; Stavdahl, Øyvind; Yamato, Masayuki; Okano, Teruo; Miyake, Jun Gravdahl, Jan Tommy
Study on Rotational and Unclogging Motions of Modular Low-Cost Humanoid Platform for Disaster Human Control of Robot Swarms with Dynamic 14:28- Magnetic Chain-Like Microrobot Response Leaders 8 14:31 Belharet, Karim; Folio, David; Ferreira, Antoine Yi, Seung-Joon; McGill, Stephen; Vadakedathu, Larry; Walker, Phillip; Amirpour Amraii, Saman; Lewis, He, Qin; Ha, Inyong; Rouleau, Michael; Hong, Dennis; Michael; Chakraborty, Nilanjan; Sycara, Katia Lee, Daniel D. Development of Chemical Stimulation System for Local Environment Control by Using Combination of Perception and Control Strategies for Driving Utility Snakes on an Inclined Plane: Learning an Adaptive 14:31- Spout and Suction from Dual Pipettes Vehicles with a Humanoid Robot Sidewinding Motion for Changing Slopes 9 14:34 Motoyoshi, Takahiro; Kojima, Masaru; Ohara, Kenichi; Rasmussen, Christopher; Sohn, Kiwon; Wang, Gong, Chaohui; Tesch, Matthew; Rollinson, David; Horade, Mitsuhiro; Kamiyama, Kazuto; Mae, Yasushi; Qiaosong; Oh, Paul Y. Choset, Howie Arai, Tatsuo
A Stick-Slip Omnidirectional Powertrain for Low-Cost Balancing experiments on a torque-controlled Flapping Actuator Inspired by Lepidotrichia of Ray- 14:34- Swarm Robotics: Mechanism, Calibration, and Control humanoid with hierarchical inverse dynamics Finned Fishes 10 14:37 Klingner, John; Kanakia, Anshul; Farrow, Nicholas; Herzog, Alexander; Righetti, Ludovic; Grimminger, Sekar, Karthik Srivatsa; Triantafyllou, Michael; Valdivia Reishus, Dustin; Correll, Nikolaus Felix; Pastor, Peter; Schaal, Stefan y Alvarado, Pablo
Non-Vector Space Stochastic Control for Nano Dynamic State Estimation Using Quadratic Design and Implementation of a Low Cost, Pump- 14:37- Robotic Manipulations Programming Based, Depth Control of a Small Robotic Fish 11 14:40 Zhao, Jianguo; Song, Bo; Xi, Ning Xinjilefu, X; Feng, Siyuan; Atkeson, Christopher Makrodimitris, Michail; Aliprantis, Ioannis; Papadopoulos, Evangelos
58 Monday Session C, 13:50 - 15:10 (Continued) Grand Ballroom State Ballroom Red Lacquer Room MoC1 MoC2 MoC3
# Time Manipulation and Grasping II Computer Vision I Distributed Robotics
Task Specific Robust Grasping for Multifingered Robot "Look at This!" Learning to Guide Visual Saliency in Distributed Management and Representation of Data 14:40- Hands Human-Robot Interaction and Context in Robotic Applications 12 14:43 Boutselis, George; Bechlioulis, Charalampos; Schauerte, Boris; Stiefelhagen, Rainer Dietrich, André; Zug, Sebastian; Mohammad, Siba; Liarokapis, Minas; Kyriakopoulos, Kostas Kaiser, Jörg
Achieving Elastic Stability of Concentric Tube Robots SuperFAST: Model-Based Adaptive Corner Detection Environment-independent Formation Flight for Micro 14:43- through Optimization of Tube Precurvature for Scalable Robotic Vision Aerial Vehicles 13 14:46 Ha, Junhyoung; Park, Frank; Dupont, Pierre Florentz, Gaspard; Aldea, Emanuel Naegeli, Tobias; Conte, Christian; domahidi, alexander; Morari, Manfred; Hilliges, Otmar
Auto-Adjusting Camera Exposure for Outdoor 14:46- Cable Stiffened Flexible Link Manipulator Robotics Using Gradient Information Rapid Multirobot Deployment with Time Constraints 14 14:49 Dixit, Rahul; Kumar, R Prasanth Shim, Inwook; Lee, Joon-Young; Kweon, In So Carpin, Stefano; Pavone, Marco; Sadler, Brian
Robotic Handwriting: Multi-Contact Manipulation A Distributed Optimal Strategy for Rendezvous of Multi- 14:49- Based on Reactional Internal Contact Hypothesis SLAM with Object Discovery, Modeling and Mapping Robots with Random Node Failures 15 14:52 Kim, Sung-Kyun; Jo, Joonhee; Oh, Yonghwan; Oh, Choudhary, Siddharth; Trevor, Alexander J B; Park, Hyongju; Hutchinson, Seth Sang-Rok; Srinivasa, Siddhartha; Likhachev, Maxim Christensen, Henrik Iskov; Dellaert, Frank
Distributed Cohesive Configuration Control for Swarm Cooperative Suspended Object Manipulation Using Robots with Boundary Information and Network 14:52- Reinforcement Learning and Energy-Based Control Real-Time Sequential Model-Based Non-Rigid SFM Sensing 16 14:55 Palunko, Ivana; Donner, Philine; Buss, Martin; Hirche, Bronte, Sebastian; Paladini, Marco; Bergasa, Luis Lee, Seoung Kyou; McLurkin, James Sandra Miguel; Agapito, Lourdes; Arroyo, Roberto
Direct Superpixel Labeling for Mobile Robot Robotic Dual Probe Setup for Reliable Pick and Place Navigation Using Learned General Optical Flow Decentralized and Complete Multi-Robot Motion 14:55- Processing on the Nanoscale Using Haptic Devices Templates Planning in Confined Spaces 17 14:58 Tiemerding, Tobias; Zimmermann, Soeren; Fatikow, Roberts, Richard; Dellaert, Frank Wiktor, Adam; Scobee, Dexter; Messenger, Sean; Sergej Clark, Christopher M.
Optimal Parameter Identification for Discrete Mechanical Systems with Application to Flexible A Directional Visual Descriptor for Large-Scale Mobile Robotic Wireless Sensor Networks for Efficient 14:58- Object Manipulation Coverage Problems Spatial Prediction 18 15:01 Caldwell, Timothy; Coleman, David; Correll, Nikolaus Tamassia, Marco; Farinelli, Alessandro; Murino, Nguyen, Linh Van; Kodagoda, Sarath; Ranasinghe, Vittorio; Del Bue, Alessio Ravindra; Dissanayake, Gamini
Real-Time Pose Estimation of Deformable Objects Improving Data Ferrying by Iteratively Learning the 15:01- The Joint Coordination in Reach-To-Grap Movements Using a Volumetric Approach Radio Frequency Environment 19 15:04 Li, Zhi; Gray, Kierstin; Roldan, Jay Ryan; Milutinovic, Li, Yinxiao; Wang, Yan; Case, Michael; Chang, Shih- Carfang, Anthony; Wagle, Neeti; Frew, Eric W. Dejan; Rosen, Jacob Fu; Allen, Peter
A Robot System Design for Low-Cost Multi-Robot PAS: Visual Odometry with Perspective Alignment A Cooperative Formation Control Strategy Maintaining Manipulation Search Connectivity of a Multi-Agent System McLurkin, James; McMullen, Adam; Robbins, Richardson, Andrew; Olson, Edwin Dutta, Rajdeep; Sun, Liang; Kothari, Mangal; Sharma, 15:04- Nicholas; Habibi, Golnaz; Becker, Aaron; Chou, Alvin; Rajnikant; Pack, Daniel 20 15:07 Li, Hao; John, Meagan; Okeke, Nnena; Rykowski, Joshua; Kim, Sunny; Xie, William; Taylor, Vaughn; Zhou, Yu; Shen, Hsin-Yu Jennifer; Chen, Nelson; Kaseman, Quillan; Langford, Lindsay; Hunt, Jeremy; Boone, Amanda; Koch, Kevin Koch
Declarative Specification of Task-Based Grasping with Planar Building Facade Segmentation and Mapping Interactive Augmented Reality for Understanding and 15:07- Constraint Validation Using Appearance and Geometric Constraints Analyzing Multi-Robot Systems 21 15:10 Schneider, Sven; Hochgeschwender, Nico; Lee, Joseph; Lu, Yan; Song, Dezhen Ghiringhelli, Fabrizio; Guzzi, Jerome; Di Caro, Gianni Kraetzschmar, Gerhard A.; caglioti, vincenzo; Gambardella, Luca; Giusti, Alessandro
59 Monday Session D, 15:20 - 16:40 Grand Ballroom State Ballroom Red Lacquer Room MoD1 MoD2 MoD3 Haptics & Human-Robot Interaction I & Formal Methods & Surgical Robotics I Robot Learning II Software and Architecture
Chair Xiao, Jing (UNC-Charlotte) De Luca, Alessandro (Sapienza University of Rome) Tumova, Jana (Royal Institute of Technology)
# Time Session Keynote Session Keynote Session Keynote Keynote: Overview of Motor Interaction with Robots 15:20- Keynote: Haptics in Robot-Assisted Surgery and Other Humans Keynote: Formal methods in robotics 1 15:40 Okamura, Allison M. Burdet, Etienne Pappas, George J. Stanford University Imperial College London University of Pennsylvania
Haptics Human-Robot Interaction I Formal Methods
Steering of Flexible Needles Combining Kinesthetic A Peer Pressure Experiment: Recreation of the Asch A Compositional Approach to Stochastic Optimal 15:40- and Vibratory Force Feedback Conformity Experiment with Robots Control with Co-safe Temporal Logic Specifications 2 15:43 Pacchierotti, Claudio; Abayazid, Momen; Misra, Brandstetter, Jürgen; Racz, Peter; Beckner, Clayton; Horowitz, Matanya; Wolff, Eric; Murray, Richard Sarthak; Prattichizzo, Domenico Sandoval, Eduardo; Hay, Jennifer; Bartneck, Christoph Inverse Reinforcement Learning Algorithms and Touch Attention Bayesian Models for Robotic Active Features for Robot Navigation in Crowds: An Formal Verification of Maneuver Automata for 15:43- Haptic Exploration of Heterogeneous Surfaces Experimental Comparison Parameterized Motion Primitives 3 15:46 Martins, Ricardo; Ferreira, João Filipe; Dias, Jorge Vasquez, Dizan; Okal, Billy; Arras, Kai Oliver Heß, Daniel; Althoff, Matthias; Sattel, Thomas
Design and Evaluation of a 1DoF ERF-Based Needle Extraction of Person-Specific Motion Style Based on a How Behavior Trees Modularize Robustness and 15:46- Insertion Haptic Platform Task Model and Imitation by Humanoid Robot Safety in Hybrid Systems 4 15:49 Graña Sanchez, Adrian; Sanchez Secades, Luis Okamoto, Takahiro; Shiratori, Takaaki; Glisson, Colledanchise, Michele; Ogren, Petter Alonso; Zemiti, Nabil; Poignet, Philippe Matthew; Yamane, Katsu; Kudoh, Shunsuke; Ikeuchi, Katsushi Haptic-Enabled Teleoperation of Base-Excited Determining Proper Grasp Configurations for Hydraulic Manipulators Applied to Live-Line Handovers through Observation of Object Movement Verification and Testing of Mobile Robot Navigation 15:49- Maintenance Patterns and Inter-Object Interactions During Usage Algorithms: A Case Study in SPARK 5 15:52 Banthia, Vikram; Maddahi, Yaser; Balakrishnan, Chan, Wesley Patrick; Kakiuchi, Yohei; Okada, Kei; Trojanek, Piotr; Eder, Kerstin Subramaniam; Sepehri, Nariman Inaba, Masayuki
A Mixed-Initiative Control System for an Aerial Service Using Spatial Language to Drive a Robot for an Indoor 15:52- Vehicle Supported by Force Feedback Environment Fetch Task Verifying and Validating Multirobot Missions 6 15:55 Cacace, Jonathan; Finzi, Alberto; Lippiello, Vincenzo Huo, Zhiyu; Alexenko, Tatiana; Skubic, Marjorie Lyons, Damian; Arkin, Ronald; Jiang, Shu; Harrington, Dagan; Liu, Tsung-Ming
Design of a Bladder Based Elastomeric Smart Shoe Speech-Based Human-Robot Interaction Robust to 15:55- for Haptic Terrain Display Acoustic Reflections in Real Environment Maximally Satisfying LTL Action Planning 7 15:58 Wang, Yue; Minor, Mark Gomez, Randy; Inoue, Koji; Nakamura, Keisuke; Tumova, Jana; Marzinotto, Alejandro; Dimarogonas, Mizumoto, Takeshi; Nakadai, Kazuhiro Dimos V.; Kragic, Danica
Contact Force Decomposition Using Tactile Head-Eyes System and Gaze Analysis of the Optimal and Dynamic Planning for Markov Decision Information for Haptic Augmented Reality Humanoid Robot Romeo Processes with Co-Safe LTL Specifications 15:58- 8 Kim, Hyoungkyun; Choi, Seungmoon; Chung, Wan Pateromichelakis, Nikolaos; Mazel, Alexandre; Hache, Lacerda, Bruno; Parker, David; Hawes, Nick 16:01 Kyun Marc-Antoine; KOUMPOGIANNIS, Thomas; Gelin, Rodolphe; MAISONNIER, Bruno; Berthoz, Alain
RoboPuppet: Low-Cost, 3D Printed Miniatures for Development of a Rehabilitation Robot Suit with SafeRobots: A Model-Driven Framework for 16:01- Teleoperating Full-Size Robots Velocity and Torque-Based Mechanical Safety Devices Developing Robotic Systems 9 16:04 Eilering, Anna; Franchi, Giulia; Hauser, Kris Kai, Yoshihiro; KITAGUCHI, Satoshi; Kanno, Shotaro; Ramaswamy, Arunkumar; Monsuez, Bruno; Tapus, Zhang, Wenlong; Tomizuka, Masayoshi Adriana
Modeling and Controller Design of Cooperative Haptic Exploration of Unknown Surfaces with Robots in Workspace Sharing Human-Robot Automated Composition of Motion Primitives for Multi- 16:04- Discontinuities Assembly Teams Robot Systems from Safe LTL Specifications 10 16:07 Jamisola, Jr., Rodrigo S.; Kormushev, Petar; Bicchi, Liu, Changliu; Tomizuka, Masayoshi Saha, Indranil; Ramaithitima, Rattanachai; Kumar, Antonio; Caldwell, Darwin G. Vijay; Pappas, George J.; Seshia, Sanjit A.
The Patched Intrinsic Tactile Object: A Tool to Adjutant: A Framework for Flexible Human-Machine A Stable Switched-System Approach to Obstacle 16:07- Investigate Human Grasps Collaborative Systems Avoidance for Mobile Robots in SE(2) 11 16:10 Serio, Alessandro; Riccomini, Emanuele; Tartaglia, Guerin, Kelleher; Riedel, Sebastian Danilo; Bohren, Jin, JingFu; Green, Adrian; Gans, Nicholas (Nick) Vincenzo; Sarakoglou, Ioannis; Gabiccini, Marco; Jonathan; Hager, Gregory Tsagarakis, Nikolaos; Bicchi, Antonio
60 Monday Session D, 15:20 - 16:40 (Continued) Grand Ballroom State Ballroom Red Lacquer Room MoD1 MoD2 MoD3
# Time Surgical Robotics I Robot Learning II Software and Architecture Etasl/etc: A Constraint-Based Task Specification Workspace Characterization for Concentric Tube Efficient Policy Search with a Parameterized Skill Language and Robot Controller Using Expression 16:10- Continuum Robots Memory Graphs 12 16:13 Burgner-Kahrs, Jessica; Gilbert, Hunter B.; Granna, Reinhart, Rene Felix; Steil, Jochen J. Aertbelien, Erwin; De Schutter, Joris Josephine; Swaney, Philip J.; Webster III, Robert James
Preliminary Evaluation of a New Microsurgical Robotic Simultaneous On-Line Discovery and Improvement of Robot Task Commander: A Framework and IDE for 16:13- System for Head and Neck Surgery Robotic Skill Options Robot Application Development 13 16:16 Olds, Kevin; Chalasani, Preetham; Pacheco-Lopez, Stulp, Freek; Herlant, Laura; Hoarau, Antoine; Raiola, Hart, Stephen; Dinh, Paul; Yamokoski, John; Paulette; Iordachita, Iulian; Akst, Lee; Taylor, Russell Gennaro Wightman, Brian; Radford, Nicolaus H. Dimensionality Reduction and Motion Coordination in Surgical Structured Light for 3D Minimally Invasive Learning Trajectories with Dynamic Movement Enhancing Software Module Reusability Using Port 16:16- Surgical Imaging Primitives Plug-Ins: An Experiment with the iCub Robot 14 16:19 Reiter, Austin; Sigaras, Alexandros; Fowler, Dennis; Colomé, Adrià; Torras, Carme Paikan, Ali; Tikhanoff, Vadim; Metta, Giorgio; Natale, Allen, Peter Lorenzo
Cooperative Teleoperation with Projection-Based OrigamiBot-I: A Thread-Actuated Origami Robot for Simple Concurrency for Robotics with the Roboscoop 16:19- Force Reflection for MIS Manipulation and Locomotion Framework 15 16:22 Takhmar, Amir; Polushin, Ilia G.; Talasaz, Ali; Patel, Vander Hoff, Evan; Jeong, Donghwa; Lee, Kiju Rusakov, Andrey; Shin, Jiwon; Meyer, Bertrand Rajnikant V.
Design of a Unified Active Locomotion Mechanism for Decoding Surface Electromyogram into Dynamic State A Lightweight, Cross-Platform, Multiuser Robot 16:22- a Wireless Laparoscopic Camera System to Extract Dynamic Motor Control Strategy of Human Visualization Using the Cloud 16 16:25 Liu, Xiaolong; Mancini, Gregory; Tan, Jindong Park, Seongsik; Chung, Wan Kyun Hilton, William; Lofaro, Daniel; Kim, Youngmoo
Toward Automated Intraocular Laser Surgery Using a ReFrESH: A Self-Adaptation Framework to Support 16:25- Handheld Micromanipulator Latent Space Policy Search for Robotics Fault Tolerance in Field Mobile Robots 17 16:28 Yang, Sungwook; MacLachlan, Robert A.; Riviere, Luck, Kevin Sebastian; Neumann, Gerhard; Berger, Cui, Yanzhe; Voyles, Richard; Lane, Joshua; Mahoor, Cameron N. Erik; Peters, Jan; Ben Amor, Heni Mohammad
Speeding up Rao-Blackwellized Particle Filter SLAM 16:28- Quasi-Static Modeling of the Da Vinci Instrument Learning of Closed-Loop Motion Control with a Multithreaded Architecture 18 16:31 Anooshahpour, Farshad; Polushin, Ilia G.; Patel, Farshidian, Farbod; Neunert, Michael; Buchli, Jonas Gouveia, Bruno; Portugal, David; Marques, Lino Rajnikant V.
Design and Evaluation of a Novel Flexible Robot for Unsupervised Learning Approach to Attention-Path Developing Virtual Testbeds for Intelligent Robot 16:31- Transluminal and Endoluminal Surgery Planning for Large-Scale Environment Classification Manipulators - an Erobotics Approach 19 16:34 Seneci, Carlo Alberto; Shang, Jianzhong; Leibrandt, LEE, Hosun; Jeong, Sungmoon; Chong, Nak Young Guiffo Kaigom, Eric; Rossmann, Juergen Konrad; Vitiello, Valentina; Patel, Nisha; Darzi, Ara; Teare, Julian; Yang, Guang-Zhong
Design of a Spine-Inspired Kinematic for the Guidance Automatic Channel Selection and Neural Signal Crowdsourcing As a Methodology to Obtain Large and 16:34- of Flexible Instruments in Minimally Invasive Surgery Estimation across Channels of Neural Probes Varied Robotic Data Sets 20 16:37 Traeger, Mattias Felix; Roppenecker, Daniel B.; Vysotska, Olga; Frank, Barbara; Istvan, Ulbert; Paul, de Croon, Guido; Gerke, Paul; Sprinkhuizen-Kuyper, Leininger, Matthias R.; Schnoes, Florian; Lueth, Tim Oliver; Ruther, Patrick; Stachniss, Cyrill; Burgard, Ida C. Wolfram
Hybrid Control of Master-Slave Velocity Control and Fast Planning of Well Conditioned Trajectories for 16:37- Admittance Control for Safe Remote Surgery Model Learning 21 16:40 Osa, Takayuki; Uchida, Satoshi; Sugita, Naohiko; Wang, Cong; Zhao, Yu; Lin, Chung-Yen; Tomizuka, Mitsuishi, Mamoru Masayoshi
61 Tuesday Session A, 09:00 - 10:20 Grand Ballroom State Ballroom Red Lacquer Room TuA1 TuA2 TuA3 Manipulation and Grasping III & Motion and Path Planning II & Search, Rescue, and Audition & Parallel Robotics Localization and Mapping II Field Robotics
Chair Guglielmelli, Eugenio (Universita' Campus Bio-Medico) LaValle, Steven M (University of Illinois) Tadokoro, Satoshi (Tohoku University)
# Time Session Keynote Session Keynote Session Keynote Keynote: Grasping and Manipulation by Humans and Keynote: Sampling-Based Planning: Foundations & Keynote: Lessons Learned in Field Robotics from 09:00- by Robots Applications Disasters 1 09:20 Brock, Oliver Amato, Nancy Murphy, Robin TU Berlin Texas A&M Texas A&M
Manipulation and Grasping III Motion and Path Planning II Search, Rescue, and Audition Characterization of the Precision Manipulation Proactive Kinodynamic Planning using the Extended The Response Robotics Summer School 2013: Capabilities of Robot Hands via the Continuous Group Social Force Model and Human Motion Prediction in Bringing Responders and Researchers Together to 09:20- of Displacements Urban Environments Advance Response Robotics 2 09:23 Rojas, Nicolas; Dollar, Aaron Ferrer, Gonzalo; Sanfeliu, Alberto Sheh, Raymond Ka-Man; Collidge, Bill; Lazarescu, Mihai; Komsuoglu, Haldun; Jacoff, Adam
An Automatic Approach for the Generation of the Design of a Hybrid Exploration Robot for Air and Land Encoderless Robot Motion Control Using Vision Roadmap for Multi-AGV Systems in an Industrial Deployment (H.E.R.A.L.D) for Urban Search and 09:23- Sensor and Back Electromotive Force Environment Rescue Applications 3 09:26 Kawamura, Akihiro; Tachibana, Miyako; Yamate, Digani, Valerio; Sabattini, Lorenzo; Secchi, Cristian; Latscha, Stella; Kofron, Michael; Stroffolino, Anthony; Soichiro; Kawamura, Sadao Fantuzzi, Cesare Davis, Lauren; Merritt, Gabrielle; Piccoli, Matthew; Yim, Mark Approaches to Robotic Teleoperation in a Disaster Humanoid Compliant Whole Arm Dexterous Recursive Non-Uniform Coverage of Unknown Scenario: From Supervised Autonomy to Direct Manipulation: Control Design and Experiments Terrains for UAVs Control 09:26- Wimboeck, Thomas; Florek - Jasinska, Monika; Ott, Sadat, Abbas; Wawerla, Jens; Vaughan, Richard Katyal, Kapil; Brown, Christopher; Hechtman, Steven 4 09:29 Christian A.; Para, Matthew; McGee, Timothy G.; Wolfe, Kevin; Murphy, Ryan Joseph; Kutzer, Michael Dennis Mays; Tunstel, Edward; Mcloughlin, Michael; Johannes, Matthew Analyzing Human Fingertip Usage in Dexterous Precision Manipulation: Implications for Robotic Finger Path Planning with Stability Uncertainty for Articulated Remote Vertical Exploration by Active Scope Camera 09:29- Design Mobile Vehicles in Challenging Environments into Collapsed Buildings 5 09:32 Bullock, Ian; Feix, Thomas; Dollar, Aaron Norouzi, Mohammad; Valls Miro, Jaime; Dissanayake, Junichi, Fukuda; Konyo, Masashi; Takeuchi, Eijiro; Gamini; Vidal-Calleja, Teresa A. Tadokoro, Satoshi
Estimation of Ground Surface Radiation Sources from Adaptive Under-Actuated Anthropomorphic Hand: ISR- Closed-Loop Global Motion Planning for Reactive Dose Map Measured by Moving Dosimeter and 3D 09:32- SoftHand Execution of Learned Tasks Map 6 09:35 Tavakoli, Mahmoud; de Almeida, Anibal Bowen, Chris; Alterovitz, Ron Minamoto, Gaku; Takeuchi, Eijiro; Tadokoro, Satoshi
Coordinated Motion Control of a Nonholonomic Mobile Making a Robot Dance to Diverse Musical Genre in 09:35- Manipulator for Accurate Motion Tracking An Empirical Study of Optimal Motion Planning Noisy Environments 7 09:38 Jia, Yunyi; Xi, Ning; Cheng, Yu; Liang, Siyang Luo, Jingru; Hauser, Kris Oliveira, João Lobato; Nakamura, Keisuke; Langlois, Thibault; Gouyon, Fabien; Nakadai, Kazuhiro; Lim, Angelica; Reis, Luís Paulo; Okuno, Hiroshi G.
Hierarchical Fingertip Space for Multi-Fingered The Lion and Man Game on Polyhedral Surfaces with Improvement in Outdoor Sound Source Detection 09:38- Precision Grasping Boundary Using a Quadrotor-Embedded Microphone Array 8 09:41 Hang, Kaiyu; Stork, Johannes Andreas; Kragic, Noori, Narges; Isler, Volkan Ohata, Takuma; Nakamura, Keisuke; Mizumoto, Danica Takeshi; Tezuka, Taiki; Nakadai, Kazuhiro
Modeling of Skid-Steer Mobile Manipulators Using Visualization of auditory awareness based on sound Spatial Vector Algebra and Experimental Validation Motion Planning under Uncertainty for Medical Needle source positions estimated by depth sensor and 09:41- with a Compact Loader Steering Using Optimization in Belief Space microphone array 9 09:44 Aguilera, Sergio; Torres-Torriti, Miguel; Auat Cheein, Sun, Wen; Alterovitz, Ron Iyama, Takahiro; Sugiyama, Osamu; Otsuka, Takuma; Fernando Itoyama, Katsutoshi; Okuno, Hiroshi G.
Physically-Consistent Sensor Fusion in Contact-Rich A Sampling-Based Algorithm for Multi-Robot Visibility- Rapidly Learning Musical Beats in the Presence of 09:44- Behaviors Based Pursuit-Evasion Environmental and Robot Ego Noise 10 09:47 Lowrey, Kendall; Kolev, Svetoslav; Tassa, Yuval; Erez, Stiffler, Nicholas; O'Kane, Jason Grunberg, David; Kim, Youngmoo Tom; Todorov, Emanuel
A Real-Time Distributed Architecture for Large-Scale Online Learning of Task-Specific Dynamics for Audio Ray Tracing for Position Estimation of Entities in 09:47- Tactile Sensing Periodic Tasks Blind Regions 11 09:50 Baglini, Emanuele; Youssefi, Shahbaz; Petric, Tadej; Gams, Andrej; Zlajpah, Leon; Ude, Ales Even, Jani; Morales Saiki, Luis Yoichi; Kallakuri, Mastrogiovanni, Fulvio; Cannata, Giorgio Nagasrikanth; Ishi, Carlos Toshinori; Hagita, Norihiro
62 Tuesday Session A, 09:00 - 10:20 (Continued) Grand Ballroom State Ballroom Red Lacquer Room TuA1 TuA2 TuA3
# Time Parallel Robotics Localization and Mapping II Field Robotics A New Extension of Desired Compensation Adaptive An Adaptive Basic I/O Gain Tuning Method Based on Control and Its Real-Time Application to Redundantly Towards Consistent Reconstructions of Indoor Spaces Leveling Control Input Histogram for Human-Machine 09:50- Actuated PKMs Based on 6D RGB-D Odometry and KinectFusion Systems 12 09:53 Bennehar, Moussab; Chemori, Ahmed; Pierrot, Dong, Haiwei; Figueroa, Nadia; El Saddik, Kamezaki, Mitsuhiro; Iwata, Hiroyasu; Sugano, François Abdulmotaleb Shigeki
Development and Field Test of Teleoperated Mobile 09:53- Structural Synthesis of Dexterous Hands Biologically Inspired SLAM Using Wi-Fi Robots for Active Volcano Observation 13 09:56 Ozgur, Erol; Gogu, Grigore; Mezouar, Youcef Berkvens, Rafael; Jacobson, Adam; Milford, Michael J; Nagatani, Keiji; Akiyama, Ken; Yamauchi, Genki; peremans, herbert; Weyn, Maarten Yoshida, Kazuya; Hada, Yasushi; Yuta, Shinichi; Izu, Tomoyuki; Randy, Mackay Intelligent Slip-Optimization Control with Traction- Study of Reconfigurable Suspended Cable-Driven Energy Trade-Off for Wheeled Robots on Rough 09:56- Parallel Robots for Airplane Maintenance Point Cloud Registration Using Congruent Pyramids Terrain 14 09:59 NGUYEN, Dinh Quan; Gouttefarde, Marc Krishnan, Aravindhan; Saripalli, Srikanth Kim, Jayoung; Lee, Jihong
On the Formulation, Performance and Design Choices Workspace Analysis of Two Similar 3-DOF Axis- of Cost-Curve Occupancy Grids for Stereo-Vision Novel Robot Mechanism Capable of 3D Differential 09:59- Symmetric Parallel Manipulators Based 3D Reconstruction Driving Inside Pipelines 15 10:02 Marlow, Kristan; Isaksson, Mats; Abdi, Hamid; Brandao, Martim; Ferreira, Ricardo; Hashimoto, Kenji; Yang, Seung Ung; Kim, Ho Moon; Suh, Jung Seok; Nahavandi, Saeid Santos-Victor, José; Takanishi, Atsuo Choi, Yun Seok; Mun, Hyeong Min; Park, Chan Min; Moon, Hyungpil; Choi, Hyouk Ryeol Improvement of the Direct Kinematic Model of a Haptic Device for Medical Application in Real Time Handling Perceptual Clutter for Robot Vision with Autonomous Robotic System for Bridge Deck Data 10:02- Using an Extra Sensor Partial Model-Based Interpretations Collection and Analysis 16 10:05 saafi, Houssem; laribi, med amine; Zeghloul, Said Tsai, Grace; Kuipers, Benjamin La, Hung; Gucunski, Nenad; Kee, Seong-Hoon; Yi, Jingang; Senlet, Turgay; Nguyen, Luan
Switching Strategy for Flexible Task Execution Using Modeling Motion Patterns of Dynamic Objects by Road Surface Washing System for Decontaminating 10:05- the Cooperative Dual Task-Space Framework IOHMM Radioactive Substances 17 10:08 Figueredo, Luis Felipe da Cruz; Adorno, Bruno Wang, Zhan; Ambrus, Rares; Jensfelt, Patric; Endo, Mitsuru; Endo, Mai; Kakizaki, Takao Vilhena; Ishihara, João Yoshiyuki; Borges, Geovany Folkesson, John Araujo Vibration Control of 3P(S)4 Class Parallel Mechanisms for High Speed Applications Using Fast Hybrid Relocation in Large Scale Metric- A Framework for Predicting the Mission-Specific 10:08- Quantitative Feedback Design Topologic-Semantic Map Performance of Autonomous Unmanned Systems 18 10:11 Avci, Ebubekir; Kenmochi, Masanori; Kawanishi, DROUILLY, Romain; Rives, Patrick; Morisset, Benoit Durst, Phillip J; Gray, Wendell; Nikitenko, Agris; Michihiro; Narikiyo, Tatsuo; Kawakami, Shinji; Saitoh, Caetano, Joao; King, Roger; Trentini, Michael Yumi Dimensional Synthesis of 4 DoFs (3T-1R) Actuatedly Redundant Parallel Manipulator Based on Dual Stereo-Vision Based Obstacle Mapping for Experimental Analysis of Models for Trajectory 10:11- Criteria: Dynamics and Precision Indoor/Outdoor SLAM Generation on Tracked Vehicles 19 10:14 SHAYYA, Samah; Krut, Sebastien; Company, Olivier; Brand, Christoph; Schuster, Martin Johannes; Fink, Jonathan; Stump, Ethan Baradat, Cédric; Pierrot, François Hirschmüller, Heiko; Suppa, Michael
Active Vibration Canceling of a Cable-Driven Parallel Meta-Rooms: Building and Maintaining Long Term Sonar-Based Chain Following Using an Autonomous Robot Using Reaction Wheels Spatial Models in a Dynamic World Underwater Vehicle 10:14- 20 Weber, Xavier; Cuvillon, Loic; Gangloff, Jacques Ambrus, Rares; Bore, Nils; Folkesson, John; Jensfelt, Hurtos, Natalia; Palomeras, Narcis; Carreras, Marc; 10:17 Patric Carrera, Arnau; Bechlioulis, Charalampos; Karras, George; Heshmati-alamdari, Shahab; Kyriakopoulos, Kostas
Sponsor Talk: BRIN: Benchmark for Robotic Indoor 10:17- Navigation Sponsor Talk: Vision-Based Navigation 21 10:20 Parent, Gershon Jones, Chris Microsoft Robotics iRobot Corporation
63 Tuesday Session B, 10:50 - 12:10 Grand Ballroom State Ballroom Red Lacquer Room TuB1 TuB2 TuB3 Medical Robots and Systems I & Human-Robot Interaction II & Marine Robotics & Rehabilitation Robotics I Robot Learning III Space Robotics
Chair Papanikolopoulos, Nikos (University of Minnesota) Zhang, Jianwei (University of Hamburg) Leonard, John (MIT)
# Time Session Keynote Session Keynote Session Keynote Keynote: Medical Robotics - Melding Clinical Need Keynote: Robots and Gaming - Therapy for Children Keynote: Human-guided video data collection in 10:50- with Engineering Research with Disabilities marine environments 1 11:10 Dupont, Pierre Howard, Ayanna Dudek, Gregory Boston University Georgia Tech EPFL
Medical Robots and Systems I Human-Robot Interaction II Marine Robotics
A Fast, Low-Cost, Computer Vision Approach for A Gesture Recognition System for Mobile Robots That Predicting the Speed of a Wave Glider Autonomous 11:10- Tracking Surgical Tools Learns Online Surface Vehicle from Wave Model Data 2 11:13 Dockter, Rodney; Sweet, Robert; Kowalewski, Timothy Hamlet, Alan; Emami, Patrick Ngo, Phillip; Das, Jnaneshwar; Ogle, Jonathan; Thomas, Jesse; Anderson, Will; Smith, Ryan N.
A Dynamically Consistent Hierarchical Control Cartesian Impedance Control of Redundant 3D Trajectory Synthesis and Control for a Legged 11:13- Architecture for Robotic-Assisted Tele-Echography Manipulators for Human-Robot Co-Manipulation Swimming Robot 3 11:16 Santos, Luís; Cortesao, Rui Ficuciello, Fanny; Romano, Amedeo; Villani, Luigi; Meger, David Paul; Shkurti, Florian; Cortés Poza, Siciliano, Bruno David; Giguere, Philippe; Dudek, Gregory
Extended Kinematic Mapping of Tendon-Driven Estimation of Contact Forces Using a Virtual Force Control of a Compact, Tetherless ROV for In-Contact 11:16- Continuum Robot for Neuroendoscopy Sensor Inspection of Complex Underwater Structures 4 11:19 Kato, Takahisa; Okumura, Ichiro; Kose, Hidekazu; Magrini, Emanuele; Flacco, Fabrizio; De Luca, Bhattacharyya, Sampriti; Asada, Harry Takagi, Kiyoshi; Hata, Nobuhiko Alessandro
Multi-Muscle FES Control of the Human Arm for Dielectrophoresis-Based Automatic 3D Cell Interaction Tasks---Stabilizing with Muscle Co- Three-Dimensional Reconstruction of Bridge Manipulation and Patterning through a Micro- Contraction and Postural Adjustment: A Simulation Structures above the Waterline with an Unmanned 11:19- 5 Electrode Integrated Multi-Layer Scaffold Study Surface Vehicle 11:22 Chu, Henry; Huan, Zhijie; Mills, James K.; Yang, Jie; Liao, Yu-Wei; Schearer, Eric; Perreault, Eric; Tresch, Han, Jungwook; Park, Jeonghong; Kim, JinWhan Sun, Dong Matthew; Lynch, Kevin
A Novel Redundant Motion Control Mechanism in Pneumatic Tubular Body Fixture for Wearable Accordance with Medical Diagnostic and Therapeutic Assistive Device - Analysis and Design of Active Cuff Task Functions for a NIUTS to Hold Upper Limb - I-AUV Docking and Intervention in a Subsea Panel 11:22- Koizumi, Norihiro; Lee, Dongjun; Seo, Joonho; Hasegawa, Yasuhisa; Hasegawa, Takaaki; Eguchi, Palomeras, Narcis; Peñalver, Antonio; Massot- 6 11:25 Tsukihara, Hiroyuki; Nomiya, Akira; Azuma, Takashi; Kiyoshi Campos, Miquel; Vallicrosa, Guillem; Negre Carrasco, Yoshinaka, Kiyoshi; Sugita, Naohiko; Homma, Yukio; Pep Lluis; Fernández, José Javier; Ridao, Pere; Sanz, Mitsuishi, Mamoru Pedro J; Oliver, Gabriel A.; Palomer, Albert
Simultaneously Powering and Controlling Many Implementation and Experimental Validation of Active Range-Only Beacon Localization for AUV 11:25- Actuators with a Clinical MRI Scanner Dynamic Movement Primitives for Object Handover Homing 7 11:28 Becker, Aaron; Felfoul, Ouajdi; Dupont, Pierre Prada, Miguel; Remazeilles, Anthony; Koene, Ansgar Vallicrosa, Guillem; Ridao, Pere; Ribas, David; Roald; Endo, Satoshi Palomer, Albert
Support Vector Machine Classification of Muscle Simultaneous Catheter and Environment Modeling for Cocontraction to Improve Physical Human-Robot Autonomous Vehicle Localization in a Vector Field: 11:28- Trans-Catheter Aortic Valve Implantation Interaction Underwater Vehicle Implementation 8 11:31 Shi, Chaoyang; Giannarou, Stamatia; Lee, Su-Lin; Moualeu, Antonio; Gallagher, William; Ueda, Jun Song, Zhuoyuan; Mohseni, Kamran Yang, Guang-Zhong
Underway Path-Planning for an Unmanned Surface Structurally-Redesigned Concentric-Tube Oscillation Reduction Scheme for Wearable Robots Vehicle Performing Cooperative Navigation for UUVs 11:31- Manipulators with Improved Stability Employing Linear Actuators and Sensors at Varying Depths 9 11:34 Azimian, Hamidreza; Francis, Peter; Looi, Thomas; Park, Jong Hyeon; Choo, Junghoon; Jeong, Dong- Hudson, Jonathan; Seto, Mae Drake, James Hyun; Jeong, Seungwoo; Chu, Gilwhoan
Online Identification of Abdominal Tissues in Vivo for Joint Configuration Strategy for Serial-Chain Safe Experimental Validation of Robotic Manifold Tracking 11:34- Tissue-Aware and Injury-Avoiding Surgical Robots Manipulators in Gyre-Like Flows 10 11:37 Sie, Astrini; Winek, Michael; Kowalewski, Timothy HONG, SeongHun; Lee, Woosub; Cho, Changhyun; Michini, Matthew; Hsieh, M. Ani; Forgoston, Eric; Kang, Sungchul; Lee, Hyeongcheol Schwartz, Ira
Trajectory Planning with Adaptive Control Primitives A Novel Micro Laser Ablation System Integrated with Single Muscle Site Semg Interface for Assistive for Autonomous Surface Vehicles Operating in 11:37- Image Sensor for Minimally Invasive Surgery Grasping Congested Civilian Traffic 11 11:40 Su, Baiquan; Shi, Zhan; Liao, Hongen Weisz, Jonathan; Barszap, Alexander; Joshi, Sanjay; Shah, Brual C.; Svec, Petr; Bertaska, Ivan R.; Klinger, Allen, Peter Wilhelm; Sinisterra, Armando J.; Ellenrieder, Karl von; Dhanak, Manhar; Gupta, Satyandra K.
64 Tuesday Session B, 10:50 - 12:10 (Continued) Grand Ballroom State Ballroom Red Lacquer Room TuB1 TuB2 TuB3
# Time Rehabilitation Robotics I Robot Learning III Space Robotics Preliminary Evaluation of a New Control Approach to Achieve Speed Adaptation in Robotic Transfemoral Using Haptics to Extract Object Shape from Rotational 11:40- Prosthesis Manipulations Inchworm Style Gecko Adhesive Climbing Robot 12 11:43 Lenzi, Tommaso; Hargrove, Levi; Sensinger, Jonathon Strub, Claudius; Wörgötter, Florentin; Ritter, Helge kalouche, Simon; Wiltsie, Nicholas; Su, Hai-Jun; Joachim; Sandamirskaya, Yulia Parness, Aaron
Development of an Elbow-Forearm Interlock Joint Mechanism Toward an Exoskeleton for Patients with Backup State Observer Based on Optic Flow Applied Essential Tremor Dynamic Attack Motion Prediction for Kendo Agent to Lunar Landing 11:43- 13 Matsumoto, Yuya; Amemiya, Motoyuki; Kaneishi, Tanaka, Yasufumi; Kosuge, Kazuhiro Sabiron, Guillaume; Burlion, Laurent; Jonniaux, 11:46 Daisuke; Nakashima, Yasutaka; Seki, Masatoshi; Grégory; Kervendal, Erwan; Bornschlegl, Eric; Ando, Takeshi; Kobayashi, Yo; Iijima, Hiroshi; Raharijaona, Thibaut; Ruffier, Franck Nagaoka, Masanori; Fujie, Masakatsu G. A Method for Predicting Personalized Pelvic Motion Integration of Various Concepts and Grounding of Experimental Evaluation of On-Board, Visual Mapping Based on Body Meta-Features for Gait Rehabilitation Word Meanings Using Multi-Layered Multimodal LDA of an Object Spinning in Micro-Gravity Aboard the 11:46- Robot for Sentence Generation International Space Station 14 11:49 Shin, Sung Yul; Hong, Jisoo; Chun, Changmook; Kim, Attamimi, Muhammad; Fadlil, Muhammad; Abe, Tweddle, Brent Edward; Setterfield, Timothy Philip; Seung-Jong; Kim, ChangHwan Kasumi; Nakamura, Tomoaki; Funakoshi, Kotaro; Saenz-Otero, Alvar; Miller, David W.; Leonard, John Nagai, Takayuki Towards Local Reflexive Control of a Powered Transfemoral Prosthesis for Robust Amputee Push A Machine Learning Approach for Real-Time 11:49- and Trip Recovery Reachability Analysis Small Body Surface Mobility with a Limbed Robot 15 11:52 Thatte, Nitish; Geyer, Hartmut Allen, Ross; Clark, Ashley; Starek, Joseph; Pavone, Helmick, Daniel; Douillard, Bertrand; Bajracharya, Max Marco
Analysis of Inertial Motion in Swing Phase of Human 11:52- Gait and Its Application to Motion Generation Method Transfer of Sparse Coding Representations and On Controller Parametric Sensitivity of Passive Object 16 11:55 of Transfemoral Prosthesis Object Classifiers across Heterogeneous Robots Handling in Space by Robotic Servicers Wada, Takahiro; Sano, Hiroshi; Sekimoto, Masahiro Kira, Zsolt Rekleitis, Georgios; Papadopoulos, Evangelos Investigation of Contralateral Leg Response to Unilateral Stiffness Perturbations Using a Novel A Perceptual Memory System for Grounding Semantic Design of a Hopping Mechanism using Permanent 11:55- Device Representations in Intelligent Service Robots Magnets for Small-scale Exploration Rovers 17 11:58 Skidmore, Jeffrey; Barkan, Andrew; Artemiadis, Oliveira, Miguel; Lim, Gi Hyun; Seabra Lopes, Luís; Kurisu, Masamitsu Panagiotis Mohades Kasaei, Seyed Hamidreza; Tomé, Ana Maria; Chauhan, Aneesh
Mobile Robotic Gait Rehabilitation System CORBYS Actor-Critic Design Using Echo State Networks in a Soft Landing of Capsule by Casting Manipulator 11:58- Overview and First Results on Orthosis Actuation Simulated Quadruped Robot System 18 12:01 Slavnic, Sinisa; Ristic-Durrant, Danijela; Tschakarow, Schmidt, Nico M.; Baumgartner, Matthias; Pfeifer, Rolf Arisumi, Hitoshi; Otsuki, Masatsugu; Nishida, Shin- Roko; Brendel, Thomas; Tüttemann, Markus; Leu, Ichiro Adrian; Gräser, Axel
Design and Control of an Exoskeleton System for Gait Expensive Multiobjective Optimization for Robotics Particle Filter Based 3D Position Tracking for Terrain 12:01- Rehabilitation Capable of Natural Pelvic Movement with Consideration of Heteroscedastic Noise Rovers Using Laser Point Clouds 19 12:04 Jung, Chan-Yul; Choi, Junho; Park, Shinsuk; Lee, Ariizumi, Ryo; Tesch, Matthew; Choset, Howie; Jayasekara, Peshala Gehan; Ishigami, Genya; Jong Min; Kim, ChangHwan; Kim, Seung-Jong Matsuno, Fumitoshi Kubota, Takashi
Integrated Control Method for Power-Assisted Rehabilitation: Ellipsoid Regression and Impedance Flop and Roll: Learning Robust Goal-Directed A Real-Time Recognition Based Drilling Strategy for 12:04- Control Locomotion for a Tensegrity Robot Lunar Exploration 20 12:07 Lee, Jaemin; Kim, MinKyu; Oh, Sang-Rok; Kim, Iscen, Atil; Agogino, Adrian; SunSpiral, Vytas; Tumer, Quan, Qiquan; Tang, Junyue Keehoon Kagan
reachMAN2: A Compact Rehabilitation Robot to Train 12:07- Reaching and Manipulation Efficient Bayesian Local Model Learning for Control 21 12:10 TONG, LIU ZHU; Klein, Julius; Anne Dual, Seraina; Meier, Franziska; Hennig, Philipp; Schaal, Stefan Teo, Chee Leong; burdet, etienne
65 Tuesday Session C, 13:30 - 14:50 Grand Ballroom State Ballroom Red Lacquer Room TuC1 TuC2 TuC3 Dynamics and Control & Humanoids and Bipeds II & Localization and Mapping III & Manipulation and Grasping IV Domestic and Interactive Robots Visual Servoing and Tracking
Chair Buchli, Jonas (ETH Zurich) Lee, C. S. George (Purdue University) Neira, José (Universidad de Zaragoza)
# Time Session Keynote Session Keynote Session Keynote Keynote: Highly dynamic, energy-aware, biomimetic Keynote: Human-Robot Interaction Socially Assistive Keynote: The SLAM Problem - A Fifteen Year Journey 13:30- robots Robotics ..... 1 13:50 Stramigioli, Stefano Scassellati, Brian Dissanayake, Gamini University of Twente Yale University University of Technology, Sydney
Dynamics and Control Humanoids and Bipeds II Localization and Mapping III Robust Control of Flexible Joint Robots Based on Motor-Side Dynamics Reshaping Using Disturbance Perturbation Recovery of Biped Walking by Updating Direction-Driven Navigation Using Cognitive Map for 13:50- Observer (DOB) the Footstep Mobile Robots 2 13:53 Kim, Min Jun; Chung, Wan Kyun Fu, Chenglong Shim, Vui Ann; Tian, Bo; Yuan, Miaolong; Tang, Huajin; Li, Haizhou
ISPCG: Incremental Subgraph-Preconditioned A Novel RISE-Based Adaptive Feedforward Controller Conjugate Gradient Method for Online SLAM with 13:53- for Redundantly Actuated Parallel Manipulators Swing-Leg Retraction Efficiency in Bipedal Walking Many Loop-Closures 3 13:56 Bennehar, Moussab; Chemori, Ahmed; Pierrot, Hasaneini, Seyed Javad; Macnab, Chris; Bertram, Jian, Yong-Dian; Dellaert, Frank François John; Leung, Henry
Falling Prevention of Humanoid Robots by Switching Real-Time RGB-D Registration and Mapping in Constrained Directions As a Path Planning Algorithm Standing Balance and Hopping Motion Based on MOA Texture-Less Environments Using Ranked Order 13:56- for Mobile Robots under Slip and Actuator Limitations Set Statistics 4 13:59 Soltani-Zarrin, Rana; Jayasuriya, Suhada Yamamoto, Ko Yousif, Khalid; Bab-hadiashar, Alireza; Hoseinnezhad, Reza
Partially Analytical Extra-Insensitive Shaper for a Preliminary Walking Experiments with Underactuated Online Global Loop Closure Detection for Large-Scale 13:59- Lightly Damped Flexible Arm 3D Bipedal Robot MARLO Multi-Session Graph-Based SLAM 5 14:02 Kang, Chul-Goo; Ha, Manh-Tuan Buss, Brian G.; Ramezani, Alireza; Akbari Hamed, Labbé, Mathieu; Michaud, Francois Kaveh; Griffin, Brent Austin; Galloway, Kevin; Grizzle, J.W Terminal Sliding-Mode Based Force Tracking Control Running into a Trap: Numerical Design of Task- of Piezoelectric Actuators for Variable Physical Optimal Preflex Behaviors for Delayed Disturbance Selecting Good Measurements Via L1 Relaxation: A 14:02- Damping System Responses Convex Approach for Robust Estimation Over Graphs 6 14:05 Lee, Jinoh; Jin, Maolin; Tsagarakis, Nikolaos; Van Why, Johnathan; Hubicki, Christian; Jones, Carlone, Luca; Censi, Andrea; Dellaert, Frank Caldwell, Darwin G. Mikhail; Daley, Monica; Hurst, Jonathan
Development of a Single Controller for the Compensation of Several Types of Disturbances During Task Execution of a Wheeled Inverted SLIP with Swing Leg Augmentation As a Model for Hybrid Inference Optimization for Robust Pose Graph 14:05- 7 Pendulum Assistant Robot Running Estimation 14:08 Canete, Luis; Takahashi, Takayuki Mohammadi Nejad Rashty, Aida; Ahmad Sharbafi, Segal, Aleksandr V.; Reid, Ian Maziar; Seyfarth, Andre
A Reverse Priority Approach to Multi-Task Control of Quantifying the Trade-Offs between Stability versus Robust Graph SLAM Back-Ends: A Comparative 14:08- Redundant Robots Energy Use for Underactuated Biped Walking Analysis 8 14:11 Flacco, Fabrizio; De Luca, Alessandro Saglam, Cenk Oguz; Byl, Katie Latif, Yasir; Cadena Lerma, Cesar Dario; Neira, José
Dynamic Modeling of Constant Curvature Continuum Highly Robust Running of Articulated Bipeds in Graph SLAM with Signed Distance Function Maps on 14:11- Robots Using the Euler-Lagrange Formalism Unobserved Terrain a Humanoid Robot 9 14:14 Falkenhahn, Valentin; Mahl, Tobias; Hildebrandt, Wu, Albert; Geyer, Hartmut Wagner, René; Frese, Udo; Bäuml, Berthold Alexander; Neumann, Ruediger; Sawodny, Oliver
Fast and Reasonable Contact Force Computation in Forward Dynamics Based on Momentum-Level From Template to Anchor: A Novel Control Strategy for Credibilist Simultaneous Localization and Mapping 14:14- Penetration Compensation Spring-Mass Running of Bipedal Robots with a LIDAR 10 14:17 Wakisaka, Naoki; Sugihara, Tomomichi Dadashzadeh, Behnam; Vejdani, Hamid Reza; Hurst, Trehard, Guillaume; Alsayed, Zayed; Pollard, Jonathan Evangeline; BRADAI, Benazouz; Nashashibi, Fawzi
Recursive Dynamics and Feedback Linearizing An Estimation Model for Footstep Modifications of Novel Insights into the Impact of Graph Structure on 14:17- Control of Serial-Chain Manipulators Biped Robots SLAM 11 14:20 Travers, Matthew; Choset, Howie Wittmann, Robert; Hildebrandt, Arne-Christoph; Khosoussi, Kasra; Huang, Shoudong; Dissanayake, Ewald, Alexander; Buschmann, Thomas Gamini
66 Tuesday Session C, 13:30 - 14:50 (Continued) Grand Ballroom State Ballroom Red Lacquer Room TuC1 TuC2 TuC3
# Time Manipulation and Grasping IV Domestic and Interactive Robots Visual Servoing and Tracking
Grasp Planning for Constricted Parts of Objects Finding and Navigating to Household Objects with 14:20- Approximated with Quadric Surfaces UHF RFID Tags by Optimizing RF Signal Strength Robust Model Predictive Control for Visual Servoing 12 14:23 Tsuji, Tokuo; Uto, Soichiro; Harada, Kensuke; Deyle, Travis; Reynolds, Matthew; Kemp, Charlie Assa, Akbar; Janabi-Sharifi, Farrokh Kurazume, Ryo; Hasegawa, Tsutomu; Morooka, Ken'ichi
Fast Grasping of Unknown Objects Using Force RGB-D Sensor Setup for Multiple Tasks of Home Prescribed Performance Image Based Visual Servoing 14:23- Balance Optimization Robots and Experimental Results under Field of View Constraints 13 14:26 LEI, QUJIANG; Wisse, Martijn de la Puente, Paloma; Bajones, Markus; Einramhof, Heshmati-alamdari, Shahab; Bechlioulis, Peter; Wolf, Daniel; Fischinger, David; Vincze, Markus Charalampos; Liarokapis, Minas; Kyriakopoulos, Kostas
Enhanced Robotic Cleaning with a Low-Cost Tool Monocular Template-Based Vehicle Tracking for 14:26- Robotic Nonprehensile Catching: Initial Experiments Attachment Autonomous Convoy Driving 14 14:29 Yashima, Masahito; Yamawaki, Tasuku Xu, Zhe; Cakmak, Maya Fries, Carsten; Wuensche, Hans J
Changing Pre-Grasp Strategies with Increasing Object CHARM: A Platform for Algorithmic Robotics Real-Time Object Pose Recognition and Tracking with 14:29- Location Uncertainty Education & Research an Imprecisely Calibrated Moving RGB-D Camera 15 14:32 Illing, Boris; Asfour, Tamim; Pollard, Nancy S Singh, Surya; Kurniawati, Hanna; Soltani Naveh, Pauwels, Karl; Ivan, Vladimir; Ros, Eduardo; Kianoosh; Song, Joshua; Zastrow, Tyson Vijayakumar, Sethu
Shrinkable, Stiffness-Controllable Soft Manipulator Development of a Comic Mark Based Expressive Based on a Bio-Inspired Antagonistic Actuation Robotic Head Adapted to Japanese Cultural Robust Ground Surface Map Generation Using 14:32- Principle Background Vehicle-Mounted Stereo Camera 16 14:35 Stilli, Agostino; Wurdemann, Helge Arne; Althoefer, KISHI, Tatsuhiro; Futaki, Hajime; Trovato, Gabriele; Motooka, Kouma; Sugimoto, Shigeki; Okutomi, Kaspar Endo, Nobutsuna; Destephe, Matthieu; Cosentino, Masatoshi; Shima, Takeshi Sarah; Hashimoto, Kenji; Takanishi, Atsuo
Guided Locomotion in 3D for Snake Robots Based on Effects of Bodily Mood Expression of a Robotic RGB-D Fusion: Real-Time Robust Tracking and 14:35- Contact Force Optimization Teacher on Students Dense Mapping with RGB-D Data Fusion 17 14:38 Ponte, Hugo; Travers, Matthew; Choset, Howie Xu, Junchao; broekens, joost; Hindriks, Koen; Lee, Seong-Oh; Lim, Hwasup; Kim, Hyoung-Gon; Ahn, Neerincx, Mark Sang Chul
Real-Time Recognition of Pointing Gestures for Robot Bearings-Only Path Following with a Vision-Based 14:38- Push Resistance in In-Hand Manipulation to Robot Interaction Potential Field 18 14:41 He, Junhu; Zhang, Jianwei Kondaxakis, Polychronis; Pajarinen, Joni; Kyrki, Ville Sabatta, Deon; Siegwart, Roland
Online Interactive Perception of Articulated Objects with Multi-Level Recursive Estimation Based on Task- Event-Based, 6-DOF Pose Tracking for High-Speed 14:41- Specific Priors Adaptive Spacing in Human-Robot Interactions Maneuvers 19 14:44 Martín Martín, Roberto; Brock, Oliver Papadakis, Panagiotis; Rives, Patrick; Spalanzani, Mueggler, Elias; Huber, Basil; Scaramuzza, Davide Anne
Using Environment Objects As Tools: Unconventional Determining the Affective Body Language of Older Learning Visual Feature Descriptors for Dynamic 14:44- Door Opening Adults during Socially Assistive HRI Lighting Conditions 20 14:47 Levihn, Martin; Stilman, Mike McColl, Derek; Nejat, Goldie Carlevaris-Bianco, Nicholas; Eustice, Ryan
Sponsor Talk: Components for Mobile Manipulation: Sponsor Talk: The Eyes: A History of Baxter's Detection of Small Moving Objects Using a Moving 14:47- Light-Weight Arms and Robotic Hands Personification Camera 21 14:50 Parlitz, Christopher Maroney, Kyle Shakeri, Moein; Zhang, Hong SCHUNK Rethink Robotics
67 Tuesday Session D, 15:00 - 16:20 Grand Ballroom State Ballroom Red Lacquer Room TuD1 TuD2 TuD3 Actuators & Reasoning and AI Planning & Sensing I & Kinematics and Mechanism Design II Path and Task Planning Sensing for Human Environments
Chair Krovi, Venkat (University at Buffalo (SUNY Buffalo)) Jacobs, Sam Ade (ABB Inc) Song, Dezhen (Texas A&M University)
# Time Session Keynote Session Keynote Session Keynote Keynote: Robots for Interaction with Humans and Keynote: Symbiotic Mobile Robot Autonomy in Human 15:00- Unknown Environments Environments Keynote: Life In a World of Ubiquitous Sensing 1 15:20 Albu-Schäffer, Alin Veloso, Manuela Hager, Gregory DLR Carnegie Mellon University Johns Hopkins University
Actuators Reasoning and AI Planning Sensing I Augmenting Bayes Filters with the Relevance Vector Prior-Assisted Propagation of Spatial Information for Machine for Time-Varying Context-Dependent 15:20- Soft Pneumatic Actuator Skin with Embedded Sensors Object Search Observation Distribution 2 15:23 Suh, Chansu; Condal Margarit, Jordi; Song, Yun Lorbach, Malte; Höfer, Sebastian; Brock, Oliver Ravet, Alexandre; Lacroix, Simon; Hattenberger, Seong; Paik, Jamie Gautier
Towards Variable Stiffness Control of Antagonistic Combining Top-Down Spatial Reasoning and Bottom- Audio-Visual Classification and Detection of Human 15:23- Twisted String Actuators Up Object Class Recognition for Scene Understanding Manipulation Actions 3 15:26 Popov, Dmitry; Gaponov, Igor; Ryu, Jee-Hwan Kunze, Lars; Burbridge, Christopher; Alberti, Marina; Pieropan, Alessandro; Salvi, Giampiero; Pauwels, Thippur, Akshaya; Folkesson, John; Jensfelt, Patric; Karl; Kjellstrom, Hedvig Hawes, Nick Object Shape Categorization in RGBD Images using Hierarchical Graph Constellation Models based on A Multiplex Pneumatic Actuator Drive Method Based Learning Relational Affordance Models for Two-Arm Unsupervisedly Learned Shape Parts described by a 15:26- 4 on Acoustic Communication in Air Supply Line Robots Set of Shape Specificity Levels 15:29 Suzumori, Koichi; Osaki, Naoto; Misumi, Jumpei; Moldovan, Bogdan; De Raedt, Luc Mueller, Christian Atanas; Pathak, Kaustubh; Birk, Yamamoto, Akina; Kanda, Takefumi Andreas
Cognitive Factories with Multiple Teams of A Low-Friction Passive Fluid Transmission and Fluid- Heterogeneous Robots: Hybrid Reasoning for Optimal sEMG-Based Decoding of Human Intentions Robust 15:29- Tendon Soft Actuator Feasible Global Plans to the Changes of Electrode Positions 5 15:32 Whitney, John; Glisson, Matthew; Brockmeyer, Eric; Saribatur, Zeynep G.; Erdem, Esra; Patoglu, Volkan Park, Myoung Soo Hodgins, Jessica
Design of a Novel Intermittent Self-Closing Mechanism for a MACCEPA-Based Series-Parallel Incorporating Kinodynamic Constraints in Automated 15:32- Elastic Actuator (SPEA) Design of Simple Machines Multi-Target Visual Tracking with Aerial Robots 6 15:35 Mathijssen, Glenn; Furnémont, Raphaël; Brackx, Erdogan, Can; Stilman, Mike Tokekar, Pratap; Isler, Volkan; Franchi, Antonio Branko; Van Ham, Ronald; Lefeber, Dirk; Vanderborght, Bram
A Resonant Parallel Elastic Actuator for Biorobotic Unifying Multi-Goal Path Planning for Autonomous Opportunistic Sampling-Based Planning for Active 15:35- Applications Data Collection Visual SLAM 7 15:38 Sudano, Angelo; Tagliamonte, Nevio Luigi; Accoto, Faigl, Jan; Hollinger, Geoffrey Chaves, Stephen; Kim, Ayoung; Eustice, Ryan Dino; Guglielmelli, Eugenio
Smart Braid: Air Muscles That Measure Force and Stochastic Collection and Replenishment (SCAR) Ear-Based Exploration on Hybrid Metric/Topological 15:38- Displacement Optimisation for Persistent Autonomy Maps 8 15:41 Felt, Wyatt; Remy, C. David Palmer, Andrew William; Hill, Andrew John; Scheding, Zhang, Qiwen; Whitney, David; Shkurti, Florian; Steven Rekleitis, Ioannis
Variable Stiffness Fabrics with Embedded Shape Fast and Effective Visual Place Recognition using 15:41- Memory Materials for Wearable Applications Coverage Planning with Finite Resources Binary Codes and Disparity Information 9 15:44 Chenal, Thomas; Case, Jennifer; Paik, Jamie; Kramer, Strimel, Grant; Veloso, Manuela Arroyo, Roberto; Fernández Alcantarilla, Pablo; Rebecca Bergasa, Luis Miguel; Yebes, José Javier; Bronte, Sebastian
A Flexible Passive Joint for Robotic Fish Pectoral Fins: Coordination in Human-Robot Teams Using Mental A Linear Approach to Visuo-Inertial Fusion for 15:44- Design, Dynamic Modeling, and Experimental Results Modeling and Plan Recognition Homography-Based Filtering and Estimation 10 15:47 Bazaz Behbahani, Sanaz; Tan, Xiaobo Talamadupula, Kartik; Briggs, Gordon; Chakraborti, Eudes, Alexandre; Morin, Pascal Tathagata; Scheutz, Matthias; Kambhampati, Subbarao A Framework for Formal Specification of Robotic Formulation and Optimization of Pulley-Gear-Type Constraint-Based Tasks and their Concurrent Fusion of Optical Flow and Inertial Measurements for SMA Heat Engine Toward Microfluidic MEMS Motor Execution with Online QoS Monitoring Robust Egomotion Estimation 15:47- 11 Aono, Hiroyuki; Imamura, Ryota; Fuchiwaki, Ohmi; Scioni, Enea; Borghesan, Gianni; Bruyninckx, Bloesch, Michael; Omari, Sammy; Fankhauser, Péter; 15:50 Yamanashi, Yuki; Böhringer, Karl F. Herman; Bonfe, Marcello Sommer, Hannes; Gehring, Christian; Hwangbo, Jemin; Hoepflinger, Mark; Hutter, Marco; Siegwart, Roland
68 Tuesday Session D, 15:00 - 16:20 (Continued) Grand Ballroom State Ballroom Red Lacquer Room TuD1 TuD2 TuD3
# Time Kinematics and Mechanism Design II Path and Task Planning Sensing for Human Environments Synthesizing Manipulation Sequences for Under- Cameraman Robot: Dynamic Trajectory Tracking with Design, Principles, and Testing of a Latching Modular Specified Tasks Using Unrolled Markov Random Final Time Constraint Using State-Time Space 15:50- Robot Connector Fields Stochastic Approach 12 15:53 Eckenstein, Nick; Yim, Mark Sung, Jaeyong; Selman, Bart; Saxena, Ashutosh Ardiyanto, Igi; Miura, Jun
Design, Modeling and Performance Evaluation of a A Probability-Based Path Planning Method Using Automatic Detection and Verification of Pipeline 15:53- Long and Slim Continuum Robotic Cable Fuzzy Logic Construction Features with Multi-Modal Data 13 15:56 Tonapi, Manas; Godage, Isuru S.; Walker, Ian Lee, Jaeyeon; Park, Wooram Vidal-Calleja, Teresa A.; Valls Miro, Jaime; Martin, Fernando; Lingnau, Daniel C.; Russell, David E.
Kinetostatic Optimization for an Adjustable Four-Bar Multi-Goal Path Planning Based on the Generalized Grasping Point Selection on an Item of Crumpled 15:56- Based Articulated Leg-Wheel Subsystem Traveling Salesman Problem with Neighborhoods Clothing Based on Relational Shape Description 14 15:59 Alamdari, Aliakbar; Sovizi, Javad; Jun, Seung-kook; Vicencio, Kevin; Davis, Brian; Gentilini, Iacopo Yamazaki, Kimitoshi Krovi, Venkat
A Multi-Tree Extension of the Transition-Based RRT: A Single DOF Arm for Transition of Climbing Robots Application to Ordering-And-Pathfinding Problems in A Solution to Pose Ambiguity of Visual Markers Using 15:59- between Perpendicular Planes Continuous Cost Spaces Moire Patterns 15 16:02 Viegas, Carlos; Tavakoli, Mahmoud Devaurs, Didier; Simeon, Thierry; Cortes, Juan Tanaka, Hideyuki; Sumi, Yasushi; Matsumoto, Yoshio
Informed RRT*: Optimal Sampling-based Path Design of Variable Release Torque-Based Compliant Planning Focused via Direct Sampling of an 16:02- Spring-Clutch and Torque Estimation Admissible Ellipsoidal Heuristic On Leader Following and Classification 16 16:05 Seok, Jushin; Kang, Sungchul; Lee, Woosub Gammell, Jonathan David; Srinivasa, Siddhartha; Stein, Procópio; Spalanzani, Anne; Santos, Vitor; Barfoot, Timothy Laugier, Christian
Complexity-Based Motion Features and Their Principles of Microscale Flexure Hinge Design for Integrating Multiple Soft Constraints for Planning Applications to Action Recognition by Hierarchical 16:05- Enhanced Endurance Practical Paths Spatio-Temporal Na ve Bayes Classifier 17 16:08 Malka, Ronit; Lussier Desbiens, Alexis; Chen, YuFeng; Yang, Jing; dymond, patrick; Jenkin, Michael Kwon, Woo Young; Suh, Il Hong Wood, Robert
Strengthening of 3D Printed Robotic Parts Via Fill Sampling-Based Trajectory Imitation in Constrained Enhancement of Layered Hidden Markov Model by 16:08- Compositing Environments Using Laplacian-RRT* Brain-Inspired Feedback Mechanism 18 16:11 Belter, Joseph; Dollar, Aaron Nierhoff, Thomas; Hirche, Sandra; Nakamura, Lee, Sang Hyoung; Kim, Min Gu; Suh, Il Hong Yoshihiko
Cogeneration of Mechanical, Electrical, and Software Designs for Printable Robots from Structural The Anatomy of a Distributed Motion Planning Guiding Computational Perception through a Shared 16:11- Specifications Roadmap Auditory Space 19 16:14 Mehta, Ankur; DelPreto, Joseph; Shaya, Benjamin; Jacobs, Sam Ade; Amato, Nancy Martinson, Eric; Yalla, Ganesh Rus, Daniela
Design of a Robotic Finger Using Series Gear Chain Classification and Identification of Robot Sensing Data 16:14- Mechanisms Safest Path Adversarial Coverage Based on Nested Infinite GMM 20 16:17 Mishima, Yuuki; Ozawa, Ryuta Yehoshua, Roi; Agmon, Noa; Kaminka, Gal A Sasaki, Yoko; Hatao, Naotaka; Kagami, Satoshi
Sponsor Talk: The Next Research Revolution with Localization of Multiple Sources from a Binaural Head 16:17- KUKA's Robotic Reference Platforms Planning with the STAR(s) in a Known Noisy Environment 21 16:20 Ryan, Corey Karydis, Konstantinos; Zarrouk, David; Poulakakis, Portello, Alban; Bustamante, Gabriel; Danès, Patrick; KUKA Robotics Corp Ioannis; Fearing, Ronald; Tanner, Herbert G. Mifsud, Alexis
69 Tuesday Session E, 16:50 - 17:55 Grand Ballroom State Ballroom Red Lacquer Room TuE1 TuE2 TuE3 Constrained and Underactuated Robots & Human-Robot Interaction III & Unmanned Aerial Systems I & Legged Robots I Grasp Learning Localization and Pose Estimation
Chair Buehler, Martin (Vecna Technologies) Wettels, Nicholas (NASA-JPL) Clark, Christopher M. (Harvey Mudd College)
# Time Session Keynote Session Keynote Session Keynote Keynote: Perception-Action-Learning and Associative 16:50- Keynote: Robot Motion Optimization Skill Memories Keynote: Aerial Robot Swarms 1 17:10 Park, Frank Schaal, Stefan Kumar, Vijay Seoul National University University of Southern California University of Pennsylvania
Constrained and Underactuated Robots Human-Robot Interaction III Unmanned Aerial Systems I Frequency-Domain Flight Dynamics Model A Novel Continuum-Style Robot with Multilayer Remote Control System for Multiple Mobile Robots Identification of MAVs - Miniature Quad-Rotor Aerial 17:10- Compliant Modules Using Touch Panel Interface and Autonomous Mobility Vehicles 2 17:13 Qi, Peng; Qiu, Chen; Liu, Hongbin; Dai, Jian; Ochiai, Yuya; Takemura, Kentaro; Ikeda, Atsutoshi; Guowei, Cai; Al Mehairi, Hind; Al-Hosani, Hanan; Seneviratne, lakmal; Althoefer, Kaspar Takamatsu, Jun; Ogasawara, Tsukasa Dias, Jorge; Seneviratne, lakmal
A Fish-Like Locomotion Model in an Ideal Fluid with 17:13- Lateral-Line-Inspired Background Flow Estimation Ridesharing with Passenger Transfers Simulating Quadrotor UAVs in Outdoor Scenarios 3 17:16 Xu, Yiming; Mohseni, Kamran Coltin, Brian; Veloso, Manuela Symington, Andrew Colquhoun; De Nardi, Renzo; Julier, Simon Justin; Hailes, Stephen
MR Compatible Continuum Robot Based on Closed Modeling of Human Velocity Habituation for a Robotic Health Aware Stochastic Planning for Persistent 17:16- Elastica with Bending and Twisting Wheelchair Package Delivery Missions Using Quadrotors 4 17:19 Yamada, Atsushi; Naka, Shigeyuki; Morikawa, Morales Saiki, Luis Yoichi; Abdur-Rahim, Jamilah; Agha-mohammadi, Ali-akbar; Ure, Nazim Kemal; How, Shigehiro; Tani, Tohru Even, Jani; Kondo, Tadahisa; Hagita, Norihiro; Jonathan; Vian, John Ogawa, Takeshi; Ishii, Shin; Watanabe, Atsushi Physical Embodied Communication between Robots Trajectory Optimization of Flapping Wings Modeled as and Children: An Approach for Relationship Building High-Throughput Study of Flapping Wing 17:19- a Three Degree-Of-Freedoms Oscillation System by Holding Hands Aerodynamics for Biological and Robotic Applications 5 17:22 Qin, Yi; Cheng, Bo; Deng, Xinyan Hieida, Chie; Abe, Kasumi; Attamimi, Muhammad; Gravish, Nicholas; Chen, YuFeng; Combes, Stacey; Shimotomai, Takayuki; Nagai, Takayuki; Omori, Wood, Robert Takashi
The Use of Unicycle Robot Control Strategies for Skid- Using Social Cues to Estimate Possible Destinations Computational Morphology for a Soft Micro Air Vehicle 17:22- Steer Robots through the ICR Kinematic Mapping When Driving a Robotic Wheelchair in Hovering Flight 6 17:25 Pentzer, Jesse; Brennan, Sean; Reichard, Karl ESCOBEDO-CABELLO, Jesus-Arturo; Spalanzani, Chevallereau, Christine; Porez, Mathieu; Boyer, Anne; Laugier, Christian Frédéric
Open-Source, Affordable, Modular, Light-Weight, Towards Valve Turning Using a Dual-Arm Aerial 17:25- Underactuated Robot Hands A Novel User-Guided Interface for Robot Search Manipulator 7 17:28 Zisimatos, Agisilaos; Liarokapis, Minas; Mavrogiannis, Kosti, Shahar; Sarne, David; Kaminka, Gal A Korpela, Christopher M.; Orsag, Matko; Oh, Paul Y. Christoforos; Kyriakopoulos, Kostas
Modeling of Wheeled Mobile Robots As Differential- Contextual Task-Aware Shared Autonomy for Assistive 17:28- Algebraic Systems Mobile Robot Teleoperation Control of a Multirotor Outdoor Aerial Manipulator 8 17:31 Kelly, Alonzo; Seegmiller, Neal Andrew Gao, Ming; Oberländer, Jan; Schamm, Thomas; Heredia, Guillermo; Jimenez-Cano, Antonio; Sanchez, Zöllner, Johann Marius M. Ivan; Llorente, Domingo; Vega, Victor; Braga, Juan; Acosta, Jose Angel; Ollero, Anibal
Practical Identification and Flatness Based Control of Personalizing Vision-Based Gestural Interfaces for Reinforcement Learning for Autonomous Dynamic 17:31- a Terrestrial Quadrotor HRI with UAVs: A Transfer Learning Approach Soaring in Shear Winds 9 17:34 thorel, sylvain; d'Andréa-Novel, Brigitte Costante, Gabriele; Bellocchio, Enrico; Valigi, Paolo; Montella, Corey; Spletzer, John Ricci, Elisa
Partial Force Control of Constrained Floating-Base Vision-Based Absolute Localization for Unmanned 17:34- Robots Multimodal Real-Time Contingency Detection for HRI Aerial Vehicles 10 17:37 Del Prete, Andrea; Mansard, Nicolas; Nori, Francesco; Chu, Vivian; Bullard, Kalesha; Thomaz, Andrea YOL, Aurélien; Delabarre, Bertrand; Dame, Amaury; Metta, Giorgio; Natale, Lorenzo Lockerd DARTOIS, Jean-Emile; Marchand, Eric
Balancing Control Algorithm for a 3D Under-Actuated Pose Estimation in Physical Human-Machine 17:37- Robot Interactions with Application to Bicycle Riding Variable Impedance Control for Aerial Interaction 11 17:40 Azad, Morteza; Featherstone, Roy Zhang, Yizhai; Chen, Kuo; Yi, Jingang; Liu, Liu Mersha, Abeje Y.; Stramigioli, Stefano; Carloni, Raffaella
70 Tuesday Session E, 16:50 - 17:55 (Continued) Grand Ballroom State Ballroom Red Lacquer Room TuE1 TuE2 TuE3
# Time Legged Robots I Grasp Learning Localization and Pose Estimation On the Convergence of Fixed-point Iteration in Solving Complementarity Problems Arising in Robot Learning of Grasp Adaptation through Experience and Improving Object Tracking through Distributed 17:40- Locomotion and Manipulation Tactile Sensing Exploration of an Information Map 12 17:43 Lu, Ying; Trinkle, Jeff Li, Miao; Bekiroglu, Yasemin; Kragic, Danica; Billard, Neveln, Izaak; Miller, Lauren; MacIver, Malcolm A.; Aude Murphey, Todd
Quadruped Bounding Control with Variable Duty Cycle Construction of an Object Manipulation Database from 17:43- Via Vertical Impulse Scaling Grasp Demonstrations Topometric Localization on a Road Network 13 17:46 Park, Hae-Won; Chuah, Meng Yee (Michael); Kim, Kent, David; Chernova, Sonia Xu, Danfei; Badino, Hernan; Huber, Daniel Sangbae
Posture and Balance Control for Humanoid Robots in Multi-Contact Scenarios Based on Model Predictive Evaluating the Efficacy of Grasp Metrics for Utilization Pose Estimation of Servo-Brake-Controlled Caster 17:46- Control in a Gaussian Process-Based Grasp Predictor Units Arbitrarily Located on a Mobile Base 14 17:49 Henze, Bernd; Ott, Christian; Roa, Maximo A. Goins, Alex; Carpenter, Ryan; Wong, Weng-Keen; Saida, Masao; Hirata, Yasuhisa; Kosuge, Kazuhiro Balasubramanian, Ravi
Predicting Object Interactions from Contact Rail-Guided Robotic End-Effector Position Error Due 17:49- Optimal Gaits and Motions for Legged Robots Distributions to Rail Compliance and Ship Motion 15 17:52 Xi, Weitao; Remy, C. David Kroemer, Oliver; Peters, Jan Borgerink, Dian J.; Stegenga, Jan; Brouwer, Dannis M.; Wörtche, Heinrich; Stramigioli, Stefano
Quadratic Programming-Based Inverse Dynamics Control for Legged Robots with Sticking and Slipping Learning Robot Tactile Sensing for Object A Multi-AUV State Estimator for Determining the 3D 17:52- Frictional Contacts Manipulation Position of Tagged Fish 16 17:55 Zapolsky, Samuel; Drumwright, Evan Chebotar, Yevgen; Kroemer, Oliver; Peters, Jan Lin, Yukun; Kastein, Hannah; Peterson, Taylor; White, Connor; Lowe, Christopher G.; Clark, Christopher M.
71 Wednesday Session A, 09:00 - 10:20 Grand Ballroom State Ballroom Red Lacquer Room WeA1 WeA2 WeA3 Medical Robots and Systems II & Motion and Path Planning III & Networked Robots & Rehabilitation Robotics II Planning, Failure Detection and Recovery Swarm Robotics
Chair Taylor, Russell H. (Johns Hopkins University) Kroeger, Torsten (Google, Inc.) Vaughan, Richard (Simon Fraser University)
# Time Session Keynote Session Keynote Session Keynote Keynote: Towards Intelligent Robotic Surgical 09:00- Assistants Keynote: Planning for Complex High-Level Missions Keynote: Networked Robots 1 09:20 Cavusoglu, M. Cenk Kavraki, Lydia Rus, Daniela Case Western Reserve University Rice University MIT
Medical Robots and Systems II Motion and Path Planning III Networked Robots Nonlinear Dimensionality Reduction for Kinematic Task-Space Motion Planning of MRI-Actuated Cartography with an Application Toward Robotic Autonomous Wireless Backbone Deployment with 09:20- Catheters for Catheter Ablation of Atrial Fibrillation Locomotion Bounded Number of Networked Robots 2 09:23 Greigarn, Tipakorn; Cavusoglu, M. Cenk Dear, Tony; Hatton, Ross; Choset, Howie Santos, Elerson Rubens da Silva; Vieira, Marcos
Orienting in Mid-Air through Configuration Changes to Using Lie Algebra for Shape Estimation of Medical Achieve a Rolling Landing for Reducing Impact after a Point Cloud Culling for Robot Vision Tasks under 09:23- Snake Robots Fall Communication Constraints 3 09:26 Rangaprasad, Arun Srivatsan; Travers, Matthew; Bingham, Jeffrey; Lee, Jeongseok; Haksar, Ravi; Beksi, William; Papanikolopoulos, Nikos Choset, Howie Ueda, Jun; Liu, Karen
Robust Routing and Multi-Confirmation Transmission Modeling and Control of Robotic Surgical Platform for Motion Planning for Non-Holonomic Mobile Robots Protocol for Connectivity Management of Mobile 09:26- Single-Port Access Surgery Using the I-PID Controller and Potential Field Robotic Teams 4 09:29 Lee, Jusuk; Kim, Jiyoung; Lee, Kwang-Kyu; Hyung, Ma, Yingchong; Zheng, Gang; perruquetti, Wilfrid; Stephan, James; Fink, Jonathan; Charrow, Benjamin; SeungYong; Kim, Yong-Jae; Kwon, Woong; Roh, QIU, Zhaopeng Kumar, Vijay; Ribeiro, Alejandro Kyungshik; Choi, Jung-Yun Semi-Autonomous Navigation for Robot Assisted Tele- A Centralized-Equivalent Decentralized Echography Using Generalized Shape Models and Co- Spherical Parabolic Blends for Robot Workspace Implementation of Extended Kalman Filters for 09:29- Registered RGB-D Cameras Trajectories Cooperative Localization 5 09:32 Zhang, Lin; Lee, Su-Lin; Yang, Guang-Zhong; Dantam, Neil; Stilman, Mike Kia, Solmaz; Rounds, Stephen; Martinez, Sonia Mylonas, George
From Autonomy to Cooperative Traded Control of State Recognition of Bone Drilling with Audio Signal in Trajectory Planning for Car-Like Robots in Unknown, Humanoid Manipulation Tasks with Unreliable 09:32- Robotic Orthopedics Surgery System Unstructured Environments Communication: System Design and Lessons Learned 6 09:35 Sun, Yu; Jin, Haiyang; HU, Ying; Zhang, Peng; Zhang, Fassbender, Dennis; Mueller, Andre; Wuensche, Hans Mainprice, Jim; Phillips-Grafflin, Calder; Suay, Halit Jianwei J Bener; Alunni, Nicholas; Lofaro, Daniel; Berenson, Dmitry; Chernova, Sonia; Lindeman, Robert; Oh, Paul Y.
Estimating Contact Force for Steerable Ablation Fast, Dynamic Trajectory Planning for a Dynamically Route Swarm: Wireless Network Optimization through 09:35- Catheters Based on Shape Analysis Stable Mobile Robot Mobility 7 09:38 Khoshnam Tehrani, Mahta; Patel, Rajnikant V. Shomin, Michael; Hollis, Ralph Williams, Ryan; Gasparri, Andrea; Krishnamachari, Bhaskar
Predicting Kinematic Configuration from String Length for a Snake-Like Manipulator Not Exhibiting Constant Risk-Aware Trajectory Generation with Application to Cooperative Dynamic Behaviors in Networked 09:38- Curvature Bending Safe Quadrotor Landing Systems with Decentralized State Estimation 8 09:41 Murphy, Ryan Joseph; Otake, Yoshito; Taylor, Russell Mueller, Joerg; Sukhatme, Gaurav Sabattini, Lorenzo; Secchi, Cristian; Fantuzzi, Cesare H.; Armand, Mehran
Comparison of Methods for Estimating the Position of Hierarchical Robustness Approach for Nonprehensile Adding Transmission Diversity to Unmanned Systems 09:41- Actuated Instruments in Flexible Endoscopic Surgery Catching of Rigid Objects through Radio Switching and Directivity 9 09:44 Cabras, Paolo; Goyard, David; Nageotte, Florent; Pekarovskiy, Alexander; Stockmann, Ferdinand; Lowrance, Christopher John; Lauf, Adrian P. zanne, Philippe; Doignon, Christophe Okada, Masafumi; Buss, Martin
Robust Forceps Tracking Using Online Calibration of Hand-Eye Coordination for Microsurgical Robotic Parameterized Controller Generation for Multiple Effective Compression of Range Data Streams for System Mode Behavior Remote Robot Operations using H.264 09:44- 10 Tanaka, Shinichi; Baek, Young Min; Harada, Kanako; Gong, Chaohui; Travers, Matthew; Kao, Hsien-Tang; Nenci, Fabrizio; Spinello, Luciano; Stachniss, Cyrill 09:47 Sugita, Naohiko; Morita, Akio; Sora, Shigeo; Choset, Howie Nakatomi, Hirofumi; Saito, Nobuhito; Mitsuishi, Mamoru
MRI-Powered Closed-Loop Control for Multiple Extending Equilibria to Periodic Orbits for Walkers Network Lifetime Maximization in Mobile Visual 09:47- Magnetic Capsules Using Continuation Methods Sensor Networks 11 09:50 Eqtami, Alina; Felfoul, Ouajdi; Dupont, Pierre Rosa, Nelson; Lynch, Kevin Yu, Shengwei; Lee, C. S. George
72 Wednesday Session A, 09:00 - 10:20 (Continued) Grand Ballroom State Ballroom Red Lacquer Room WeA1 WeA2 WeA3
# Time Rehabilitation Robotics II Planning, Failure Detection and Recovery Swarm Robotics Development and Evaluation of an Operation Interface Task Assignment and Trajectory Optimization for for Physical Therapy Devices Based on Rehabilitation Global Registration of Mid-Range 3D Observations Displaying Stick Figure Animations with Multiple 09:50- Database and Short Range Next Best Views Mobile Robots 12 09:53 Tsuji, Toshiaki; Momiki, Chinami; Sakaino, Sho Aleotti, Jacopo; Lodi Rizzini, Dario; Monica, Riccardo; Yamane, Katsu; Goerner, Jared Caselli, Stefano
EMG-Based Continuous Control Method for Electric Worst-Case Optimal Average Consensus Estimators 09:53- Wheelchair Model-Free Robot Anomaly Detection for Robot Swarms 13 09:56 Jang, Giho; Choi, Youngjin Hornung, Rachel Hannah; Urbanek, Holger; Elwin, Matthew; Freeman, Randy; Lynch, Kevin Klodmann, Julian; Osendorfer, Christian; van der Smagt, Patrick
NTUH-II Robot Arm with Dynamic Torque Gain A Constraint-Based Method for Solving Sequential Robust Sensor Cloud Localization from Range 09:56- Adjustment Method for Frozen Shoulder Rehabilitation Manipulation Planning Problems Measurements 14 09:59 Lin, Chia-Hsun; Lien, Wei-Ming; Wang, Wei-Wen; Lozano-Perez, Tomas; Kaelbling, Leslie Dubbelman, Gijs; Duisterwinkel, Erik; Demi, Libertario; Chen, Sung-Hua; Lo, Chan-Hsiang; Lin, Sheng-Yen; Talnishnikh, Elena; Wörtche, Heinrich; Bergmans, Jan Fu, Li-Chen; Lai, Jin-Shin W. M.
Involuntary Movement During Haptics-Enabled Attack Resilient State Estimation for Autonomous Application of Grazing-Inspired Guidance Laws to 09:59- Robotic Rehabilitation: Analysis and Control Design Robotic Systems Autonomous Information Gathering 15 10:02 Atashzar, Seyed Farokh; Saxena, Abhijit; Shahbazi, Bezzo, Nicola; Weimer, James; Pajic, Miroslav; Apker, Thomas; Liu, Shih-Yuan; Sofge, Donald; Mahya; Patel, Rajnikant V. Sokolsky, Oleg; Pappas, George J.; Lee, Insup Hedrick, Karl
A Framework for Supervised Robotics-Assisted Mirror A Metric for Self-Rightability and Understanding Its 10:02- Rehabilitation Therapy Relationship to Simple Morphologies Human-Swarm Interaction Using Spatial Gestures 16 10:05 Shahbazi, Mahya; Atashzar, Seyed Farokh; Patel, Kessens, Chad C.; Lennon, Craig; Collins, Jason Nagi, Jawad; Giusti, Alessandro; Gambardella, Luca; Rajnikant V. Di Caro, Gianni A.
Development of an Upper Limb Exoskeleton Powered Sampling Based Motion Planning with Reachable Via Pneumatic Electric Hybrid Actuators with Bowden Volumes: Application to Manipulators and Closed Mapping of Unknown Environments Using Minimal 10:05- Cable Chain Systems Sensing from a Stochastic Swarm 17 10:08 Noda, Tomoyuki; Teramae, Tatsuya; Ugurlu, Barkan; McMahon, Troy; Thomas, Shawna; Amato, Nancy Dirafzoon, Alireza; Betthauser, Joseph; Schornick, Morimoto, Jun Jeff; Benavides, Daniel; Lobaton, Edgar
A Novel Customized Cable-Driven Robot for 3-DOF Probabilistically Complete Kinodynamic Planning for Probabilistic Guidance of Distributed Systems Using 10:08- Wrist and Forearm Motion Training Robot Manipulators with Acceleration Limits Sequential Convex Programming 18 10:11 Cui, Xiang; Chen, Weihai; Agrawal, Sunil; Wang, Kunz, Tobias; Stilman, Mike Morgan, Daniel; Subramanian, Giri Prashanth; Jianhua Bandyopadhyay, Saptarshi; Chung, Soon-Jo; Hadaegh, Fred Run-Time Detection of Faults in Autonomous Mobile Identifying Inverse Human Arm Dynamics Using a Robots Based on the Comparison of Simulated and Geodesic Topological Voronoi Tessellations in 10:11- Robotic Testbed Real Robot Behaviour Triangulated Environments with Multi-Robot Systems 19 10:14 Schearer, Eric; Liao, Yu-Wei; Perreault, Eric; Tresch, Millard, Alan Gregory; Timmis, Jon; Winfield, Alan Lee, Seoung Kyou; Fekete, Sándor; McLurkin, James Matthew; Memberg, William; Kirsch, Robert; Lynch, Kevin A Risk Assessment Infrastructure for Powered Sampling-Based Tree Search with Discrete Wheelchair Motion Commands without Full Sensor Abstractions for Motion Planning with Dynamics and Outdoor Flocking and Formation Flight with 10:14- Coverage Temporal Logic Autonomous Aerial Robots 20 10:17 TalebiFard, Pouria; Sattar, Junaed; Mitchell, Ian McMahon, James; Plaku, Erion Vásárhelyi, Gábor; Virágh, Csaba; Somorjai, Gergo; Tarcai, Norbert; Szörényi, Tamás; Nepusz, Tamás; Vicsek, Tamas
LINarm: a Low-cost Variable Stiffness Device for Distributed Fault Detection and Recovery for Sponsor Talk: Autonomous Robot Fleets for 10:17- Upper-limb Rehabilitation Networked Robots Automated Warehouses 21 10:20 Malosio, Matteo; Caimmi, Marco; Legnani, Giovanni; Arrichiello, Filippo; Marino, Alessandro; Pierri, Sweet, Larry Molinari, Lorenzo Francesco Symbotic LLC
73 Wednesday Session B, 10:50 - 12:10 Grand Ballroom State Ballroom Red Lacquer Room WeB1 WeB2 WeB3 Mechanisms and Actuators & Humanoids and Bipeds III & Collision Detection and Avoidance & Force and Tactile Sensing Human Detection and Tracking Sensing II
Chair Okamura, Allison M. (Stanford University) Bertrand, Sylvain (IHMC) MacDonald, Bruce (University of Auckland)
# Time Session Keynote Session Keynote Session Keynote Keynote: Natural Machine Motion and Embodied Keynote: Bayesian Perception & Decision From 10:50- Intelligence Keynote on Humanoids and Bipeds Theory to Real World Applications 1 11:10 Bicchi, Antonio Hong, Dennis Laugier, Christian University of Pisa UCLA INRIA
Mechanisms and Actuators Humanoids and Bipeds III Collision Detection and Avoidance Dynamic Trajectory Planning of Planar 2-Dof Redundantly Actuated Cable-Suspended Parallel Real-Time Collision Avoidance in Human-Robot 11:10- Robots 3D-SLIP Steering for High-Speed Humanoid Turns Interaction Based on Kinetostatic Safety Field 2 11:13 Tang, Lewei; Gosselin, Clement; Tang, Xiaoqiang; Wensing, Patrick; Orin, David Parigi Polverini, Matteo; Zanchettin, Andrea Maria; Jiang, Xiaoling Rocco, Paolo
Workspace Augmentation of Spatial 3-DOF Cable Emergence of Humanoid Walking Behaviors from Determining States of Inevitable Collision Using 11:13- Parallel Robots Using Differential Actuation Mixed-Integer Model Predictive Control Reachability Analysis 3 11:16 Khakpour, Hamed; Birglen, Lionel Ibanez, Aurélien; Bidaud, Philippe; Padois, Vincent Lawitzky, Andreas; Nicklas, Anselm; Wollherr, Dirk; Buss, Martin
Trajectory Generation for Continuous Leg Forces Tendon Routing Resolving Inverse Kinematics for During Double Support and Heel-To-Toe Shift Based Collision Prediction among Polygons with Arbitrary 11:16- Variable Stiffness Joint on Divergent Component of Motion Shape and Unknown 4 11:19 Shirafuji, Shouhei; Ikemoto, Shuhei; Hosoda, Koh Englsberger, Johannes; Koolen, Twan; Bertrand, Lu, Yanyan; Xi, Zhonghua; Lien, Jyh-Ming Sylvain; Pratt, Jerry; Ott, Christian; Albu-Schäffer, Alin
Drum Stroke Variation Using Variable Stiffness Model Preview Control in Multi-Contact Motion - Unified GPU Voxel Collision Detection for Mobile 11:19- Actuators Application to a Humanoid Robot Manipulation Planning 5 11:22 Kim, Yongtae; Garabini, Manolo; Park, Jaeheung; Audren, Hervé; Vaillant, Joris; Kheddar, Hermann, Andreas; Drews, Florian; Bauer, Jörg; Bicchi, Antonio Abderrahmane; Escande, Adrien; Kaneko, Kenji; Klemm, Sebastian; Roennau, Arne; Dillmann, Rüdiger Yoshida, Eiichi A Practical Reachability-Based Collision Avoidance Predictive Control for Dynamic Locomotion of Real Algorithm for Sampled-Data Systems: Application to 11:22- Compliant Robotic Systems on Graphs Humanoid Robots Ground Robots 6 11:25 Groothuis, Stefan S.; Stramigioli, Stefano; Carloni, Piperakis, Stylianos; Orfanoudakis, Emmanouil; Dabadie, Charles; Kaynama, Shahab; Tomlin, Claire Raffaella Lagoudakis, Michail
Reaching desired states time-optimally from Time Scaled Collision Cone Based Trajectory equilibrium and vice versa for visco-elastic joint robots A Robot-Machine Interface for Full-Functionality Optimization Approach for Reactive Planning in 11:25- with limited elastic deflection Automation Using a Humanoid Dynamic Environments 7 11:28 Mansfeld, Nico; Haddadin, Sami Jeong, Heejin; Shim, David Hyunchul; Cho, Sungwook Singh, Arun Kumar; GOPALAKRISHNAN, BHARATH; Krishna, Madhava
A Representation Method Based on the Probability of Force-Guiding Particle Chains for Shape-Shifting Planar Sliding Analysis of a Biped Robot in Centroid Collision for Safe Robot Navigation in Domestic 11:28- Displays Acceleration Space Environments 8 11:31 Lasagni, Matteo; Roemer, Kay Senoo, Taku; Ishikawa, Masatoshi Coenen, Sebastiaan Antonius Maria; Lunenburg, Janno Johan Maria; van de Molengraft, Marinus Jacobus Gerardus; Steinbuch, Maarten
A Class of Microstructures for Scalable Collective Energy Based Control of Compass Gait Soft Limbed 11:31- Actuation of Programmable Matter Bipeds Real-Time 3D Collision Avoidance for Biped Robots 9 11:34 Holobut, Pawel; Kursa, Michał; Lengiewicz, Godage, Isuru S.; Wang, Yue; Walker, Ian Hildebrandt, Arne-Christoph; Wittmann, Robert; Jakub Wahrmann, Daniel; Ewald, Alexander; Buschmann, Thomas HiGen: A High-Speed Genderless Mechanical Analytical Control Parameters of the Swing Leg Connection Mechanism with Single-Sided Disconnect Retraction Method using an Instantaneous SLIP Ensuring Safety in Human-Robot Coexistence 11:34- for Self-Reconfigurable Modular Robots Model Environment 10 11:37 Parrott, Christopher; Dodd, T J; Gross, Roderich Shemer, Natan; Degani, Amir Tsai, Chi-Shen; Hu, Jwu-Sheng; Tomizuka, Masayoshi
A Unified Framework for External Wrench Estimation, Task-Oriented Whole-Body Planning for Humanoids Interaction Control and Collision Reflexes for Flying 11:37- Stretchable Electroadhesion for Soft Robots Based on Hybrid Motion Generation Robots 11 11:40 Germann, Juerg Markus; Schubert, Bryan; Floreano, Cognetti, Marco; Mohammadi, Pouya; Oriolo, Tomic, Teodor; Haddadin, Sami Dario Giuseppe; Vendittelli, Marilena
74 Wednesday Session B, 10:50 - 12:10 (Continued) Grand Ballroom State Ballroom Red Lacquer Room WeB1 WeB2 WeB3
# Time Force and Tactile Sensing Human Detection and Tracking Sensing II
Real-Time People Detection and Tracking for Indoor Deterioration of Depth Measurements Due to 11:40- Miniature Capacitive Three-Axis Force Sensor Surveillance Using Multiple Top-View Depth Cameras Interference of Multiple RGB-D Sensors 12 11:43 Bekhti, Rachid; Duchaine, Vincent; Cardou, Philippe Tseng, Ting-En; Liu, An-Sheng; Hsiao, Po-Hao; Martín Martín, Roberto; Lorbach, Malte; Brock, Oliver Huang, Cheng-Ming; Fu, Li-Chen
Robot-Assisted Human Indoor Localization Using the IMU/LIDAR Based Positioning of a Gangway for 11:43- A Framework for Dynamic Sensory Substitution Kinect Sensor and Smartphones Maintenance Operations on Wind Farms 13 11:46 Mkhitaryan, Artashes; Burschka, Darius Jiang, Chao; Fahad, Muhammad; Guo, Yi; Yang, Jie; merriaux, Pierre; Boutteau, Rémi; Vasseur, Pascal; Chen, Yingying Savatier, Xavier
High-Throughput Analysis of the Morphology and Mechanics of Tip Growing Cells Using a Microrobotic Gesture-Based Attention Direction for a Telepresence A Quantitative Evaluation of Surface Normal 11:46- Platform Robot: Design and Experimental Study Estimation in Point Clouds 14 11:49 Felekis, Dimitrios; Vogler, Hannes; Mecja, Geraldo; Tee, Keng Peng; Yan, Rui; Chua, Yuanwei; Huang, Jordan, Krzysztof; Mordohai, Philippos Muntwyler, Simon; Sakar, Mahmut Selman; Zhiyong; Liemhetcharat, Somchaya Grossniklaus, Ueli; Nelson, Bradley J.
What's in the Container? Classifying Object Contents Kinect-Based People Detection and Tracking from View Planning for 3D Object Reconstruction with a 11:49- from Vision and Touch Small-Footprint Ground Robots Mobile Manipulator Robot 15 11:52 Güler, Püren; Bekiroglu, Yasemin; Kragic, Danica; Pesenti Gritti, Armando; Tarabini, Oscar; Guzzi, Vasquez-Gomez, J. Irving; Sucar, Luis Enrique; Gratal Martínez, Xavi; Pauwels, Karl Jerome; Di Caro, Gianni A.; caglioti, vincenzo; Murrieta-Cid, Rafael Gambardella, Luca; Giusti, Alessandro
3D Spatial Self-Organization of a Modular Artificial Robust Articulated Upper Body Pose Tracking under Planar Pose Estimation for General Cameras Using 11:52- Skin Severe Occlusions Known 3D Lines 16 11:55 Mittendorfer, Philipp; Dean-Leon, Emmanuel; Cheng, Sigalas, Markos; Pateraki, Maria; Trahanias, Panos Miraldo, Pedro; Araujo, Helder Gordon
Detection of Membrane Puncture with Haptic Pedestrian Detection Combining RGB and Dense GPS-Based Preliminary Map Estimation for 11:55- Feedback Using a Tip-Force Sensing Needle LIDAR Data Autonomous Vehicle Mission Preparation 17 11:58 Elayaperumal, Santhi; Bae, Jung Hwa; Daniel, Bruce; Premebida, Cristiano; Carreira, Joao Luis da Silva; Dupuis, Yohan; merriaux, Pierre; Subirats, Peggy; Cutkosky, Mark Batista, Jorge; Nunes, Urbano Boutteau, Rémi; Savatier, Xavier; Vasseur, Pascal
Confidence-Based Pedestrian Tracking in Unstructured Environments Using 3D Laser Distance Dynamic Objects Tracking with a Mobile Robot Using 11:58- Active Gathering of Frictional Properties from Objects Measurements Passive UHF RFID Tags 18 12:01 Rosales, Carlos; Ajoudani, Arash; Gabiccini, Marco; Häselich, Marcel; Jöbgen, Benedikt; Wojke, Nicolai; Liu, Ran; Huskić, Goran; Zell, Andreas Bicchi, Antonio Hedrich, Jens; Paulus, Dietrich
Whole-Body Pose Estimation in Physical Rider-Bicycle Localization and Manipulation of Small Parts Using Interactions with a Monocular Camera and a Set of Spatio-Temporal Motion Features for Laser-Based 12:01- GelSight Tactile Sensing Wearable Gyroscopes Moving Objects Detection and Tracking 19 12:04 Li, Rui; Platt, Robert; Yuan, Wenzhen; ten Pas, Lu, Xiang; Yu, Kaiyan; Zhang, Yizhai; Yi, Jingang; Liu, Shen, Xiaotong; Kim, Seong-Woo; Ang Jr, Marcelo H Andreas; Roscup, Nathan; Srinivasan, Mandayam; Jingtai Adelson, Edward
Exploiting Global Force Torque Measurements for Pedalvatar: An IMU-Based Real-Time Body Motion The Role of Target Modeling in Designing Search 12:04- Local Compliance Estimation in Tactile Arrays Capture System Using Foot Rooted Kinematic Model Strategies 20 12:07 Ciliberto, Carlo; Fiorio, Luca; Maggiali, Marco; Natale, Zheng, Yang; Chan, Ka Chun; Wang, Charlie C.L. Renzaglia, Alessandro; Noori, Narges; Isler, Volkan Lorenzo; Rosasco, Lorenzo; Metta, Giorgio; SANDINI, GIULIO; Nori, Francesco Toward a Modular Soft Sensor-Embedded Glove for Human Hand Motion and Tactile Pressure Advances in Fibrillar On-Off Polymer Adhesive: 12:07- Measurement Sponsor Talk: TOYOTA - Partner Robot Sensing and Engagement Speed 21 12:10 Hammond III, Frank L.; Menguc, Yigit; Wood, Robert Djugash, Joseph Wettels, Nicholas; Parness, Aaron Toyota Motor Eng. & Manuf. North America
75 Wednesday Session C, 14:00 - 15:20 Grand Ballroom State Ballroom Red Lacquer Room WeC1 WeC2 WeC3 Surgical Robotics II & Learning by Demonstration & Localization and Mapping IV & Teleoperation and Telerobotics Industrial and Manufacturing Robotics Locomotion, Navigation, and Mobility
Chair Hamel, William R. (University of Tennessee) Parker, Lynne (University of Tennessee) Antonelli, Gianluca (Univ. of Cassino and S. Lazio)
# Time Session Keynote Session Keynote Session Keynote Keynote: Machine Learning of Motor Skills for Keynote: Toward Persistent SLAM in Challenging 14:00- Keynote: Surgical Robotics: Transition to Automation Robotics Environments 1 14:20 Hannaford, Blake Peters, Jan Eustice, Ryan University of Washington TU Darmstadt University of Michigan
Surgical Robotics II Learning by Demonstration Localization and Mapping IV Bimanual Telerobotic Surgery with Asymmetric Haptic A Robust Autoregressive Gaussian Process Motion Force Feedback: A Davinci Surgical System Model Using L1-Norm Based Low-Rank Kernel Simultaneous Localization and Planning on Multiple 14:20- Implementation Approximation Map Hypotheses 2 14:23 Mohareri, Omid; Schneider, Caitlin; Salcudean, Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai Morris, Timothy; Dayoub, Feras; Corke, Peter; Septimiu E. Upcroft, Ben
First 3D Printed Medical Robot for ENT Surgery - Unifying Scene Registration and Trajectory Long--Term Topological Localisation for Service Application Specific Manufacturing of Laser Sintered Optimization for Learning from Demonstrations with Robots in Dynamic Environments Using Spectral 14:23- Disposable Manipulators Application to Manipulation of Deformable Objects Maps 3 14:26 Entsfellner, Konrad; Kuru, Ismail; Maier, Thomas; Lee, Alex Xavier; Huang, Sandy; Hadfield-Menell, Krajník, Tomás; Pulido Fentanes, Jaime; Martinez Gumprecht, Jan David Jerome; Lueth, Tim C. Dylan; Tzeng, Eric; Abbeel, Pieter Mozos, Oscar; Duckett, Tom; Ekekrantz, Johan; Hanheide, Marc
Mass and Inertia Optimization for Natural Motion in Robot Learns Chinese Calligraphy from SAIL-MAP: Loop-Closure Detection Using Saliency- 14:26- Hands-On Robotic Surgery Demonstrations Based Features 4 14:29 Petersen, Joshua; Rodriguez y Baena, Ferdinando Sun, Yuandong; QIAN, Huihuan; Xu, Yangsheng BIREM, Merwan; QUINTON, Jean-Charles; berry, francois; Mezouar, Youcef
Interleaved Continuum-Rigid Manipulation Approach: Development and Functional Evaluation of a Clinical Learning to Sequence Movement Primitives from Visual Place Recognition using HMM Sequence 14:29- Scale Manipulator Demonstrations Matching 5 14:32 Conrad, Benjamin; Zinn, Michael Manschitz, Simon; Kober, Jens; Gienger, Michael; Hansen, Peter; Browning, Brett Peters, Jan
Using Monocular Images to Estimate Interaction Linear-Time Estimation with Tree Assumed Density 14:32- Forces During Minimally Invasive Surgery Kinematically Optimised Predictions of Object Motion Filtering and Low-Rank Approximation 6 14:35 Noohi, Ehsan; Parastegari, Sina; Zefran, Milos Belter, Dominik; Wyatt, Jeremy; Kopicki, Marek; Zurek, Ta, Duy-Nguyen; Dellaert, Frank Sebastian
Large-Scale Image Mosaicking Using Multimodal Hyperedge Constraints from Multiple Registration Recursive Estimation of Needle Pose for Control of 3D- Program Synthesis by Examples for Object Methods within the Generalized Graph SLAM 14:35- 7 Ultrasound-Guided Robotic Needle Steering Repositioning Tasks Framework 14:38 Adebar, Troy K.; Okamura, Allison M. Feniello, Ashley; Dang, Hao; Birchfield, Stan Pfingsthorn, Max; Birk, Andreas; Ferreira, Fausto; Veruggio, Gianmarco; Caccia, Massimo; Bruzzone, Gabriele Development of Multi-Axial Force Sensing System for Localization Algorithm Based on Zigbee Wireless Haptic Feedback Enabled Minimally Invasive Robotic Sensor Network with Application to an Active 14:38- Surgery LAT: A Simple Learning from Demonstration Method Shopping Cart 8 14:41 Lee, Dong-Hyuk; Kim, Uikyum; Choi, Hyouk Ryeol Reiner, Benjamin; Ertel, Wolfgang; Posenauer, Heiko; Gai, Shengnan; Jung, Eui-jung; Yi, Byung-Ju Schneider, Markus
Estimation of Needle Tissue Interaction Based on Non-Discovering Task Constraints through Observation and RF Odometry for Localization in Pipes Based on 14:41- Linear Elastic Modulus and Friction Force Patterns Active Learning Periodic Signal Fadings 9 14:44 Elgezua Fernandez, Inko; Kobayashi, Yo; Fujie, Hayes, Bradley; Scassellati, Brian Rizzo, Carlos; Kumar, Vijay; Lera, Francisco; Masakatsu G. Villarroel, José Luis
Design and Realization of Grasper-Integrated Force Unsupervised Object Individuation from RGB-D Image Multi-Vehicle Localisation with Additive Compressed 14:44- Sensor for Minimally Invasive Robotic Surgery Sequences Factor Graphs 10 14:47 Kim, Uikyum; Lee, Dong-Hyuk; Choi, Hyouk Ryeol; Koo, Seongyong; Lee, Dongheui; Kwon, Dong-Soo Toohey, Lachlan; Pizarro, Oscar; Williams, Stefan Moon, Hyungpil; Koo, Ja Choon Bernard
A Biomechanical Model Describing Tangential Tissue Grasp Planning Based on Strategy Extracted from Building Local Terrain Maps Using Spatio-Temporal 14:47- Deformations During Contact Micro-Probe Scanning Demonstration Classification for Semantic Robot Localization 11 14:50 Rosa, Benoît; Morel, Guillaume; Szewczyk, Jérôme Lin, Yun; Sun, Yu Laible, Stefan; Zell, Andreas
76 Wednesday Session C, 14:00 - 15:20 (Continued) Grand Ballroom State Ballroom Red Lacquer Room WeC1 WeC2 WeC3
# Time Teleoperation and Telerobotics Industrial and Manufacturing Robotics Locomotion, Navigation, and Mobility
Industrial Robotic Assembly Process Modeling Using Stiffness Modeling of Industrial Robots for HexaMorph: A Reconfigurable and Foldable Hexapod 14:50- Support Vector Regression Deformation Compensation in Machining Robot Inspired by Origami 12 14:53 Li, Binbin; Chen, Heping; Jin, Tongdan Schneider, Ulrich; Momeni, Mahdi; Ansaloni, Matteo; Gao, Wei; Huo, Ke; Seehra, Jasjeet Singh; Ramani, Verl, Alexander Karthik; Cipra, Raymond
A Study on Data-Driven In-Hand Twisting Process Teleoperation System Using past Image Records for Using a Novel Dexterous Robotic Gripper for On the Optimal Selection of Motors and Transmissions 14:53- Mobile Manipulator Assembly Automation for Electromechanical and Robotic Systems 13 14:56 Murata, Ryosuke; Songtong, Sira; Mizumoto, Hisashi; Chen, Fei; Cannella, Ferdinando; Canali, Carlo; Rezazadeh, Siavash; Hurst, Jonathan Kon, Kazuyuki; Matsuno, Fumitoshi Hauptman, Traveler; Sofia, Giuseppe; Caldwell, Darwin G. Active Behavior of Musculoskeletal Robot Arms Driven Experimental Evaluation of Guidance and Forbidden Velocity Coordination and Corner Matching in a Multi- by Pneumatic Artificial Muscles for Receiving Human's 14:56- Region Virtual Fixtures for Object Telemanipulation Robot Sewing Cell Direct Teaching Effectively 14 14:59 King, H. Hawkeye; Hannaford, Blake Schrimpf, Johannes; Bjerkeng, Magnus; Mathisen, Ikemoto, Shuhei; Kayano, Yuji; Hosoda, Koh Geir
Investigating Human Perceptions of Robot Capabilities in Remote Human-Robot Team Tasks Based on First- On the Location of the Center of Mass for Parts with Received Signal Strength Based Bearing-Only Robot 14:59- Person Robot Video Feeds Shape Variation Navigation in a Sensor Network Field 15 15:02 Canning, Cody; Donahue, Thomas; Scheutz, Matthias Panahi, Fatemeh; van der Stappen, Frank Deshpande, Nikhil; Grant, Edward; Draelos, Mark; Henderson, Thomas C.
Know Thy User: Designing Human-Robot Interaction Design and Motion Planning of Body-In-White GeckoGripper: A Soft, Inflatable Robotic Gripper Using 15:02- Paradigms for Multi-Robot Manipulation Assembly Cells Gecko-Inspired Elastomer Micro-Fiber Adhesives 16 15:05 Lewis, Bennie; Sukthankar, Gita Pellegrinelli, Stefania; Pedrocchi, Nicola; Molinari Song, Sukho; Majidi, Carmel; Sitti, Metin Tosatti, Lorenzo; Fischer, Anath; Tolio, Tullio A. M.
Modeling Visuo-Motor Control and Guidance Cartesian Sensor-Less Force Control for Industrial Design and Architecture of a Series Elastic Snake Functions in Remote-Control Operation Robots Robot 15:05- 17 Andersh, Jonathan; Li, Bin; Mettler, Berenice Cho, Hyunchul; Kim, Min Jeong; Lim, Hyunkyu; Kim, Rollinson, David; Bilgen, Yigit; Brown, H. Ben; Enner, 15:08 Donghyeok Florian; Ford, Steven; Layton, Curtis; Rembisz, Justine; Schwerin, Michael; Willig, Andrew; Velagapudi, Prasanna; Choset, Howie Transparency Compensation for Bilateral Teleoperators with Time-Varying Communication Improving the Sequence of Robotic Tasks with Hybrid Unmanned Aerial Underwater Vehicle: 15:08- Delays Freedom of Execution Modeling and Simulation 18 15:11 Rodriguez-Seda, Erick J. Alatartsev, Sergey; Ortmeier, Frank Drews Jr, Paulo; Alves Neto, Armando; Campos, Mario Montenegro
Model-Free Path Planning for Redundant Robots Parallel Active/Passive Force Control of Industrial Circumnavigation by a Mobile Robot Using Bearing 15:11- Using Sparse Data from Kinesthetic Teaching Robots with Joint Compliance Measurements 19 15:14 Seidel, Daniel; Emmerich, Christian; Steil, Jochen J. Dayal, Udai, Arun; Hayat, Abdullah Aamir; Saha, Subir Zheng, Ronghao; Sun, Dong Kumar
Learning Task Outcome Prediction for Robot Control Automated Guidance of Peg-In-Hole Assembly Tasks 15:14- from Interactive Environments for Complex-Shaped Parts 20 15:17 Haidu, Andrei; Daniel, Kohlsdorf; Beetz, Michael Song, Hee-Chan; Kim, Young-Loul; Song, Jae-Bok
Intuitive Skill-Level Programming of Industrial 15:17- Handling Tasks on a Mobile Manipulator 21 15:20 Pedersen, Mikkel Rath; Herzog, Dennis Levin; Krueger, Volker
77 Wednesday Session D, 15:50 - 17:10 Grand Ballroom State Ballroom Red Lacquer Room WeD1 WeD2 WeD3 Micro-Nano Robots II & Unmanned Aerial Systems II & Computer Vision II & Impedance, Compliance, and Force Control Legged Robots II Recognition
Chair Sun, Dong (City University of Hong Kong) Carloni, Raffaella (University of Twente) Martinet, Philippe (Ecole Centrale de Nantes)
# Time Session Keynote Session Keynote Session Keynote Keynote: Soft, printable, and small: an overview of Keynote: Material-Handling - Paradigms for Keynote: Semantic Parsing in Indoors and Outdoors 15:50- manufacturing methods for novel robots at Harvard Humanoids and UAVs Environments 1 16:10 Wood, Robert Oh, Paul Y. Kosecka, Jana Harvard University University of Nevada, Las Vegas (UNLV) George Mason University
Micro-Nano Robots II Unmanned Aerial Systems II Computer Vision II
Modeling and experiments of high speed magnetic Robust Attitude Controller for Uncertain Hexarotor A Model-Free Approach for the Segmentation of 16:10- micromanipulation at the air/liquid interface Micro Aerial Vehicles (MAVs) Unknown Objects 2 16:13 Dkhil, Mohamed; Bolopion, Aude; Gauthier, Michael; Derawi, Dafizal; Salim, Nurul Dayana; Zamzuri, Hairi; ASIF, UMAR; Bennamoun, Mohammed; Sohel, Régnier, Stéphane Liu, Hao; Abdul Rahman, Mohd Azizi; Mazlan, Saiful Ferdous Amri
Assembly and Mechanical Characterizations of Emergency Landing for a Quadrotor in Case of a Automatic Detection of Pole-Like Structures in 3D 16:13- Polymer Microhelical Devices Propeller Failure: A Backstepping Approach Urban Environments 3 16:16 Alvo, Sébastien; Decanini, Dominique; Couraud, Lippiello, Vincenzo; Ruggiero, Fabio; Serra, Diana Tombari, Federico; Fioraio, Nicola; Cavallari, Laurent; Haghiri-Gosnet, Anne-Marie; Hwang, Tommaso; Salti, Samuele; Petrelli, Alioscia; Di Gilgueng Stefano, Luigi Real-Time and Low Latency Embedded Computer Controllable Roll-To-Swim Motion Transition of Helical Guaranteed Road Network Search with Small Vision Hardware Based on a Combination of FPGA 16:16- Nanoswimmers Unmanned Aircraft and Mobile CPU 4 16:19 Barbot, Antoine; Decanini, Dominique; Hwang, Dille, Michael; Grocholsky, Ben; Singh, Sanjiv Honegger, Dominik; Oleynikova, Helen; Pollefeys, Gilgueng Marc
Three Dimensional Rotation of Bovine Oocyte by A Ground-Based Optical System for Autonomous Multi-View Terrain Classification Using Panoramic 16:19- using Magnetically Driven On-chip Robot Landing of a Fixed Wing UAV Imagery and LIDAR 5 16:22 Feng, Lin; U, Ningga; Turan, Bilal; Arai, Fumihito Kong, Weiwei; Zhou, Dianle; Zhang, Yu; Zhang, Taghavi Namin, Sarah; Najafi, Mohammad; Petersson, Daibing; Wang, Xun; Zhao, Boxin; Yan, Chengping; Lars Shen, Lincheng; Zhang, Jianwei
Robust Nanomanipulation Control Based on Laser Efficient Real-Time Loop Closure Detection Using 16:22- Beam Feedback On Crop Height Estimation with UAVs GMM and Tree Structure 6 16:25 Amari, Nabil; Folio, David; Ferreira, Antoine Anthony, David; Elbaum, Sebastian; Lorenz, Aaron; BOULEKCHOUR, MOHAMMED; Aouf, Nabil Detweiler, Carrick
Microrobotic Platform for Mechanical Stimulation of Model-Aided State Estimation for Quadrotor Micro Air Place Categorization using Sparse and Redundant 16:25- Swimming Microorganism on a Chip Vehicles Amidst Wind Disturbances Representations 7 16:28 Ahmad, Belal; Kawahara, Tomohiro; Yasuda, Takashi; Abeywardena, Dinuka; Wang, Zhan; Dissanayake, Carrillo, Henry; Latif, Yasir; Neira, José; Castellanos, Arai, Fumihito Gamini; Waslander, Steven Lake; Kodagoda, Sarath Jose A.
Real-Time Global Localization of Intelligent Road Magnetic-Based Motion Control of Sperm-Shaped Inspection of Pole-Like Structures Using Vision- Vehicles in Lane-Level Via Lane Marking Detection 16:28- Microrobots Using Weak Oscillating Magnetic Fields Controlled VTOL UAV and Shared Autonomy and Shape Registration 8 16:31 Khalil, Islam S.M.; Youakim, Kareem; Sanchez Sa, Inkyu; Hrabar, Stefan; Corke, Peter Cui, Dixiao; Xue, Jianru; Du, Shaoyi; Zheng, Nanning Secades, Luis Alonso; Misra, Sarthak
On-Chip Flexible Scaffold for Construction of Image-Based Control for Dynamically Cross-Coupled On-Road Vehicle Detection through Part Model Multishaped Tissues Aerial Manipulation Learning and Probabilistic Inference 16:31- 9 Chumtong, Puwanan; Kojima, Masaru; Horade, Mebarki, Rafik; Lippiello, Vincenzo; Siciliano, Bruno Wang, Chao; Zhao, Huijing; Guo, Chunzhao; Mita, 16:34 Mitsuhiro; Ohara, Kenichi; Kamiyama, Kazuto; Mae, Seiichi; Zha, Hongbin Yasushi; Akiyama, Yoshikatsu; Yamato, Masayuki; Arai, Tatsuo
The Quadroller: Modeling of a UAV/UGV Hybrid 16:34- Cell Isolation System for Rare Circulating Tumor Cell Quadrotor Real-time Depth Enhanced Monocular Odometry 10 16:37 Masuda, Taisuke; Sun, Yiling; Song, Woneui; Niimi, Page, Jared; Pounds, Paul Zhang, Ji; Kaess, Michael; Singh, Sanjiv Miyako; Yusa, Akiko; Hayao, Nakanishi; Arai, Fumihito
Incorporating In-Situ Force Sensing Capabilities in a Persistent monitoring with a team of autonomous 16:37- Magnetic Microrobot gliders using static soaring MEVO: Multi-Environment Stereo Visual Odometry 11 16:40 Jing, Wuming; Cappelleri, David Acevedo, José Joaquín; Lawrance, Nicholas Robert Koletschka, Thomas; Puig, Luis; Daniilidis, Kostas Jonathon; Arrue, Begoña C.; Sukkarieh, Salah; Ollero, Anibal
78 Wednesday Session D, 15:50 - 17:10 (Continued) Grand Ballroom State Ballroom Red Lacquer Room WeD1 WeD2 WeD3
# Time Impedance, Compliance, and Force Control Legged Robots II Recognition Place Recognition and Self-Localization in Interior Joint Space Torque Controller Based on Time-Delay Compliant Terrain Legged Locomotion Using a Hallways by Indoor Mobile Robots: A Signature-Based 16:40- Control with Collision Detection Viscoplastic Approach Cascaded Filtering Framework 12 16:43 Hur, Sung-moon; Oh, Sang-Rok; Oh, Yonghwan Vasilopoulos, Vasileios; Paraskevas, Iosif S.; Ahmad Yousef, Khalil; Park, Johnny; Kak, Avinash Papadopoulos, Evangelos
Force/vision Control for Robotic Cutting of Soft Passive Dynamic Walking of Compass-Like Biped Automated Perception of Safe Docking Locations with 16:43- Materials Robot with Dynamic Absorbers Alignment Information for Assistive Wheelchairs 13 16:46 Long, Philip; Khalil, Wisama; Martinet, Philippe Akutsu, Yukihiro; Asano, Fumihiko; Tokuda, Isao Jain, Siddarth; Argall, Brenna
Hierarchical Inequality Task Specification for Indirect More Solutions Means More Problems: Resolving Force Controlled Robots Using Quadratic Kinematic Redundancy in Robot Locomotion on 16:46- Programming Complex Terrain Terrain Classification Using Laser Range Finder 14 16:49 Lutscher, Ewald; Cheng, Gordon Satzinger, Brian; Reid, Jason; Bajracharya, Max; Walas, Krzysztof, Tadeusz; Nowicki, Micha Hebert, Paul; Byl, Katie
Fast Dual-Arm Manipulation Using Variable Admittance Control: Implementation and Experimental Hopping Control for the Musculoskeletal Bipedal A Novel Feature for Polyp Detection in Wireless 16:49- Results Robot BioBiped Capsule Endoscopy Images 15 16:52 Bjerkeng, Magnus; Schrimpf, Johannes; Myhre, Ahmad Sharbafi, Maziar; Radkhah, Katayon; von Yuan, Yixuan; Meng, Max Q.-H. Torstein; Pettersen, Kristin Y. Stryk, Oskar; Seyfarth, Andre
External Torque Sensing Algorithm for Flexible-Joint A Passive Dynamic Quadruped That Moves in a Large Automation of "Ground Truth" Annotation for Multi- 16:52- Robot Based on Disturbance Observer Structure Variety of Gaits View RGB-D Object Instance Recognition Datasets 16 16:55 Park, Young Jin; Chung, Wan Kyun Gan, Zhenyu; Remy, C. David Aldoma, Aitor; Fäulhammer, Thomas; Vincze, Markus
Implicit Force Control for an Industrial Robot with Velocity Disturbance Rejection for Planar Bipeds Recognition of Inside Pipeline Geometry by Using 16:55- Flexible Joints and Flexible Links Walking with HZD-Based Control PSD Sensors for Autonomous Navigation 17 16:58 Rossi, Roberto; Bascetta, Luca; Rocco, Paolo Post, David; Schmiedeler, James Choi, Yun Seok; Kim, Ho Moon; Suh, Jung Seok; Mun, Hyeong Min; Yang, Seung Ung; Park, Chan Min; Choi, Hyouk Ryeol
Cartesian Space Synchronous Impedance Control of Reactive Posture Behaviors for Stable Legged Large Scale Place Recognition in 2D LIDAR Scans 16:58- Two 7-DOF Robot Arm Manipulators Locomotion Over Steep Inclines and Large Obstacles Using Geometrical Landmark Relations 18 17:01 Jin, Minghe; Zhang, Zijian; Ni, Fenglei; Liu, Hong Roennau, Arne; Heppner, Georg; Nowicki, Himstedt, Marian; Hartmann, Jan; Hellbach, Sven; Micha; Zöllner, Johann Marius; Dillmann, Boehme, Hans-Joachim; Maehle, Erik Rüdiger
Fully Omnidirectional Compliance in Mobile Robots The Effect of Leg Impedance on Stability and Evaluation of Feature Selection and Model Training 17:01- Via Drive-Torque Sensor Feedback Efficiency in Quadrupedal Trotting Strategies for Object Category Recognition 19 17:04 Kim, Kwan Suk; Kwok, Alan; Thomas, Gray; Sentis, Bosworth, William; Kim, Sangbae; Hogan, Neville Ali, Haider; Marton, Zoltan-Csaba Luis
Augmenting Impedance Control with Structural Automatic Segmentation and Recognition of Human Compliance for Improved Contact Transition On the Energetics of Quadrupedal Bounding with and Activities from Observation Based on Semantic 17:04- Performance without Torso Compliance Reasoning 20 17:07 Kim, Dongwon; Gillespie, Brent; Johnson, Brandon Cao, Qu; Poulakakis, Ioannis Ramirez-Amaro, Karinne; Beetz, Michael; Cheng, Gordon
On the Dynamics of a Quadruped Robot Model with Fuzzy Learning Variable Admittance Control for Impedance Control: Self-Stabilizing High Speed Trot- Detection of Liquids in Cups Based on the Refraction 17:07- Human-Robot Cooperation Running and Period-Doubling Bifurcations of Light with a Depth Camera Using Triangulation 21 17:10 Dimeas, Fotios; Aspragathos, Nikos A. Lee, Jongwoo; Hyun, Dong Jin; Ahn, Jooeun; Kim, Hara, Yoshitaka; Honda, Fuhito; Tsubouchi, Takashi; Sangbae; Hogan, Neville Ohya, Akihisa
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Monday September 15
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82 Session MoA1 Grand Ballroom Monday, September 15, 2014, 09:20–10:40 Manipulation and Grasping I / Robust and Optimal Control Chair Oussama Khatib, Stanford University Co-Chair
09:20–09:40 MoA1.1 09:40–09:43 MoA1.2 Robotic manipulation in object Keynote: What is Manipulation? composition space
Matthew Mason Joni Pajarinen1, Ville Kyrki1, Carnegie Mellon University 1Aalto University • Fun with definitions • RGB-D image: uncertainty • Examples about object composition • Robo • Instead of “best” composition, • Bio plan actions using a probability • Types distribution over compositions • Manipulation graphs • For task planning use a POMDP model that takes uncertainty in object compositions, observations, and actions, into account
09:43–09:46 MoA1.3 09:46–09:49 MoA1.4 6D Proximity Servoing for Preshaping Multi-Joint Gripper and Haptic Exploration using CTPS with Differential Gear System Stefan Escaida Navarro, Martin Schonert, Takumi Tamamoto, Kazuhiro Sayama, Björn Hein and Heinz Wörn and Koichi Koganezawa Karlsruhe Institute of Technology Tokai University, Japan • Gripper equipped with 2x2 6D Preshaping • Multi-joint gripper with differential gear system using arrangement of capacitive tactile no-wire transmission. proximity sensors (CTPS) in its • It has a variable stiffness mechanism. fingers • The paper shows experiments of grasping various • Implementation of proximity Haptic Exploration shape objects as servoing which allows for well as simulation applications such as preshaping and study. haptic exploration
09:49–09:52 MoA1.5 09:52–09:55 MoA1.6 Design and Implementation of a Low-Cost Artificial Hand with Stiffness Adjuster and Lightweight Inflatable Robot Finger Koichi Koganezawa and Akira Ito Ronghuai Qi1, Tin Lun Lam1, and Yangsheng Xu2 1Smart China Research, Smart China Holdings Limited, Hong Kong Department of Mechanical Engineering 2Dept. of Mechanical and Automation Engineering, The Chinese Tokai University, Japan University of Hong Kong, Hong Kong • Underactuated with Back-drivability • A new structure of soft inflatable using the Planetary gear system. robot finger is proposed • Synergic grasping motion by • It only weighs 0.8 grams the compound four-bar linkage. • Stiffness adjusting of joints. • The cost of fabricating is pretty low • All-in-one design with five actuators • It can be easily and massively in the palm with no wire transmission. manufactured • Simple and intrinsically safe control. • It has many potential applications • It achieves six typical motions as a hand. (e.g. human-safe interactions, etc.)
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
83 Session MoA1 Grand Ballroom Monday, September 15, 2014, 09:20–10:40 Manipulation and Grasping I / Robust and Optimal Control Chair Oussama Khatib, Stanford University Co-Chair
09:55–09:58 MoA1.7 09:58–10:01 MoA1.8
Design of Hands for Aerial Manipulation: Actuator Robust Model Free Control of Robotic Number and Routing for Grasping and Perching Manipulators with Prescribed Transient and Steady State Performance Spencer B. Backus1, Lael U. Odhner1 and Aaron 1 Charalampos P. Bechlioulis, Minas V. Liarokapis and M. Dollar Kostas J. Kyriakopoulos 1 Yale University National Technical University of Athens • Grasping objects from UAV’s while in • A novel model-free control scheme that Joint Spacep flight is challenging imposes prescribed transient and steady state response for robotic manipulators in both joint • We present a grasp simulation and and Cartesian workspace. use it to analyze the impacts of hand • No information regarding the dynamic model is employed. design parameters under conditions a Cartesian Space • The control gains selection is simple and grasping UAV might encounter. decoupled from the achieved tracking performance. • Very low computational complexity makes implementation on fast embedded control platforms straightforward. 10:01–10:04 MoA1.9 10:04–10:07 MoA1.10 Dual Execution of Optimized Contact Quasi-static manipulation of a planar Interaction Trajectories elastic rod using multiple robotic grippers M. Toussaint1, N. Ratliff12, J. Bohg2, L. Righetti2, M. Mukadam, A. Borum, and T. Bretl P. Englert1, S. Schaal2 University of Illinois at Urbana-Champaign, USA 1Univ. of Stuttgart, 2Max-Plank-Inst. Tübingen • Efficient manipulation needs contact • We develop a manipulation planning interaction to reduce uncertainty algorithm for a planar elastic rod • We optimize trajectories, rewarding held by multiple robotic grippers uncertainty reduction through • Upper and lower bounds are constraint interaction established for the number of • Force controllers reproduce the grippers needed to hold the rod in a constraint interaction profile collision-free configuration in an encoded in the dual solution environment with obstacles
10:07–10:10 MoA1.11 10:10–10:13 MoA1.12 Garment Perception and its Folding Numerical Approximation for Visibility using a Dual-arm Robot Based Pursuit Evasion Game Jan Stria, Daniel Průša, Václav Hlaváč, Sourabh Bhattacharya1, Tamer Basar2, L. Wagner, V. Petrík, P. Krsek, V. Smutný and Maurizio Falcone3 1Iowa State University Czech Technical University in Prague 2University of Illinois 3LaSapienza, Rome • Complete pipeline for fully image automated folding of various • Vision-based pursuit-evasion game
garments (shirts, pants, towels) in the presence of obstacles. any text in the • Existence of a value function. • Based on fitting garment contour imae should • Numerical computation of saddle- (extracted from a single image) to be the same point strategies. polygonal model of clothing size as main (partially learned from data) text • Convergence of the numerical • Achieved state of the art results schemes.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
84 Session MoA1 Grand Ballroom Monday, September 15, 2014, 09:20–10:40 Manipulation and Grasping I / Robust and Optimal Control Chair Oussama Khatib, Stanford University Co-Chair
10:13–10:16 MoA1.13 10:16–10:19 MoA1.14 Optimized Visibility Motion Planning for Target Tracking and Localization Chanyoung Jun, Subhrajit Bhattacharya, Robert Ghrist Hongchuan Wei1, Wenjie Lu1, Pingping Zhu1 University of Pennsylvania Guoquan Huang2, John Leonard3, Silvia Ferrari1 • Design control input for pursuer Agents represented 1Duke University 2Delaware University 3MIT with knowledge of pursuer’s by normal probability distribution, , and evader’s distributions instead • Target tracking-robot localization: estimated distribution, , only. of points. Maximize probability of detection • Show bound of the distance
• Control law for sector shaped • Show bound of “distance” sensor under EKF framework • Hence show that distance
• Low target loss rate i.e., pursuer “catches up” with the evader. 10:19–10:22 MoA1.15 10:22–10:25 MoA1.16 Optimal control for robot-hand manipulation Camera Control For Learning Nonlinear using dynamic visual servoing Target Dynamics via Bayesian Carlos A. Jara, Jorge Pomares, Nonparametric Dirichlet-Process Francisco A. Candelas and Fernando Torres Gaussian-ProcessH. Wei1, W. Lu1, P. Zhu(DP-GP)1, S. Ferrari Models1, University of Alicante R. H. Klein2, S. Omidshafiei2, J. P. How2 1 2 • Framework to define direct visual Duke MIT image servoing control laws for robot • Described complex target behavior by hands: Sensor any text in the DP-GP mixture model image should • Expected information value function • Robot-hand guidance using visual be the same to calculate gain by a measurement servoing and maintenance of size as main • Particle filter representing target
interaction forces (control law with text position distribution to reduce torques optimization). computational complexity
10:25–10:28 MoA1.17 10:28–10:31 MoA1.18 Reactive Phase and Task Space Remote Operated Vehicle Tether Disturbances Analysis and Target Tracking Control Adaptation for Robust Motion Execution
Huang Hai, Sheng Ming-wei, Li Yue-ming, Wan Lei, Pang Yong-jie Peter Englert National Key Laboratory of Science and Technology of Underwater Marc Toussaint Vehicle, Harbin Engineering University, China U Stuttgart Z The tether effects have been analyzed through a • Adapting motion plans partial differential equation during execution to new with waves and current situations disturbances • Parameterization with • A backstepping sliding phase variable instead mode controller has been of fixed timing established. • Goal: Bridge gap • Realize a spiral line and pipeline tracking between motion planning and motion execution
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
85 Session MoA1 Grand Ballroom Monday, September 15, 2014, 09:20–10:40 Manipulation and Grasping I / Robust and Optimal Control Chair Oussama Khatib, Stanford University Co-Chair
10:31–10:34 MoA1.19 10:34–10:37 MoA1.20 Synchronization and Consensus of a Robust Fixed Point Traf. Based Design Robot Network on a Dynamic Platform for MRAC of a Modified TORA System Kim-Doang Nguyen, Harry Dankowicz, J.K. Tar, T.A. Várkonyi, University of Illinois at Urbana-Champaign L. Kovács, I.J. Rudas, T. Haidegger • A fast adaptation scheme for ABC for iRobotics, Óbuda University, Hungary cooperative control, which does not • Iterative control strategy require the system model. • Simple design methodology Model • The behavior of the controlled through rough model estimation network matches closely that of a • Limited to 3 free parameters RFPT nonadaptive reference system. • Avoiding complex calculation Delay • The cooperation control objectives • Control is trustworthy, despite Delay are achieved despite the platform’s local stability is only guaranteed Model unmodelled dynamics. • Error is halved, if employed System
10:37–10:40 MoA1.21 Receding Horizon Optimization of Robot Motions generated by Hierarchical Movement Primitives Manuel Mühlig1, Akinobu Hayashi1, Michael Gienger1, Soshi Iba2 and Takahide Yoshiike2
1Honda Research Institute Europe 2Honda R&D Co. • Motion generation frameworkk that combines MPs with receding horizon optimizationn • Continuous optimization of robot motion, with rapid reaction to disturbances • Real robot experiment with human interaction
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
86 Session MoA2 State Ballroom Monday, September 15, 2014, 09:20–10:40 Localization and Mapping I / Motion and Path Planning I Chair Giuseppe Oriolo, Sapienza University of Rome Co-Chair
09:20–09:40 MoA2.1 09:40–09:43 MoA2.2 Mining Visual Phrases for Long-Term Keynote: Dense, Object-based 3D SLAM Visual SLAM John Leonard Kanji Tanaka1, Yuuto Chokushi1, Massachusetts Institute of Technology Masatoshi Ando1 1University of Fukui • This talk will review recent • Single-view place recognition for progress in dense 3D SLAM image long-term visual SLAM algorithm development query db CPD • Key tool: Kintinuous (Whelan et • Visual phrases explain an input any text in the al., ICRA 2013/IROS 2014) query/DB scene image image should • Extension to detect objects from • Mining visual experience to find be the same effective visual phrases size as main changes in the environment Deformation-based • A compact discriminative bounding text • Future: Object-oriented and loop closure (Whelan) Semantic 3D SLAM box –based scene descriptor
09:43–09:46 MoA2.3 09:46–09:49 MoA2.4 Network localization from relative Towards Indoor Localization using Visible Light Communication for Consumer Electronic Devices bearing measurements Ming Liu, Kejie Qiu, Fengyu Che, Shaohua Li, Babar Hussain, Liang Wu, C. Patrick Yue Ryan Kennedy and Camillo J. Taylor The Hong Kong University of Science and Technology {eelium, kqiuaa, fyche, slias, bhussain, eewuliang, eepatrick}@ust.hk University of Pennsylvania
A dedicated driver for LED beacons with VLC capability, Setup: A network where each node which at the same time could can only measure relative angles also support indoor illumination. use standard microphone to Problem: What is the layout of the decode the analog signal entire network? captured by the photonic sensor a novel algorithm to decode the We present a novel optimization problem and two light pattern using rolling-shutter cameras algorithms for solving it. We also show how the model the luminance distribution method can be extended to 3D, and discuss its relation for a VLC bulb in 3D space using Gaussian Process to the “structure-from-motion” problem in computer vision.
09:49–09:52 MoA2.5 09:52–09:55 MoA2.6 2D-3D Camera Fusion for Visual Position Control of a Robot End-Effector Odometry in Outdoor Environments Based on SAR Wireless Localization Danda Pani Paudel1, Cédric Demonceaux1, Albert Marschall1, Thorsten Voigt2, Adlane Habed2, Pascal Vasseur3, In So Kweon4 Gang Li1, Ulrich Konigorski2 and Martin Vossiek1 1Bourgogne U 2Strasbourg U 3Rouen U 4KAIST 1FAU Erlangen-Nürnberg 2TU Darmstadt • We propose an optimization framework for robot • Innovative position control concept localization using both 2D and 3D information. of a lightweight non-rigid robot with • It uses minimal number of points for initial estimation, wireless positioning approach constrained optimization • Robust and ultra-precise synthetic based motion refinement. aperture radar (SAR) locating 3-axis linear • Weights derived from algorithm for severe multipath unit with light- environments scale-histogram take care weight arm and • Accurate system error compensation transponder of the scene occlusions.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
87 Session MoA2 State Ballroom Monday, September 15, 2014, 09:20–10:40 Localization and Mapping I / Motion and Path Planning I Chair Giuseppe Oriolo, Sapienza University of Rome Co-Chair
09:55–09:58 MoA2.7 09:58–10:01 MoA2.8 Static forces weighted Jacobian motion Visual Localization within LIDAR Maps models for improved Odometry for Automated Urban Driving J. Hidalgo-Carrio1, A. Babu1, F. Kirchner1,2 Ryan W. Wolcott and Ryan M. Eustice 1DFKI - Robotics Innovation Center 2University of University of Michigan Bremen • Full image registration in The prediction step of a localization 3D prior map augmented framework is commonly performed with surface reflectivities using odometry techniques. A • Benchmarked against Jacobian motion model-based state-of-the-art LIDAR approach for real-time inertial-aided methods, yielding similar odometry is presented. The algorithm relates normal error rates forces with the probability of a contact-point to slip. Field • Leveraged OpenGL and testing and in-depth error analysis are discussed, CUDA for 10 Hz pose resulting in a more accurate localization. updates and real-time usee
10:01–10:04 MoA2.9 10:04–10:07 MoA2.10 Decentralized Cooperative Trajectory Vision Based Robot Localization by Ground to Estimation for AUVs Satellite Matching in GPS-denied Situations
Liam Paull1, Mae Seto2 and John J. Leonard1 Anirudh Viswanathan, Berna rdo Pires, Daniel Huber 1MIT 2Defence R&D Canada Robotics Institute, Carnegie Mellon University
• Full multi-AUV cooperative • Matching ground level images to trajectory estimation satellite or aerial vehicle images. • Feasible data packet sizes for • Challenging due to the change in acoustic communications Acoustic coms perspective between the ground with 3 AUVs in • Estimates are consistent and exact and aerial imagery. TDMA scheme • Explore image-feature space for the matching problem. Air-Ground Localization
10:07–10:10 MoA2.11 10:10–10:13 MoA2.12
Hybridization of Monte Carlo and Set- A Novel RRT Extend Function for Efficient and membership Methods for the Global Smooth Mobile Robot Motion Planning
Localization of Underwater Robot Luigi Palmieri, Kai O. Arras, Renata Neuland1, Jeremy Nicola2, Renan Maffei1, Social Robotics Lab, University of Freiburg Luc Jaulin2, Edson Prestes1 and Mariana Kolberg1 1UFRGS 2ENSTA Bretagne •A novel extender for sampling-based motion planners that solves the 2-point BVP • We modify a discontinous control law for wheeled • A new approach that combines robots and prove all relevant stability properties probabilistic and interval strategies to • Experiments show that the approach outperfoms solve the global localization problem. motion primitives and a spline-based extender: PF • For RRT, it finds smoother paths in less time • Contractors reduce the uncertainty with smaller trees. For RRT*, it finds shorter about the robot localization. paths with smaller trees while being on par in planning time and smoothness. • Particle filter refines the localization • When given more planning time for RRT*, our using the interval results. Hybrid approach finds the lowest cost solution
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
88 Session MoA2 State Ballroom Monday, September 15, 2014, 09:20–10:40 Localization and Mapping I / Motion and Path Planning I Chair Giuseppe Oriolo, Sapienza University of Rome Co-Chair
10:13–10:16 MoA2.13 10:16–10:19 MoA2.14 Guiding Sampling-Based Tree Search for Planning agile motions for quadrotors in Motion Planning with Dynamics via constrained environments Probabilistic Roadmap Abstractions Alexandre Boeuf1, Juan Cortés1, Duong Le1 and Erion Plaku1 Rachid Alami1 and Thierry Siméon1 1Catholic University of America 1LAAS-CNRS and Univ de Toulouse, France • Roadmap constructed over • Computationally efficient local low-dimensional configuration trajectory planner for quadrotors space used in two global motion • Guides expansion of motion planning approaches: tree in the full state space 1. As part of an optimization • Simulation experiments with method within a decoupled nonlinear dynamics and approach. physics-based simulations 2. As a steering method inside a sampling-based motion planner.
10:19–10:22 MoA2.15 10:22–10:25 MoA2.16 Optimal Navigation Functions for A Lattice-Based Approach to Multi-Robot Nonlinear Stochastic Systems Motion Planning for Non-Holonomic V. Marcello Cirillo1, Tansel Uras2 and Sven Koenig2 Matanya B Horowitz, Joel W Burdick, 1Örebro University California Institute of Technology 2University of Southern California • Connection between navigation • New framework for multi-robot image functions and Hamilton Jacobi motion planning under non-
Bellman equation holonomic constraints any text in the • Generalizes existing results in • Kinematically feasible motions image should literature guaranteed to be executable be the same • New methods to incorporate • New approach tested in simulation size as main stochasticity, nonlinear dynamics Optimal Nav. and as part of a complete fleet text Function management system
10:25–10:28 MoA2.17 10:28–10:31 MoA2.18 Multi-cost Robotic Motion Planning Under Constrained Path Optimization with Uncertainty Bezier Curve Primitives Richard Simpson1, James Revell2, Ji-Wung Choi1 and Kalevi Huhtala1 Anders Johansson1 and Arthur Richards1 1Tampere University of Technology, Finland 1University of Bristol 2BAE Systems ATC • Motion planning with multiple costs • Bezier curve parametric path to overcome mission constraints efficiently solves the constrained and position uncertainty. path optimization problem. • e.g. distance travelled, position • Path regularization merging uncertainty, fuel remaining consecutive segments leads to fast • Uses a graph of waypoints, best- computation. first graph search, Pareto front, • Cusp points are adjustable to refine EKF, LQR and non-linear motion the planned path. models.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
89 Session MoA2 State Ballroom Monday, September 15, 2014, 09:20–10:40 Localization and Mapping I / Motion and Path Planning I Chair Giuseppe Oriolo, Sapienza University of Rome Co-Chair
10:31–10:34 MoA2.19 10:34–10:37 MoA2.20 Distance Metric Approximation for State- State Lattice with Controllers: Space RRTs using Supervised Learning Augmenting Lattice-Based Path Planning 1 1 1 with Controller-Based Motion Primitives M. Bharatheesha , W. Caarls , W.J. Wolfslag and Jonathan Butzke, Krishna Sapkota, Kush Prasad, Brian MacAllister, Max Likhachev M. Wisse1 1Delft University of Technology, The Netherlands Allows formal method Controller- of augmenting search graph with Based • RRT for planning in state-space controller-based GPS Denied Region Motion motion primitives Primitive • Distance = optimal cost Z Time intensive Shifts between • Cost approximation via Learning controllers in response to Z 1000x quicker Metric Motion perceptual triggers Primitive
Carnegie Mellon University – Robotics Institute
10:37–10:40 MoA2.21 Sponsor Talk: Motion Planning for Collaborative Robots Jennifer Barry Rethink Robotics
• Trajectory Requirements • Smooth, efficient, predictable • Safe • Easy to train • Constraints • Non-expert users • No 3D sensor
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
90 Session MoA3 Red Lacquer Room Monday, September 15, 2014, 09:20–10:40 Bioinspired Robots I / Multi-Robot Coordination Chair Maria Gini, University of Minnesota Co-Chair
09:20–09:40 MoA3.1 09:40–09:43 MoA3.2 Keynote: Bio-inspired Multi-modal Flying Modeling of underwater snake robots Robots moving in a vertical plane in 3D
Dario Floreano E. Kelasidi, K. Y. Pettersen and J. T. Gravdahl EPFL Dept. of Engineering Cybernetics, NTNU I will describe flying robots that are capable of withstanding and • A model of the kinematics and the exploiting collisions for better dynamics of underwater snake navigation in cluttered robot is presented environments, and that can adapt • The combination of hydrodynamic their morphology to transition and hydrostatic forces and torques between aerial and ground are considered locomotion. The technologies are • A closed form solution is proposed inspired by biological principles of avoiding the numerical evaluation multi-modal navigation. of drag effects
09:43–09:46 MoA3.3 09:46–09:49 MoA3.4 Actuation strategies for underactuated New Rolling and Crawling Gaits for anthropomorphic hands Snake-like Robots M.Tavakoli1, B. Enes1, L. Marques1 and A.T. de Almeida1 1 Richard Primerano and Stephen Wolfe Institute of Systems and Robotics, University of Coimbra, Portugal Drexel University Electrical and Computer • Proposal of 16 actuation strategies compared in two Engineering Department Philadelphia, PA 19104 analysis: –Grasp Diversity, out of a list of 33 grasp • Each segment incorporates –Grasp Funcionality, compared to the top10 grasps two translational and one with the highest usage frequency rotational degree, giving rise to several new gaits. • These degrees of freedom give rise to several new gaits
09:49–09:52 MoA3.5 09:52–09:55 MoA3.6 Mamba - A Waterproof Snake Robot iSplash-MICRO: A 50mm Robotic Fish Generating the Maximum Velocity of Real Fish with Tactile Sensing Richard James Clapham and Huosheng Hu Pål Liljebäck1,2, Øyvind Stavdahl1, School of Computer Science and Electronic Engineering, 1 1 University of Essex, United Kingdom Kristin Y. Pettersen and Jan Tommy Gravdahl 1NTNU 2SINTEF ICT
• The small fish with a length of 50mm has generated an • We present a modular and equivalent average waterproof snake robot. maximum velocity to real fish, measured in body • A force/torque sensor in each joint lengths/ second (BL/s). module enables contact forces
• Achieving a consistent free along the body to be measured. swimming speed of 10.4BL/s (0.52m/s) at 19Hz. • Applications: Adaptive locomotion in cluttered environments and underwater locomotion.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
91 Session MoA3 Red Lacquer Room Monday, September 15, 2014, 09:20–10:40 Bioinspired Robots I / Multi-Robot Coordination Chair Maria Gini, University of Minnesota Co-Chair
09:55–09:58 MoA3.7 09:58–10:01 MoA3.8
Multi-arm Robotic Swimming ReBiS with Octopus-inspired Compliant Web – Reconfigurable Bipedal Snake Robot M. Sfakiotakis, A. Kazakidi, A. Chatzidaki, T. Evdaimon, D.P. Tsakiris Institute of Computer Science – FORTH, Heraklion, Greece Rohan Thakker, Ajinkya Kamat, Sachin Bharambe, S. Chiddarwar, and K. Bhurchandi • The propulsive capabilities of an 8-arm robotic swimmer with compliant arms Visvesvaraya National Institute of and web, inspired by the octopus arm- Technology, Nagpur, India swimming behavior, are investigated.
• Different arm sculling patterns produce (a) (b) different forward swimming gaits. • Novel Modular • A dynamical model, which considers arm Reconfigurable Robot and web compliance, was used to study Design the effect of the sculling parameters (c) (d) on forward swimming propulsion. • Reconfiguration without • An 8-arm compliant robotic swimmer rearrangement of modules was used to generate the swimming gaits, and evaluate this novel mode of propulsion. Speeds of 0.5 body lengths per second and propulsive forces • Transforming, Walking of up to 10.5 N were achieved, with a cost of transport as low as 0.62. and Snake gaits.
10:01–10:04 MoA3.9 10:04–10:07 MoA3.10 Role of Compliant Leg in the Flea- Optimal Force Mapping for Obstacle- Inspired Jumping Robot Aided Locomotion in 2D Snake Robots Gwang-Pil Jung1, Je-Sung Koh1, Christian Holden1, Øyvind Stavdahl1, Ji-Suk Kim1, Sun-Pil Jung and Kyu-Jin Cho1 Jan Tommy Gravdahl1 1Seoul National University, Biorobotics Lab. 1Norwegian Univ. of Science And Technology • In obstacle-aided locomotion, a snake pushes against • Jumping robot’s legs experience the environment to achieve propulsion. extremely large acceleration during take-off, which induces bending in • We optimally determine the motor inputs giving desired the jumping leg. obstacle forces achieving a desired path for the snake. • We study how the bending of the leg • We present an explicit algebraic relationship between affects the jumping performance by input and obstacle forces. switching five legs having different • We formulate an optimization problem that minimizes stiffness. energy consumption while achieving the control goal.
10:07–10:10 MoA3.11 10:10–10:13 MoA3.12 Empirical Investigation of Closed-Loop Reactive Switching Protocols for Control of Extensible Continuum Multi-Robot High-Level Tasks Manipulators Vasumathi Raman Apoorva Kapadia, Katelyn Fry, and Ian Walker California Institute of Technology Clemson University • First closed-loop • Correct-by-construction controllers experimental results for for teams of interchangeable robots extensible continuum in a nondeterministic environment manipulators. • Team modeled as a switched • 3 controllers analyzed: 2 C- system, allowing dynamic goal space controllers (PID and reassignment sliding mode) and 1 task- /0123 4560 789150 • Resulting controllers satisfy space controller reactive specifications in linear temporal logic
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
92 Session MoA3 Red Lacquer Room Monday, September 15, 2014, 09:20–10:40 Bioinspired Robots I / Multi-Robot Coordination Chair Maria Gini, University of Minnesota Co-Chair
10:13–10:16 MoA3.13 10:16–10:19 MoA3.14
022 '4 2$ )4 2$)" 20' ( ) $43 $11'$4$0) 40 Cooperative Control of a Heterogeneous Multi- )!02(4$6 4# '))$)" !02 23$34 )4 0)$402$)" 3&3 Robot System based on Relative Localization 1 1 1 1 2 5@ @@9 #7" 2@9 ) )$ ' 53@@ M.Cognetti , G.Oriolo , P.Peliti , L.Rosa , P.Stegagno @ 0340) )$6 23$48 @@ 33#53 443 )34$454 0! #)0'0"8 1Sapienza University of Rome, Italy 2MPI for Biological Cybernetics, Germany • Multi-robot system composed of an UAV % carrying a camera and several UGVs • Primary task: keep UGVs in camera % FOV. Additional tasks: formation control, navigation, obstacle avoidance • Primary task allows relative visual % localization and identification of UGVs • Different cooperation levels
10:19–10:22 MoA3.15 10:22–10:25 MoA3.16
Three-Dimensional Multirobot Finding Optimal Routes for Multi- Formation Control for Target Enclosing Robot Patrolling in Generic Graphs Miguel Aranda1, Gonzalo López-Nicolás1, David Portugal and Rui P. Rocha 1 2 Institute of Systems and Robotics, University of Coimbra, Portugal Carlos Sagüés and Michael M. Zavlanos Charles Pippin and Henrik Christensen 1Universidad de Zaragoza 2Duke University Georgia Tech Research Institute, Georgia Institute of Technology, USA
• Relative position measurements • Trade-off in performance, travel cost and are used, the method relies on a coordination of multi-robot patrolling strategies. locally computed rotation matrix • Graph topology and team size determine the best choice for a patrolling strategy. • Any 3D enclosing pattern can be • Cyclic strategies are superior when small achieved, with arbitrary rotation teams are used, but have greater travel cost. • Partitioning is suitable for larger teams and • A global coordinate frame for the unbalanced graphs, yielding small travel cost. robots is not required • Theoretical analysis and results across • Exponentially stable controller Octahedron-shaped multiple environments. enclosing pattern
10:25–10:28 MoA3.17 10:28–10:31 MoA3.18 Fleet Size of Multi-Robot Systems for Stable Formation of Groups of Robots Exploration of Structured Environments Via Synchronization Flavio Cabrera-Mora1 and Jizhong Xiao2, L. Valbuena1, P. Cruz2, R. Figueroa2, 1Vaughn College of Aeronautics and Technology F. Sorrentino1, and R. Fierro2 2The City College of New York 1ME Dept., 2ECE Dept., University of New Mexico • Fleet size of a multi-robot system is • Decentralized formation control of an important parameter that two different groups of robots. determines cost and execution time • Stability analysis of the desired of any given task. intra-group and inter-group phase • Analyze how changing the fleet size synchronization. affects the exploration time. • Experimentally verified using a • Analyze how to bound the fleet size group of quadrotors and a group of using the size of the environment. ground nonholonomic robots.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
93 Session MoA3 Red Lacquer Room Monday, September 15, 2014, 09:20–10:40 Bioinspired Robots I / Multi-Robot Coordination Chair Maria Gini, University of Minnesota Co-Chair
10:31–10:34 MoA3.19 10:34–10:37 MoA3.20 RoboCup Drop-In Player Challenges: Aligning Coordinate Frames in Multi-Robot Experiments in Ad Hoc Teamwork Systems with Relative Sensing Information
Patrick MacAlpine, Katie Genter, Sasanka Nagavalli, Andrew Lybarger, Lingzhi Luo, Nilanjan Chakraborty, Katia Sycara
Samuel Barrett and Peter Stone Robotics Institute, Carnegie Mellon University University of Texas at Austin • Problem: Establish common reference frame for a multi-robot system with each robot equipped with range-limited sensors that measure only positions of other robots within its field of view • Centralized and asynchronous distributed algorithms that make no assumptions about sensor noise model • Provably optimal if (1) measurements are noiseless or • Series of pick-up robot soccer games held across three (2) communication graph has a tree structure and leagues at RoboCup robot soccer competition measurements are noisy • Simulation results show our method outperforms • Robots programmed by different labs are put on teams conventional techniques (e.g. Gauss-Newton) and play soccer together with no pre-coordination • Preliminary testing on multi-robot system (6 TurtleBots) • Ad hoc teamwork challenge
10:37–10:40 MoA3.21 A Mathematical Programming Approach to Collaborative Missions with Heterogeneous Teams E. F. Flushing, L. M. Gambardella, G.A. Di Caro Dalle Molle Institute for Artificial Intelligence (IDSIA), Lugano, Switzerland • Joint mission planning as a Mixed- Integer Linear Program.
• Modeling realistic aspects from real-world scenarios: deviations in plan execution, agents' spatio- temporal relations, incremental and collaborative completion of tasks. • Validation in search and rescue
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
94 Session MoB1 Grand Ballroom Monday, September 15, 2014, 11:10–12:30 Calibration and Identification / Kinematics and Mechanism Design I Chair Anthony A. Maciejewski, Colorado State University Co-Chair
11:10–11:30 MoB1.1 11:30–11:33 MoB1.2 Keynote: Innovative Mechanical Systems Locally-weighted Homographies for to Address Current Robotics Challenges Calibration of Imaging Systems
Clément Gosselin Pradeep Ranganathan, Edwin Olson Université Laval, Québec, Canada University of Michigan - Ann Arbor • Robotics challenges: advanced manipulation, variety of working • Novel non-parametric non-linear conditions, locomotion, homography technique collaboration with humans • Independent estimate of lens • The design of novel robotic distortion from a single image mechanical systems is a key • Distortion estimate improves component of future progress stability of classic camera calibration • Several illustrative examples • Allows rectification of arbitrary provided in this talk sources of image distortion
11:33–11:36 MoB1.3 11:36–11:39 MoB1.4
Towards Simultaneous Coordinate Calibrations for Force calibration of KUKA LWR-like robots including Cooperative Multiple Robots embedded joint torque sensors and robot structure Jiaole Wang1,2, Liao Wu2, Max Meng1 and Hongliang Ren*2 1 The Chinese University of Hong Kong 1 1,2 2National University of Singapore Maxime Gautier and Anthony Jubien *Corresponding author: [email protected] 1University of Nantes, IRCCyN, France 2ONERA, The French Aerospace Lab, Toulouse, France
A fundamental calibration problem for multi-robot cooperation is modeled and formulated as an AXB=YCZ problem. • Calibration (gain,offset) of the Kuka LightWeightRobot torque
An efficient iterative solution is presented to simultaneously solve X, Y, Z. sensors mounted on the link side of the actuated joints
A comparison between the simultaneous method and the non-simultaneous • Usual: special test for each sensor separately, before mounting ones are carried out to • New: simultaneous in situ identification of the mounted torque sensors + dynamic parameters of the links show the efficiency and • trajectories without load + trajectories with a known weighed robustness of the payload, collecting internal control joint torque sensor and Kuka LWR4+ proposed simultaneous position data With payload method. • Inverse Dynamic Identification Model + total least squares 4.6136(kg) • Experimental validation on the Kuka LWR4+ robot
11:39–11:42 MoB1.5 11:42–11:45 MoB1.6 Calibrating a Pair of Inertial Sensors at Extrinsic calibration of a set of range Opposite Ends of an Imperfect cameras in 5 seconds without pattern Kinematic Chain Eduardo Fernández-Moral1, Javier González1, Patrick Rives2 and Vicente Arévalo1 Oliver Birbach and Berthold Bäuml 1 2 Institute of Robotics and Mechatronics, German Aerospace Center (DLR) Universidad de Málaga INRIA Sophia-Antipolis • Easy and quick calibration • Agile Justin's kinematic state of torso not • No pattern required known to required precision. • A single observation can be • Groundwork for obtaining its kinematic sufficient for calibration state from a pair of IMUs. • Calibration routine and model to obtain • No overlapping required. required pose of IMUs (HI & PI) mounted • The covariance of the at opposite ends (H & P) of the torso calibration is provided. kinematic chain.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
95 Session MoB1 Grand Ballroom Monday, September 15, 2014, 11:10–12:30 Calibration and Identification / Kinematics and Mechanism Design I Chair Anthony A. Maciejewski, Colorado State University Co-Chair
11:45–11:48 MoB1.7 11:48–11:51 MoB1.8 Extrinsic Calibration of Non-overlapping Magnetometer Bias Calibration Camera-Laser System using Struct. Env. Based on Relative Angular Position Yunsu Bok1, Dong-Geol Choi1, Giancarlo Troni and Ryan M. Eustice Pascal Vasseur2 and In So Kweon1 University of Michigan, USA 1KAIST, Korea 2Univ. de Rouen, France • Relative angular position (from • Two methods of computing relative image registration or laser scan- pose between a camera and a 2D matching) used to estimate the laser sensor ‘without overlap’ magnetometer bias. • No ‘bridging’ sensor • Two methods are proposed based • Normal vector of a plane or on batch linear least squares and a intersecting line of two planes real-time discrete Kalman filter. Vision-based parallel to any axis of world • Simulation and experimental magnetometer calibration coordinate system evaluation under different conditions.
11:51–11:54 MoB1.9 11:54–11:57 MoB1.10
Automatic Calibration of RGBD Spatio-Temporal Laser to Visual/Inertial Calibration and Thermal Cameras with Applications to Hand-Held, Large Scale Scanning Joern Rehder1,2, Paul Beardsley2, Jake T. Lussier1, Sebastian Thrun1 Roland Siegwart1 and Paul Furgale1 1Stanford University 1ETH Zurich 2Disney Research Zurich • Automatic method for synchronization and calibration of • Introducing a novel approach for RGBD & thermal cameras in arbitrary environments. laser range finder to camera/IMU • Aligns edges in thermal calibration and depth images. • Capable of estimating the rigid transformation along with the time • No checkerboard needed. delay between sensors • Results in high-quality • Demonstrated effectiveness in RGBDT data. hand-held scanning of large scale structures
11:57–12:00 MoB1.11 12:00–12:03 MoB1.12 A Catadioptric Extension A Dual-Motor Robot Joint Mechanism for RGB-D Cameras With Epicyclic Gear Train Felix Endres1, Christoph Sprunk1, Vincent Babin1, Clément Gosselin1 Rainer Kümmerle2 and Wolfram Burgard1 and Jean-François Allan2 1University of Freiburg 2KUKA Laboratories 1Université Laval 2Hydro-Québec • RGB-D cameras have a • Improving performances of field image small field of view robots with the use of a two DOF Mirrors epicyclic gear train with dual input • Planar mirrors split the any text in the single output. view into front and back image should • Auto-calibration from • Preventing backdrivability with the be the same planar motion use of a worm-set. size as main Rear FrontFront • Improves SLAM results RGB-D • Prototype and simulation data text View View presented as proof of concept. compared to regular sensor Camera Proposed Mechanism
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
96 Session MoB1 Grand Ballroom Monday, September 15, 2014, 11:10–12:30 Calibration and Identification / Kinematics and Mechanism Design I Chair Anthony A. Maciejewski, Colorado State University Co-Chair
12:03–12:06 MoB1.13 12:06–12:09 MoB1.14 Kinematic Design and Analysis for a An alternative approach to robot safety Macaque Upper-Limb Exoskeleton K. Haninger1, J. Lu1, W. Chen1 and M. Tomizuka1 Alberto Parmiggiani1, Marco Randazzo1, Lorenzo 1Department of Mechanical Engineering, Natale1 and Giorgio Metta1 University of California, Berkeley 1iCub Facility, Fondazione Istituto Italiano di Tecnologia • Algorithm presented to infer joint center • We addressed the issue of location from motion capture data robot safety by proposing a • Motion capture data of macaque upper- novel design of actuators with limb is used to validate a joint model an overload protection. • Validated joint model used to motivate an • We constructed a prototype ergonomic exoskeleton implementing this approach; quantitative evaluations • Bounds on required joint speed found demonstrate the effectiveness from desired end effector speeds of the approach
12:09–12:12 MoB1.15 12:12–12:15 MoB1.16 On the Performance Evaluation and Analysis of General Robots with Mixed DoFs S. SHAYYA1,2, S. KRUT2, O. COMPANY2, C. BARADAT1, and F. PIERROT2 H. Azimian1, T. Looi1 and J. Drake1 1 2 Tecnalia France LIRMM-Université Montpellier 2- 1CIGITI, Hospital for Sick Children, Toronto France • Clarifies the problematic regarding performance evaluation of mixed dofs robots • A closed-form solution for real-time • Suggests a relevant approach based on proper separation of translation inverse kinematics under inequality and rotation constraints is proposed. • The approach suits all robots regardless of their type (serial, parallel or • The solution is based on using hybrid...) and whether actuatedly or kinematically redundant • It focuses on kinetostatic analysis based on isotropic performances in slack variables and is efficient and velocity and force stable. • Also suggests relevant precision related measures (operational resolution) • Efficacy of the solution is shown for concentric-tube • Provides a case study on DUAL V (3 dof , 2T-1R) actuatedly redundant kinematic control of a concentric- robot to clarify the approach robot prototype tube manipulator. 12:15–12:18 MoB1.17 12:18–12:21 MoB1.18
Novel 3-DOF Ankle Mechanism for Robust Solution of Prioritized Inverse Kinematics Lower-Limb Exoskeleton Based On Hestenes-Powell Multiplier Method Man Bok Hong1, Young June Shin1, Tomomichi Sugihara and Ji-Hyeun Wang1 Osaka University, Japan 1Agency for Defense Development • A novel solution to prioritized IK based on Hestenes- Powell’s multiplier method • Fully passive-type 3-DOF ankle • Pros1: Light implementation and computation cost module of a lower-limb … weighted IK + error accumulation of high-priority exoskeleton designed for rough- constraint + estimation of Lagrange’s multiplier terrain tasks is presented with • Pros2: Solvability-unconcerned … robust as long as kinematic analyses. original weighted IK solver is robust • Cons: Lagrange’s multiplier linearly converges, while joint displacement superlinearly converges … slow
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
97 Session MoB1 Grand Ballroom Monday, September 15, 2014, 11:10–12:30 Calibration and Identification / Kinematics and Mechanism Design I Chair Anthony A. Maciejewski, Colorado State University Co-Chair
12:21–12:24 MoB1.19 12:24–12:27 MoB1.20
Analytical Inverse Kinematic Solution for Modularized 7-DoF A Flexible and Robust Robotic Arm Redundant Manipulators with Offsets at Shoulder and Wrist Design and Skill Learning by Using RNN 1 1 Ren C. Luo, Tsung-Wei Lin, Yun-Hsuan Tsai Boon Hwa Tan , Huajin Tang , 1 2 1 International Center of Excellence in Intelligent Robotics and Automation Rui Yan and Jun Tani Institute for Infocomm Research, National Taiwan University, Taiwan (R.O.C) Research, Singapore 2KAIST,Korea • An analytical inverse kinematic solution is • Flexible robotic arm design derived for a 7-DoF redundant manipulator mimicked from the kinematic with offsets at shoulder and wrist redundancy of human arm. • Two sets of equations are derived with different joints seen as redundancy, while • Human-guided motion teaching and method to select proper joint as redundant behavior learning via S-CTRNN. is also proposed. • Motion generalization through • Video demonstration for the developed grasping an object from an arbitrary experimental modularized 7-DoF position. NECO-III redundant manipulator is presented.
12:27–12:30 MoB1.21 Sponsor Talk: The da Vinci Xi Surgical System Simon DiMaio Intuitive Surgical
The da Vinci Xi Surgical System enables surgeons to perform delicate and complex operations minimally-invasively, with increased vision, precision, dexterity and control. State-of-the-art robotic technology allows the surgeon䇻s hand movements to be scaled, filtered and translatedd into precise movements of the instruments working inside the patient䇻s body.
The end result: a breakthrough in surgical capabilities.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
98 Session MoB2 State Ballroom Monday, September 15, 2014, 11:10–12:30 Soft-Bodied Robotics / Robot Learning I Chair Jamie Paik, Ecole Polytechnique Federale de Lausanne Co-Chair
11:10–11:30 MoB2.1 11:30–11:33 MoB2.2 A new coefficient-adaptive orthonormal basis function model Keynote: Soft Robotics structure for identifying a class of pneumatic actuators X. Wang1, T. Geng1, Y. Elsayed1 Cecilia Laschi T. Ranzani2 C. Saaj1 C. Lekakou1 The BioRobotics Institute, Scuola Superiore Sant’Anna, 1University of Surrey, Pisa, Italy 2Sant’Anna School of Advanced Studies
• Soft materials and -1 -1 z 1 z components in robotics ... - + + ... + + • From biological Switching ... inspiration to soft robot The DIO-PWL-OBF n prototypes model structure • A direction-dependent multisegement piecewise-linear • Applications of soft identification method is proposed. robotics, from the • A Difference-Input-Output PieceWise-Linear biomedical field to Orthonormal Basis Function (DIO-PWL-OBF) model underwater tasks structure is developed.
11:33–11:36 MoB2.3 11:36–11:39 MoB2.4
Design of Paper Mechatronics Development of A Meal Assistive Exoskeleton made - Towards a Fully Printed Robot - of Soft Materials for polymyositis patients Hiroki Shigemune1, Shingo Maeda2 , I. Koo1, C. Yun1, M. Costa, J. Scognamiglio, Yusuke Hara3 and Shuji Hashimoto 1 T. Yangali1, D. Park1 and Kyu-Jin Cho1 1Waseda University 1Seoul National University 2Shibaura Institute of Technology 3AIST • The fabrication of printed 0 s 28 s • Soft wearable self-folding paper robot exoskeleton • Self-folding of paper printed • Target task is meal by a commercial ink jet assistance 66 s 87 s printer • Made of Soft materials • Driven by electro thermal (fabric, wire, vinyl and actuator printed on the paper flexible plate) • Rapid and low-cost prototyping 2 cm
11:39–11:42 MoB2.5 11:42–11:45 MoB2.6 Spatial Parallel Soft Robotic Whole Arm Planning for a Soft and Highly Architectures Compliant 2D Robotic Manipulator
1 1 Charles Kim and Jordan Rivera , Andrew Marchese, Robert Katzschmann, and Daniela Rus 1Bucknell University EECS, Massachusetts Institute of Technology, USA
• Many fully soft robotic systems • A planner for whole body motion of a soft suffer from an inability to support planar manipulator that considers the tasks of significant loads both controlling end effector pose while minimizing collisions between the whole arm’s • Parallel architectures offer changing envelop and a confining environment. significantly increased stiffness and Entirely soft planer a wider range of possible dramatic • A modular design for a pneumatic highly manipulator using whole compliant planar manipulator that is composed are planning to move its motions for a soft system entirely of soft silicone rubber. entire body through a confined pipe-like environment.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
99 Session MoB2 State Ballroom Monday, September 15, 2014, 11:10–12:30 Soft-Bodied Robotics / Robot Learning I Chair Jamie Paik, Ecole Polytechnique Federale de Lausanne Co-Chair
11:45–11:48 MoB2.7 11:48–11:51 MoB2.8 An Untethered Jumping Soft Robot Motion Pattern Discrimination for Soft Robots Michael T. Tolley1, Robert F. Shepherd2, Michael with Morphologically Flexible Sensors 1 1 1 Karpelson , Nicholas W. Bartlett , Kevin C. Galloway , Utku Culha, Umar Wani, Surya G. Nurzaman1, Frank 1 1 1 Michael Wehner , Rui Nunes , George M. Whitesides , Clemens2 and Fumiya Iida1 Robert J. Wood1 1Institute of Robotics and Intelligent Systems , ETH Zurich, Switzerland 1Harvard University 2Cornell University 2EMPA Dubendorf, Switzerland • We present an untethered soft-bodied • Suggested approach designs robot that uses a combination of custom sensor morphologies pneumatic and explosive actuators for for soft robots. directional jumping • Sensors are fabricated out of • This robot can jump 0.6 m (7.5 times conductive thermoplastic it’s body height) elastomers. • We also present a thermodynamic model for the combustion of butane • Body integrated sensors can discriminate twisting and used to power jumping serpentine motion patterns.
11:51–11:54 MoB2.9 11:54–11:57 MoB2.10 Active Compliant Control Mode for Conformable Actuation and Sensing with a Pneumatic Soft Robot Robotic Fabric Jeffrey Queißer1, Klaus Neumann1, M. Yuen1, A. Cherian1, Matthias Rolf2, Felix Reinhart1 and Jochen Steil1 J.C. Case1, J. Seipel1 and R.K. Kramer1 1University of Bielefeld 2Osaka University 1Purdue University • Passive compliant air-actuated • Thread-like actuators “Bionic Handling Assistant” (Festo) and sensors are sewn • Accurate models not available onto a fabric base • Hybrid control with learned • Two distinct modes of equilibrium model and classical motion (bending (a), feedback control enables compression (b)) are controlled by varying – Fast and agile control the orientation of the – Compliant control mode fabric
11:57–12:00 MoB2.11 12:00–12:03 MoB2.12 Kinematics of a New Class of Soft Unsupervised and online non-stationary Actuators based on generalized PAMs obstacle discovery and modeling using a laser range finder Girish Krishnan1 G. Duceux, D. Filliat 1University of Illinois Urbana-Champaign ENSTA ParisTech - INRIA FLOWERS •A Configuration Memory effect, • Detect, learn and recognize dynamic analogous to the shape memory objects using standard laser scanner effect is proposed to explain the • Multi-view model based on bags of behavior. laser scan descriptors • The behavior is validated by FEA • 89% recognition rate on 22 objects and prototype testing. using supervised learning • Design implications of the • Discover coherent object models configuration memory effect are without supervision explored 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
100 Session MoB2 State Ballroom Monday, September 15, 2014, 11:10–12:30 Soft-Bodied Robotics / Robot Learning I Chair Jamie Paik, Ecole Polytechnique Federale de Lausanne Co-Chair
12:03–12:06 MoB2.13 12:06–12:09 MoB2.14
Mutual Learning of an Object Concept and Language Model Object Manifold Learning with Action Features Based on MLDA and NPYLM for Active Tactile Object Recognition Tomoaki Nakamura1,2, Takayuki Nagai2, Kotaro Funakoshi1, Daisuke Tanaka, Takamitsu Matsubara, Shogo Nagasaka3, Tadahiro Taniguchi3, and Naoto Iwahashi4 Kentaro Ichien and Kenji Sugimoto 1Honda Research Institute Japan Co., Ltd, 2University of Electro-Communications 3Ritsumeikan University, 4Okayama Prefectural University Nara Institute of Science and Technology, Japan • We propose a stochastic model by • Tactile object recognition by active which a robot can mutually learn a Thisisa exploratory movements language model and object concepts plasticbottle • Object Manifold Learning to extract • The object concept is formed by low-dimensional object features classifying multimodal information, from tactile data and action features and the language model is acquired • Sequential object’s belief update on from human speech the manifold with information- • The accuracy of speech recognition and object concept maximizing movements can be improved by the mutual learning
12:09–12:12 MoB2.15 12:12–12:15 MoB2.16 Entropy-Based Strategies for Physical Knowledge Propagation and Relation Exploration of the Environment's Learning for Predicting Action Effects Degrees of Freedom Sandor Szedmak, Emre Ugur, and Justus Piater 1 1 Stefan Otte , Johannes Kulick , Marc Toussaint1 and Oliver Brock2 University of Innsbruck University Stuttgart1, Technical University Berlin2 • Complex affordances are learned • The Exploration Challenge: minimizing the entropy of from large amount of sparse data the environment's degrees of freedom by exploration via Max-Margin based methods • Integrated system: motion, action selection, learning,... from recommender systems. • Predictions are propagated by superposing all paths in the underlying object interaction graph.
12:15–12:18 MoB2.17 12:18–12:21 MoB2.18
Learning to Reach into the Unknown: Haptic Representation for Manipulating Selecting Initial Conditions When Reaching in Clutter Deformable Food Objects Daehyung Park, Ariel Kapusta, Youkeun Kim, Mevlana Gemici and Ashutosh Saxena James M. Rehg and Charles C. Kemp Cornell University Georgia Institute of Technology • Learning Initial Conditions (LIC) is • Goal: Have robot prepare a salad! a data-driven approach. • LIC learns a probabilistic model with • Input: Haptic sensory signals (force and touch). only a few features from a library of previous experiences using the • Machine learning for modeling the behavior in similar context. physical properties of food objects. • LIC selects a good initial • Unsupervised learning of beliefs about configuration that greatly improves a haptic properties of an object. robot’s success at reaching to a goal.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
101 Session MoB2 State Ballroom Monday, September 15, 2014, 11:10–12:30 Soft-Bodied Robotics / Robot Learning I Chair Jamie Paik, Ecole Polytechnique Federale de Lausanne Co-Chair
12:21–12:24 MoB2.19 12:24–12:27 MoB2.20 A neural dynamics architecture for Control in the Reliable Region of a Statistical grasping that integrates […] Model with Gaussian Process Regression G. Knips1, S. K. U. Zibner1, Youngmok Yun and Ashish D. Deshpande 1 1 1 H. Reimann , I. Popova and G. Schöner Dept of Mechanical Engineering, The University of Texas at Austin, USA 1Ruhr-Universität Bochum • We present a novel statistical • Integrative grasping architecture model-based control algorithm, called Control in the Reliable based solely on neural dynamics Region of a Statistical Model • Autonomous organization of scene (CRROS)
representation, pose estimation, • CRROS is to track a desired object classification, and movement output by using the generation pseudoinverse of the Jacobian of the GPR model, and A manipulator called the Flex-finger, • On-line updating as an emergent simultaneously regulate the null for which it is challenging to build an analytical model, was controlled to space to drive toward a region feature validate CRROS of low uncertainty.
12:27–12:30 MoB2.21 Confidence-based roadmap using Gaussian process regression for a robot control Y. Okadome1, Y. Nakamura1, K. Urai1, Y. Nakata1 and H. Ishiguro1 1Osaka university • `Sample’-based motion planning • Inverse dynamics: estimated by Gaussian process regression • Edge cost: confidence interval • Application: control of an actual robotic arm driven by air-actuators
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
102 Session MoB3 Red Lacquer Room Monday, September 15, 2014, 11:10–12:30 Navigation / Visual Servoing Chair Seth Hutchinson, University of Illinois Co-Chair
11:10–11:30 MoB3.1 11:30–11:33 MoB3.2 Environment-based Trajectory Keynote: From Robotics to VR and Back Clustering for Autonomous Vehicles 1,2 2 2 Steve LaValle Georg Tanzmeister , Dirk Wollherr , Martin Buss Oculus VR and University of Illinois 1BMW Group Research and Technology, 2 Inst. Automatic Control Engineering, TU München • Finally, current technology can support compelling VR • Similar to homotopy, but without • VR challenges are familiar to same-goal-state requirement, roboticists: configuration spaces, thus for local motion planner sensing, localization, collision • Closed curve is formed by detection, HCI, algorithms sampling intermediate trajectories • VR + robots = fun! • O(n) in the number of paths for non-overlapping clusters
11:33–11:36 MoB3.3 11:36–11:39 MoB3.4
Wide-Field Optical Flow Aided Inertial Experimental Study of Odometry Estimation Navigation for Unmanned Aerial Vehicles Methods using RGB-D Cameras 1 2 3 Matthew B. Rhudy , Haiyang Chao , and Yu Gu Zheng Fang1, Sebastian Scherer2 1 2 Lafayette College University of Kansas 1Northeastern University, China 2Carnegie Mellon 3 West Virginia University University, USA • An integration of wide-field optical • Six real-time RGB-D visual odometry estimation flow and Inertial measurements was methods are evaluated. performed for UAV ground speed • Libviso2 (Visual Feature) and attitude estimation; • Fovis (Visual & Depth) • Non-drifting estimates were • DVO (Intensity & Depth) obtained with approximately 1.4 m/s • FastICP (Point Cloud) of error for velocity and 1.4 degrees of standard deviation of error for • GICP (Geometric & Cloud) pitch and roll attitude angles. • NDT (Visual & Cloud)
11:39–11:42 MoB3.5 11:42–11:45 MoB3.6 Precise Vision-Aided Aerial Navigation Real-time Autonomous 3D Navigation for Tracked Vehicles in Rescue Environments Han-Pang Chiu, Aveek Das, Phillip Miller, Supun Samarasekera, Rakesh (Teddy) Kumar Matteo Menna1, Mario Gianni1, Center for Vision Technologies, SRI International, USA Federico Ferri1 and Fiora Pirri1 1 • We proposes a novel aerial ALCOR Lab, University of Rome ‘Sapienza‘, Italy navigation approach to continuously estimates precise 3D absolute pose • Flipper contact sensor model using only IMU and mono. cameras. • Curvatures and normals estimation • All sensor measurements are fully optimized in a smoother-based • Segmentation and labeling inference framework over a constant- length of sliding window. • Traversability • Experimental results demonstrate • 3D path and motion planning that our approach provides accurate • Geo-registered information are (3D RMS error < 10 meters) and incorporated into two kinds of visual consistent solutions on large-scale measurements: (1) 2D-3D tie-points GPS-denied scenarios. (2) geo-registered feature tracks.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
103 Session MoB3 Red Lacquer Room Monday, September 15, 2014, 11:10–12:30 Navigation / Visual Servoing Chair Seth Hutchinson, University of Illinois Co-Chair
11:45–11:48 MoB3.7 11:48–11:51 MoB3.8 Interactive Navigation of Humans from a Layered Costmaps Game Theoretic Perspective For Contextualized Navigation Annemarie Turnwald, Wiktor Olszowy, David V. Lu1, D.Hershberger2 and W.D. Smart3 Dirk Wollherr and Martin Buss 1Washington University in St. Louis LSR, Technische Universität München, Germany 2Willow Garage 3Oregon State University • Interactive navigation • Robot navigation requires many types of humans of information b mutual avoidance • Monolithic costmaps are unsuited for tracking complex contextual information • Interaction can be explained • Layered costmaps semantically with the theory of Nash separate obstacle, proxemic and other equilibria in non- data into modularized layers. cooperative games. • Integrated into ROS Navigation Stack
11:51–11:54 MoB3.9 11:54–11:57 MoB3.10 Omnidirectional 3D Reconstruction in Semantic Mapping for Object Category Augmented Manhattan Worlds and Structural Class Miriam Schönbein1, Andreas Geiger2, Zhe Zhao, Xiaoping Chen 1MRT, Karlsruhe Institute of Technology, Germany University of Science and Technology of China 2MPI for Intelligent Systems, Tübingen, Germany • 360 reconstruction from • We want to build a semantic map of imageiimmage catadioptric stereo pairs. the indoor scene with object category and structural class. • Hough voting-based plane anyanny texttteexxtt inin theththe • Each RGB-D image is labeled by a hypotheses. imageimage shshouldhououldld CRF model and the camera poses • Slanted-plane MRF. bebe thethhee samesamame are estimated by RGB-D SLAM. • Novel omnidirectional data sizessiizeze asas mainmamaiinn set with 3D ground truth. text • The final semantic map is built through the semantic label fusion step.
11:57–12:00 MoB3.11 12:00–12:03 MoB3.12 Anytime Navigation with 6D Image-based Visual Servoing with Progressive Hindsight Optimization uncalibrated Stereo Cameras Julio Godoy, Ioannis Karamouzas, Caixia Cai, Emmanuel Dean-Leon, Stephen J. Guy and Maria Gini Nikhil Somani and Alois Knoll University of Minnesota Technische Universität München, Germany • We propose an anytime algorithm ORCA (PHOP) to plan paths of agents in an • New 6D image features for environment with many other agents. dynamic IBVS • An agent predicts the motion of other • New full-rank square Image agents and plans its path accordingly. PHOP Jacobian It executes one step of the plan and • Singularity-free repeats the process. • Uncalibrated stereo cameras • PHOP increases the energy and time efficiency of the agents’ motion. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
104 Session MoB3 Red Lacquer Room Monday, September 15, 2014, 11:10–12:30 Navigation / Visual Servoing Chair Seth Hutchinson, University of Illinois Co-Chair
12:03–12:06 MoB3.13 12:06–12:09 MoB3.14
Weakly Calibrated Stereoscopic Visual Servoing for Novel Two-Stage Control Scheme for Laser Steering: Application to Phonomicrosurgery Robust Constrained Visual Servoing
Brahim Tamadazte and Nicolas Andreff Akbar Assa, Farrokh Janabi-Sharifi FEMTO-ST Institute, AS2M department Department of Mechanical and Industrial Engineering 24 rue Savary, 25000 Besançon, Ryerson University
Initial Image 130 • Stereoscopic visual servoing • A two-stage controller is proposed Desired Image Image Boundaries 120 • Multiple view geometry for constraint-aware robust visual 110 100 v (pixel) • Automatic laser steering for laser servoing. 90 80
surgery • A model predictive controller is 70 120 140 160 180 200 u (pixel) • Weak eye-to-hand and camera exploited for constraint handling. -0.8 calibration • The effect of uncertainties are -0.6 -0.4 z (m) • Decoupled controller, stable and minimized through a proper cost -0.2 0 0.2 easy to implement 0.2 0 function. 0 -0.2 -0.2 y (m) x (m) 12:09–12:12 MoB3.15 12:12–12:15 MoB3.16 Lyapunov-stable Eye-in-hand Kinematic Visual A Sequence of Micro-assembly for Irregular Servoing with Unstructured Static Feature Points Objects Based on a Multiple Manipulator Platform David Navarro-Alarcon and Yun-hui Liu Dengpeng Xing, De Xu, and Haipeng Li, The Chinese University of Hong Kong Institute of Automation, Chinese Academy of Sciences • Design a micro-operational platform • We present two visual servoing with multiple manipulators to methods to regulate the image accomplish a sequence of position of unstructured feature microassembly for irregular points components • Desire to solve the soft assembly with • We prove the stability of these contact image-based controllers with • Propose a hybrid control strategy to Lyapunov theory achieve high precision and protect objects
12:15–12:18 MoB3.17 12:18–12:21 MoB3.18 Visual Servoing Based Trajectory Image Jacobian Estimation Using Structure Tracking of Underactuated Water Surface from Motion on a Centralized Point Robots without Direct Position Victor Nevarez1 and Ron Lumia1 Measurement 1University of New Mexico Kai Wang, Yunhui Liu and Luyang Li • A centralized motion The Chinese University of Hong Kong algorithm (CMA) is • Estimate the global position of the proposed as a fast and robot online using natural visual efficient online calibration features and AHRS sensors method. • Proved asymptotic tracking of a • By exploiting a desired trajectory and convergence “centralized motion” a of the position estimation to the chosen feature point actual position should have little to no • The experiment demonstrated the change in pixel CMA error model validity of the proposed controller coordinates. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
105 Session MoB3 Red Lacquer Room Monday, September 15, 2014, 11:10–12:30 Navigation / Visual Servoing Chair Seth Hutchinson, University of Illinois Co-Chair
12:21–12:24 MoB3.19 12:24–12:27 MoB3.20 A Two Phase RGB-D Visual Servoing VisionVision Guided Robotic Block StackiStackingng Controller Nathanael Macias JJohnohn T. Wen Abdullah Hojaij1, John Zelek1, Applied Physics Laboratory RensselaerRensselaer PolPolyytechnic Institute Daniel Asmar2 • Goal: Robust vision-based block ppick-upick-up and stackingstacking usingusing 1University of Waterloo, 2AUB webcamwebcam anandd industrialindustrial robotrobot • Approach:Approach: Binary marker forfor block identiidentification/locafication/localization;lization; CustomCustom • Two-phase visual servoing using a gripper fforor fflexiblelexible & reliable grasgrasp;p; OOptimization-basedptimization-based pick-uppick-up Kinect RGB-D sensor strategy;strategy; RRobotobot RRaconteuraconteur didistribstributeutedd mmiddlewareiddleware arcarchitecturehitecture • Phase 1 is a quick alignment phase using registration of image features • Phase 2 is a refinement based on depth-map error minimization • Experiments performed on a Barret WAM manipulator
12:27–12:30 MoB3.21
Pose Error Correction For Visual Features Prediction Nicolas Cazy Irisa/Inria, Rennes, France Claire Dune University Sud Toulon-Var La Garde at HandiBio, France Pierre-Brice Wieber Inria, Grenobles, France Paolo Robuffo Giordano CNRS at Irisa/Inria, Rennes, France François Chaumette Irisa/Inria, Rennes, France • Novel nonlinear correction strategy to correct the relative pose between the camera and the target
• Comparison of the improvements obtained during the feature prediction phase
• Simulation results for a eye-in hand camera and four point features
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
106 Session MoC1 Grand Ballroom Monday, September 15, 2014, 13:50–15:10 Micro/Nano Robotics I / Manipulation and Grasping II Chair Oliver Brock, Technische Universität Berlin Co-Chair
13:50–14:10 MoC1.1 14:10–14:13 MoC1.2 Keynote: Micro and Nano Robotics Three Dimensional Multi-cell Spheroids for Biomedical Innovations Assembly using Thermoresponsive Gel Probe Masaru Takeuchi1, Masahiro Nakajima1, Fumihito Arai Toshio Fukuda1,2,3 and Yasuhisa Hasegawa1 Nagoya University 1Nagoya University 2Meijo University • Micro and Nano Robotics: 3Beijing Institute of Technology What is expected in biomedical • Spheroids manipulation was achieved by the Thermoresponsive Gel probe field? Why Robotics?? Force sensor Spheroid • On-chip Robotics: Key issues! • Cell viability was checked after • Essential micro-nano fabrication: manipulation of spheroids by the probe present and future Probe • Patterning of multi-cell spheroids in 2D • Open Question: How do you and 3D was achieved. control floating cells on a chip? • Cells were grown in the assembled 200 m spheroid structures
14:13–14:16 MoC1.3 14:16–14:19 MoC1.4 Construction of Vascular-like Microtubes via Magnetic Actuation of Ultra-Compliant Fluidic Axis-translation Self-assembly based on Micro Robotic Mechanisms Multiple Hydrogels Tao Yue, Masahiro Nakajima, Masaru Takeuchi, Toshio Fukuda 1 1 Dept. Micro-Nano Systems Engr., Nagoya University, Japan Dana Vogtmann and Sarah Bergbreiter Qiang Huang, and Toshio Fukuda 1University of Maryland, College Park School of Mechatronical Engr., Beijing Institute of Technology, China
• A method of constructing 3D multilayered • Microfabricated mechanisms vascular-like microtubes based on fluidic with integrated elastomeric axis-translation self-assembly of 2D hinges are actuated using microstructures was presented. • Microtubes with alternating cell layers were embedded magnetic features constructed based on multiple hydrogels. in an external magnetic field • The fabrication of GelMa microstructures was demonstrated and the degradability of • Simple in- and out-of-plane cell embedded GelMa microstructures was mechanisms and a magnetically actuated evaluated. The construction of vascular-like compliant gripper are demonstrated microtubes by multiple hydrogels
14:19–14:22 MoC1.5 14:22–14:25 MoC1.6 Selective and Rapid Cell Injection of Fluorescence Sensor Encapsulated in Liposome Using Optical Control of Zeta Potential Real-Time LOC-based Morphological Cell and Local Mechanical Stimulus by Optical Tweezers Analysis System Using High-Speed Vision Hisataka Maruyama, Taisuke Masuda, Qingyi Gu, Tadayoshi Aoyama, Takeshi Takaki, Liu Hengjun and Fumihito Arai Idaku Ishii, Ayumi Takemoto, and N. Sakamoto Nagoya University Hiroshima University • Selective adhesion and injection Sensor compact of micro-nanoparticle sensor • Real-time Vision-based camera Morphological Analysis System head into a specific cell • Multi-object extraction by microscope • Optical control of zeta potential 100 nm hardware on HFR vision system using photoisomerization of Vibration electric 10 • Cell tracking and analysis on PC syringe lens photochromic material • Morphological analysis of fertilized pump • Local vibration stimulus using sea urchin eggs in microchannel optical tweezers for rapid and • Size, eccentricity, transparency microfluidic local injection of the sensor • 500 cells/second chip 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
107 Session MoC1 Grand Ballroom Monday, September 15, 2014, 13:50–15:10 Micro/Nano Robotics I / Manipulation and Grasping II Chair Oliver Brock, Technische Universität Berlin Co-Chair
14:25–14:28 MoC1.7 14:28–14:31 MoC1.8 Noncontact Fine Alignment for Study on Rotational an Unclogging Multiple Microcontact Printing Motions of Magnetic Chain-Like Nobuyuki Tanaka1, 2, Hiroki Ota2, Microrobot Kazuhiro Fukumori2, Masayuki Yamato2, Karim Belharet1, David Folio2 and Antoine Teruo Okano2, and Jun Miyake1 Ferreira2 1Osaka Univ. 2Tokyo Women’s Medical Univ. 1HEI campus Centre 2INSA-CVL • PDMS stamp was adjusted by • Modeling of magnetic microrobot integrated linear/rotation navigating in viscous flow stages within a maximum • Experimental setup error of 33 m. • Magnetic rotation of chain-like • Three-time microcontact microrobot in viscous flow printing was performed for • An unclogging strategy for the single cell culture dish. chain-like magnetic microrobot
14:31–14:34 MoC1.9 14:34–14:37 MoC1.10 A Stick-Slip Omnidirectional Powertrain for Low-Cost Swarm Robotics John Klingner1, Anshul Kanakia1, Nicholas T.Motoyoshi1, M.Kojima1, K.Ohara1, M.Horade1 Farrow1, Dustin Reishus, and Nikolaus Correll1 K.Kamiyama1,Y.Mae1 and T.Arai1 1University of Colorado Boulder 1 Osaka University • We present a mechanism using image simple vibration motors for Suck Supply • Chemical Stimulation System omnidirectional motion in a any text in the for single cell analysis physical robot. image should • Control the concentration of • We also present an approach for be the same the solution between pipettes calibration and control of this size as main • Observing by the fluorescent mechanism. text substance 100μm
14:37–14:40 MoC1.11 14:40–14:43 MoC1.12 Non-vector Space Stochastic Control for Task Specific Robust Grasping For Nano Robotic Manipulations Multifingered Robot Hands George Boutselis, Charalampos Bechlioulis, Jianguo Zhao1, Bo Song1, and Ning Xi1 Minas Liarokapis and Kostas Kyriakopoulos 1Michigan State University NTUA, School Of Mechanical Engineering • With image feedback, non- • Determination of task oriented vector space control is applied optimal configuration using the Q- to nano robotic manipulations; distance • Combined with stochastic • Dealing with grasping uncertainties control, the method can deal • Computation of sufficient contact with noisy image feedback; forces • The precision can be as good • Experimental validation utilizing as image resolution without tactile sensing position sensors. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
108 Session MoC1 Grand Ballroom Monday, September 15, 2014, 13:50–15:10 Micro/Nano Robotics I / Manipulation and Grasping II Chair Oliver Brock, Technische Universität Berlin Co-Chair
14:43–14:46 MoC1.13 14:46–14:49 MoC1.14
Achieving Elastic Stability of Concentric Tube Robots Through Optimization of Tube Precurvature Cable Stiffened Flexible Link Manipulator Junhyoung Ha1, Frank C. Park1 and Rahul Dixit1,2, R Prasanth Kumar2 Pierre E. Dupont2 1Research Center Imarat, DRDO, Hyderabad 1Seoul National Univ. 2Harvard Medical School 2Indian Institute of Technology Hyderabad • Varying tube pre-curvature as • Bending stiffness is much less a function of arc length is used than axial stiffness in tension as a means to enhance • Using cables/strings, deflection stability. can be reduced significantly with • Stability conditions for a planar marginal increase in inertia tube pair are presented. • Drawback of acceleration • Optimal design problem is induced buckling could be defined to maximize stability. Enhanced stability by overcome using multiple strings varying pre-curvature
14:49–14:52 MoC1.15 14:52–14:55 MoC1.16
Robotic Handwriting: Multi-contact Cooperative Suspended Object Manipulation Using Manipulation Based on Reactional Reinforcement Learning and Energy-based Control Internal Contact Ivana Palunko1, Philine Donner2, S.-K. Kim1, J. Jo2, Y. Oh2, S.-R. Oh2, Martin Buss2 and Sandra Hirche3 S. Srinivasa1, M. Likhachev1, 1UNIZG-FER 2TUM-IAS 3TUM-ITR 1 2 Carnegie Mellon University KIST • Adaptive controller which combines • Multi-contact manipulation reinforcement learning with energy = stable object-body grasping based swing-up control. + dexterous object-end manipulation • It is successfully verified in a single • Difficult due to internal link contact robot and human-robot experimental • By utilizing the internal contact force setup for different suspended that works as a reaction force, objects. desired fingertip forces can be reduced for handwriting tasks
14:55–14:58 MoC1.17 14:58–15:01 MoC1.18
Robotic Dual Probe Setup for Reliable Pick and Place Processing on the Nanoscale ! Tobias Tiemerding1, Sören Zimmermann1, T. M. Caldwell1, D. Coleman1 and N. Correll1 Sergej Fatikow1,2 1University of Colorado, Boulder 1University of Oldenburg, 2OFFIS • Due to adhesive forces pick and place • Stiffness identification of flexible loop using handling of nanoparticles is not highly Rethink Robotics Baxter robot. reproducible • Formulates model parameter identification of flexible objects with variational • Dual AFM tip technique with tailored integrators. end effectors to purposefully utilize • Discrete-time adjoint based gradient forces is presented calculation for optimal parameter • Reliable handling is possible, allowing identification.
for 2D- and 3D (hetero-)structures 1
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
109 Session MoC1 Grand Ballroom Monday, September 15, 2014, 13:50–15:10 Micro/Nano Robotics I / Manipulation and Grasping II Chair Oliver Brock, Technische Universität Berlin Co-Chair
15:01–15:04 MoC1.19 15:04–15:07 MoC1.20 The Joint Coordination in Reach-to- A Robot System Design for Low-Cost grasp Movements Multi-Robot Manipulation Zhi Li1, Kierstin Gray1, Jay Ryan Roldan1, Dejan James McLurkin1, A.M.1, N.R.1, G.H.1, A.B.1, Milutinovic1, and Jacob Rosen1 A.C.1, H.L.1, M.J.1,N.O.1, J.R.2, S.K., et al. University of California, Santa Cruz, USA 1Rice University, 2USMA • Established open-source • Motion analysis based on kinematic platform with vast sensor modeling of human arm suite • Coordination of grasping-relevant • Omni-directional gripper joints by their task-relevance simplifies manipulation • Synergetic coordination of the • Enables scalable macro- and micro-structures environmental interaction • Guidelines for the control of the • Cost-effective design upper limb exoskeleton allows for large swarms
15:07–15:10 MoC1.21 Declarative Specification of Task-based Grasping with Constraint Validation Sven Schneider1, Nico Hochgeschwender1 and Gerhard K. Kraetzschmar1 1Bonn-Rhein-Sieg University • Grasping objects in a task-oriented manner is challenging for a robot • It requires an understanding of the object, the task and the robot's capabilities • We capture this knowledge in the Grasp Domain Definition Language (GDDL) • Formal constraints allow validation of the specifications
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
110 Session MoC2 State Ballroom Monday, September 15, 2014, 13:50–15:10 Humanoids and Bipeds I / Computer Vision I Chair Rüdiger Dillmann, Karlsruhe Institute of Technology (KIT) Co-Chair
13:50–14:10 MoC2.1 14:10–14:13 MoC2.2 Keynote: What is a humanoid robot Identification of HRP-2 Foot's Dynamics good for? Kazuhito Yokoi Yuya Mikami1, Thomas Moulard2, AIST Eichi Yoshida2 and Gentiane Venture1 1TUAT 2CNRS-AIST • R&D of humanoid robots are very active all around the world in order to • Identified about the viscoelasticity of open up a new application besides the sole rubber bush of HRP-2 research tool and crowd puller. • Used some simple active motions • Is it true that a future humanoid robot and composed these motions will execute complex tasks in • Compare the identified parameters dangerous, degraded, human- using the experimental results and engineered environments or evaluate simulator results human assistive device?
14:13–14:16 MoC2.3 14:16–14:19 MoC2.4 Integration of Non-Inclusive Contacts 3D Dynamics of Bipedal Running: Effects of in Posture Generation Step Width on an Amputee-Inspired Robot S. Brossette, A. Escande, J. Vaillant, F. Keith, Timothy Sullivan1 and Justin Seipel1 T. Moulard and A. Kheddar 1Purdue University CNRS-UM2 LIRMM, CNRS-AIST JRL • Novel approach for contact search • We studied the effects • Smooth optimization of contact of varying step width on patch positioning by modeling the 3D running stability contact region as ellipse of a bipedal amputee- • Allows richer set of feasible poses inspired robot. • Allows contact between non- • As the step width is inclusive polygons decreased towards human-like values,
stability decreases.
14:19–14:22 MoC2.5 14:22–14:25 MoC2.6
State Estimation for a Humanoid Robot
† † 1 2 † Nicholas Rotella , Michael Bloesch , † 3 1,3 Ludovic Righetti and Stefan Schaal Centre for Robotics Research, King’s College London, United Kingdom 1 2 3 USC ETH Zurich Max Planck Institute
• • State estimation framework humanoid’s agnostic of task, terrain and robot. • system’s • Fuses integrated IMU sensor data with knowledge of leg kinematics. • • Utilizes full 6DOF pose of feet to • improve observability properties and performance over prior work. • Verified in simulated walking task.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
111 Session MoC2 State Ballroom Monday, September 15, 2014, 13:50–15:10 Humanoids and Bipeds I / Computer Vision I Chair Rüdiger Dillmann, Karlsruhe Institute of Technology (KIT) Co-Chair
14:25–14:28 MoC2.7 14:28–14:31 MoC2.8 Sideward Locomotion Control of Biped Modular Low-Cost Humanoid Platform Robots Based on Dynamics Morphing For Disaster Response Hiroshi Atsuta1 and Tomomichi Sugihara1 S. –J. Yi1, S. McGill1, L. Vadakedathu1, Q. He1, 1Osaka University, Japan I. Ha2, M. Rouleau3, D. Hong4, and D. D. Lee1 1 2 3 4 • A trajectory-free sideward locomotion controller for U. of Penn Robotis Virginia Tech UCLA biped robots is proposed. • Modular, general purpose actuators • A cyclic acceleration and decel- and structural components eration is needed for avoiding • Low development and manufacture the collision of the pair of legs. cost, rapid field repairability • This is realized by alternating • Modular and multi-layered software the velocity-following control structure and the self-excited oscillating • Acquired the finalist status at DRC control in accordance with the Trials 2013 supporting condition.
14:31–14:34 MoC2.9 14:34–14:37 MoC2.10 Control Strategies for Driving Utility Balancing experiments on a torque-controlled Vehicles with a Humanoid Robot humanoid with hierarchical inverse dynamics Christopher Rasmussen1, Kiwon Sohn2, Alexander Herzog1, Ludovic Righetti1,2, Qiaosong Wang1 and Paul Oh2 Felix Grimminger1 Peter Pastor 2, Stefan Schaal1,2 1University of Delaware 2Drexel University 1Max-Planck IS, AMD 2Uni. South. Calif., CLMC • Sensor head & driving software for • we express DRC-Hubo and constraints on sub-parts • Vehicle recognition, robot pose of a torque controlled humanoid estimate from point clouds • the is used in a • Steering & speed actuation and run in a 1 kHz • Velocity control, trajectory following control-loop • Results from simulation, 5+ km of • the control framework is evaluated on the offline data, integrated live tests real robot together with , , etc 14:37–14:40 MoC2.11 14:40–14:43 MoC2.12 Dynamic State Estimation using “Look at this!” Learning to Guide Visual Quadratic Programming Saliency in Human-Robot Interaction X Xinjilefu Boris Schauerte1, Rainer Stiefelhagen1 Siyuan Feng and Christopher G. Atkeson 1Karlsruhe Institute of Technology Carnegie Mellon University
' Using full-body dynamics for • We train CRFs to identify and humanoid state estimation segment (unknown) objects that have
' Advantages of a QP estimator over been pointed at and/or spoken about a nonlinear Kalman filter • Here, saliency highlights potential
'Does not require the dynamic candidate objects (or parts) and we system in the state space form do not require detectors for specific objects or object classes 'Handles constraints naturally • We select the correct object in over 'Considers modeling error 80% of the evaluation samples 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
112 Session MoC2 State Ballroom Monday, September 15, 2014, 13:50–15:10 Humanoids and Bipeds I / Computer Vision I Chair Rüdiger Dillmann, Karlsruhe Institute of Technology (KIT) Co-Chair
14:43–14:46 MoC2.13 14:46–14:49 MoC2.14 SuperFAST : Model-Based Adaptive Corner Auto-adjusting Camera Exposure for Detection for Scalable Robotic Vision Outdoor Robotics using Gradient Information
Gaspard Florentz1 and Emanuel Aldea2 Inwook Shim, Joon-Young Lee, In So Kweon 1Parrot SA, 2Paris Sud U. Robotics and Computer Vision Lab, KAIST
• Predict an optimal threshold for • Adjusting camera FAST detector to extract a constant exposure to maximize number of corner image features in the Auto Manual Ours • Based on an occurrence Model gradient domain. • Uses temporal and inter-scale • Robust against Auto Manual Ours analysis illumination conditions. • 1ms for detection + bucketing • Proposed method is designed for outdoor • Relevant for highly-optimized SLAM Auto robotics application. Manual Ours
14:49–14:52 MoC2.15 14:52–14:55 MoC2.16 Real-Time Sequential Model-Based Non- Rigid SFM Siddharth Choudhary, Alexander J. B. Trevor, S. Bronte1, M. Paladini2, Henrik I. Christensen and Frank Dellaert L. M. Bergasa1, L. Agapito3 and R. Arroyo1 Georgia Institute of Technology 1UAH 2Ocado Tech. 3UCL • Integrates object discovery and • The method, based on PTAM, image modeling in a SLAM framework. is capable of giving pose and
• Online learning paradigm. deformation coefficients of an object for each frame based in any text in the • An object database is produced the previous frame estimation. image should along with the map. be the same • Processing time meets real • Discovered objects used as size as main time constrains (~30 fps). landmarks during SLAM, producing text improved mapping result. • Maintains a good balance performance-accuracy.
14:55–14:58 MoC2.17 14:58–15:01 MoC2.18
Direct Superpixel Labeling for Mobile Robot Navigation A Directional Visual Descriptor for Using Learned General Optical Flow Templates Large-Scale Coverage Problems Richard Roberts1, Frank Dellaert1, M. Tamassia1, A. Farinelli3, V. Murino2 and A. Del Bue2 1Institute for Robotics and Intelligent Machines, 1RMIT Univ., 2Istituto Italiano di Tecnologia, 3Univ. of Verona Georgia Institute of Technology
• Semantic superpixel labeling • How to visually cover 3D environments for obstacle detection. autonomously? • For uncalibrated cameras • Define the visibility of the camera in terms of FoV, focus, resolution, viewing with arbitrary optics. angle, etc. • Informed by optical flow • We propose a directional coverage templates learned descriptor for visual based navigation. • Experiments in a simulated environment unsupervised from data. using real world data.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
113 Session MoC2 State Ballroom Monday, September 15, 2014, 13:50–15:10 Humanoids and Bipeds I / Computer Vision I Chair Rüdiger Dillmann, Karlsruhe Institute of Technology (KIT) Co-Chair
15:01–15:04 MoC2.19 15:04–15:07 MoC2.20 Real-time Pose Estimation of Deformable PAS: Visual Odometry with Perspective Objects Using a Volumetric Approach Alignment Search Yinxiao Li, Yan Wang, Michael Case, Andrew Richardson and Edwin Olson Shih-Fu Chang, Peter K. Allen University of Michigan Columbia University • A real-time approach to reconstruct • Multi-scale search over pose for a smooth 3D model of a moving motion estimation deformable object • Descriptorless and implicit data • 3D real-time shape matching with a association when matching over learned distance metric unknown motion • A Database of deformable objects • Joint alignment of all features that can be used for efficient data- • Evaluated in visual odometry driven pose recognition system for a small ground robot
15:07–15:10 MoC2.21
Planar Building Facade Segmentation and Mapping Using Appearance and Geometric Constraints
Joseph Lee, Yan Lu, and Dezhen Song Texas A&M University
• Planar building facade segmentation using appearance and geometric data • Planar building facade mapping using reprojection error, orientation, and coplanarity constraints • Reduces angular error of reprojection error-based 3D mapping by an average of 82.82%
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
114 Session MoC3 Red Lacquer Room Monday, September 15, 2014, 13:50–15:10 Bioinspired Robots II / Distributed Robotics Chair M. Ani Hsieh, Drexel University Co-Chair
13:50–14:10 MoC3.1 14:10–14:13 MoC3.2 Keynote: Compliance Computation for Continuum From Biology to Robot and Back Types of Robots Howie Choset G. Smoljkic, D. Reynaerts, Carnegie Mellon J. Vander Sloten and E. Vander Poorten KU Leuven, dept. of mech. eng., Leuven, Belgium • Bio-Inspired robotic
locomotion • Calculation the Compliance Matrix of a single section • Successful locomotion on continuum robot u2 u2 granular medium Robot • Analytic formulation u3 • Low dimensional control of backbone u1 high dimensional systems • Experimentally validated • Robotic validation of biological principles Compliance ellipsoid for force of 0.625N exerted on robot tip
14:13–14:16 MoC3.3 14:16–14:19 MoC3.4 Multiport Modeling of Force and iSplash-II: Realizing Fast Carangiform Displacement in Elastic Transmissions Swimming to Outperform a Real Fish Richard James Clapham and Huosheng Hu Michael Martell and Joshua Schultz School of Computer Science and Electronic Engineering, University of Tulsa University of Essex, United Kingdom
• Construction of an elastic transmission • Outperforming real fish in terms mechanism for a compliant underactuated robotic of average maximum velocity (measured in BL/s) and hand from the interconnection of smaller endurance, the duration that top compliant mechanisms speed is maintained.
• Mathematical model for interaction between • Achieving a maximum velocity of multiple actuators and multiple digits 11.6BL/s (i.e. 3.7m/s) at 20Hz with a stride rate of 0.58 and a • Positive definiteness of a force production of 9N. transmission’s stiffness matrix and grasp stability
14:19–14:22 MoC3.5 14:22–14:25 MoC3.6 Multi-functional Bio-inspired Leg for Torque Control Strategies Underwater Robots For Snake Robots Hee Joong Kim1, Bong Huan Jun2 and Jihong David Rollinson1, Kalyan Vasudev Alwala2, Lee3 1,3Chungnam National University, 2Korea Nico Zevallos1 and Howie Choset1 Ocean Research and Development Institute 1Carnegie Mellon 2IIT Madras • Bio-inspired legged underwater robot • Mimicking the locomotion of diving beetles • Designing multi-functional legs • Performance verification for the designed leg in the water
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
115 Session MoC3 Red Lacquer Room Monday, September 15, 2014, 13:50–15:10 Bioinspired Robots II / Distributed Robotics Chair M. Ani Hsieh, Drexel University Co-Chair
14:25–14:28 MoC3.7 14:28–14:31 MoC3.8 A 3D Motion Planning Framework Human Control of Robot Swarms with for Snake Robots Dynamic Leaders Pål Liljebäck1,2, Kristin Y. Pettersen1, Phillip Walker1,Saman Amirpour Amraii1,Nilanjan Øyvind Stavdahl1 and Jan Tommy Gravdahl1 Chakraborty2,Michael Lewis1 and Katia Sycara2 1NTNU 2SINTEF ICT 1Univeristy of Pittsburgh 2Carnegie Mellon University • We present a motion planning • Investigated dynamically-selected framework for 3D body shape leaders in human-swarm system control of snake robots. • Also restricted information to/from • Instead of joint angles, the body the leaders of the swarm shape is defined in terms of Cartesian coordinates, which gives • Results show that more leaders a more intuitive parameterization. were better, but only to a point • The framework can be applied to • Restricting information also had design complex motion patterns. no effect on user performance
14:31–14:34 MoC3.9 14:34–14:37 MoC3.10 Snakes on an Inclined Plane: Learning Flapping Actuator Inspired by an Adaptive Sidewinding Motion for Lepidotrichia of Ray-Finned Fishes Changing Slopes K.S. Sekar1, M.S. Triantafyllou1,2, Chaohui Gong, Matthew Tesch, David Rollinson and P. Valdivia y Alvarado1,2 and Howie Choset 1Singapore-MIT Alliance for Research and Carnegie Mellon University Technology 2 • Efficient offline learning for Massachusetts Institute of Technology optimal policy • Flapping actuator capable of producing lengthwise curvature is • Robust state estimation for designed and modeled terrain shape inference • Model predictions (deflection, • Online execution by force, and energy consumption) combining optimal policy are compared to experiments in Actuated and state estimation two flapper configurations flapper
14:37–14:40 MoC3.11 14:40–14:43 MoC3.12 Design and Implementation of a Distributed Management and Low Cost, Pump-Based, Depth Control Representation of Data and Context of a Small Robotic Fish in Robotic Applications
M. Macrodimitris, I. Aliprantis, E. Papadopoulos, André Dietrich, Sebastian Zug, National Technical University of Athens Siba Mohammad and Jörg Kaiser • Developed depth control of a small Otto-von-Guericke-Universität Magdeburg biomimetic fish, even at zero speed • General classification of data in • Control implemented using a small smart environments DC pump, pump encoder and • Bottom-up approach of pressure sensor distributed data organization • Partial state feedback controller with nonlinearity • Dynamic reconstruction of world compensation yields good response both in simulation models, as a basis for further ab- and experimentally stractions and data interpretation
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
116 Session MoC3 Red Lacquer Room Monday, September 15, 2014, 13:50–15:10 Bioinspired Robots II / Distributed Robotics Chair M. Ani Hsieh, Drexel University Co-Chair
14:43–14:46 MoC3.13 14:46–14:49 MoC3.14 Rapid Multirobot Deployment Environment-independent Formation Flight with Time Constraints for Micro Aerial Vehicles Stefano Carpin1 Marco Pavone2 Brian Sadler3 1Univ. California Merced 2Stanford University Tobias Nägeli, Christian Conte, Alexander 3Army Research Lb Domahidi, Manfred Morari, Otmar Hilliges • Swarm deployment under temporal • Precise relative formation flight relying deadlines only onboard cameras, IMU and agent- • Provably optimal strategies based to-agent communication. on Constrained Markov Decision • In particular, an on-board monocular Processes camera is used to acquire relative • Exact failure probability distance measurements in combination with a consensus-based distributed • Simulations confirm theoretical Kalman filter. predictions
14:49–14:52 MoC3.15 14:52–14:55 MoC3.16 A distributed optimal strategy for rendezvous Distributed Cohesive Configuration Control of multi-robots with random node failures for Swarm Robots with Boundary Hyongju Park1, Seth Hutchinson1, Information and Network Sensing 1Beckman Institute, University of Illinois at Seoung Kyou Lee and James McLurkin, Urbana-Champaign Rice University • We present a distributed • Aim to achieve flock formation and rendezvous algorithm resilient to heading consensus while maintaining random node failures connectivity • We formulate our problem as 1-step • Combine boundary force algorithm sequential optimal control and clump remover to form convex • We show via simulation results that boundary and dense network our proposed algorithm provides • Propose network sensing and mode better rendezvous performance in switching to maintain connectivity cases for which failures occur from initially vulnerable network 14:55–14:58 MoC3.17 14:58–15:01 MoC3.18 Decentralized and Complete Multi-Robot Mobile Robotic Wireless Sensor Motion Planning in Confined Spaces Networks for Efficient Spatial Prediction Adam Wiktor1, Dexter Scobee1, Linh V. Nguyen1, Sarath Kodagoda1, Sean Messenger2 and Christopher Clark2 Ravindra Ranasinghe1 and Gamini Dissanayake1 1Princeton University 2Harvey Mudd College 1University of Technology, Sydney, Australia • Tree-based Multi Robot Motion • A network of mobile, wireless and noisy sensors is Planning utilized to monitor physical spatial phenomenon that is • Decentralized modelled by Gaussian Markov Random Field (GMRF). 3 • Due to the sparsity of a precision Proposed GMRF • Complete 2.5 Xu et al. [6] matrix, GMRF gains remarkable GP • Validated in simulations and multi- 2 benefits in real-time computation.
robot experiments RMSE 1.5 • Linearly-computed and novel 1 optimal criterion for the adaptive 0.5 0 5 10 15 20 sampling strategy is proposed. time
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
117 Session MoC3 Red Lacquer Room Monday, September 15, 2014, 13:50–15:10 Bioinspired Robots II / Distributed Robotics Chair M. Ani Hsieh, Drexel University Co-Chair
15:01–15:04 MoC3.19 15:04–15:07 MoC3.20 Improving Data Ferrying by Iteratively A Cooperative Formation Control Learning the RF Environment Strategy Maintaining Connectivity Anthony J. Carfang1, Neeti Wagle1, Rajdeep Dutta1, Liang Sun1, and Eric W. Frew1 M K2, R S3 and Daniel Pack1 1University of Colorado Boulder 1U T S A 2IIT K 3U S U • Using a GP, opportunistically learn the radio frequency • A team of 4 UAVs environment while data-ferrying with UA. making formation • After 9 iterations, effective throughput improves from around one target 30% to 93% of optimal, leading to better ferry paths. • The network connectivity changes over time " " & ! $ % % $ $ " "
" #$ ! ! " # depending on the '# agents dynamics " " '
15:07–15:10 MoC3.21 Interactive AR for understanding and analyzing multi-robot systems F. Ghiringhelli1, J. Guzzi2, G.A. Di Caro2, V. Caglioti1, L.M. Gambardella2, and A. Giusti2 1Politecnico Milano 2IDSIA USI/SUPSI Lugano • Localizes, identifies and tracks ground robots in the scene • Augments the camera view with live information exposed by robots, such as textual message and spatially situated data • Provides simple tools to customize the AR view
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
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Tuesday September 16
119
120 Session MoD1 Grand Ballroom Monday, September 15, 2014, 15:20–16:40 Haptics / Surgical Robotics I Chair Jing Xiao, UNC-Charlotte Co-Chair
15:20–15:40 MoD1.1 15:40–15:43 MoD1.2 Keynote: Steering of Flexible Needles Combining Haptics in Robot-Assisted Surgery Kinesthetic and Vibratory Force Feedback Claudio Pacchierotti1,2, Momen Abayazid3, Allison Okamura, Stanford University Sarthak Misra3 and Domenico Prattichizzo1,2 • Haptic feedback in robot-assisted surgery presents 1University of Siena 2Istituto Italiano di Tecnologia challenges in sensing, actuation, control, and 3University of Twente operating room • We present a teleoperated compatibility. robotic system able to steer • This talk will describe flexible needles. recent research • The system computes results and future needle’s ideal position and directions. orientation to reach a given target. Images courtesy of Intuitive • The haptic interface provides Surgical and Zhan Fan Quek kinesthetic-vibratory navigation cues to the clinician. 15:43–15:46 MoD1.3 15:46–15:49 MoD1.4 Touch attention Bayesian models for Design and evaluation of a 1DoF ERF- robotic active haptic exploration based Needle Insertion Haptic Platform Ricardo Martins1, João Filipe Ferreira1 A. G. Sánchez, A. Sanchez, N. Zemiti, P. Poignet, Jorge Dias1,2 LIRMM, Univ. Montpellier 2 - CNRS 1University of Coimbra 2Khalifa University • Active haptic exploration of surfaces - A passive 1 DoF needle insertion haptic interface based using robotic hands. on Electro-Rheological Fluid (ERF) brakes, - Force controller that allows to simulate different tissue • Capability to deal with uncertainty behaviors against the and sensory noise (environments needle movement with an unknown structure). - Very low mechanical • Haptic exploration strategy with impedance generalization capability (different configurations of the surfaces).
15:49–15:52 MoD1.5 15:52–15:55 MoD1.6 Haptic-Enabled Teleoperation for Live- A Mixed-Initiative Control System for an Aerial Line Maintenance Service Vehicle supported by force feedback Vikram Banthia, Yaser Maddahi, Jonathan Cacace1, Alberto Finzi1, Subramaniam Balakrishnan and Nariman Sepehri Vincenzo Lippiello1 University of Mantioba 1University of Naples “Federico II” • This paper investigates haptic- • Mixed initiative control system for UAVs enabled teleoperation of a base- combining continuous mixed initiative excited hydrau lic manipulator planning/replanning and haptic feedback; working under a wireless • The force feedback gives an intuitive feeling of the robot deviation from the communication channel. generated path avoiding replanning; • Results indicate that adding a • The approach is assessed in virtual and speed regulating haptic force to real environments considering simple the system helps linemen navigation tasks to be achieved in a mixed function more effectively. initiative control mode.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
121 Session MoD1 Grand Ballroom Monday, September 15, 2014, 15:20–16:40 Haptics / Surgical Robotics I Chair Jing Xiao, UNC-Charlotte Co-Chair
15:55–15:58 MoD1.7 15:58–16:01 MoD1.8 Design of a Bladder Based Elastomeric Contact Force Decomposition Using Tactile Smart Shoe for Haptic Terrain Display Information for Haptic Augmented Reality
Yue Wang, Mark A. Minor Hyoungkyun Kim1, Seungmoon Choi1 and Wan University of Utah Kyun Chung1 1POSTECH
• Introducing an innovative haptic terrain display footwear; • Decomposing contact force • Capable of rendering slopes and subtle features; into deformation and friction • Passive air bladder; force using contact force and • Fabricated with silicone pressure for haptic AR rubber and embedded • Simulation result showed mechatronics; remarkable performance of • Used in VR and potentially proposed decomposition used as a rehab device. method
16:01–16:04 MoD1.9 16:04–16:07 MoD1.10 ROBOPuppet: 3D Printed Miniatures for Haptic Exploration of Unknown Surfaces Teleoperating Full-Size Robots with Discontinuities Anna Eilering, Giulia Franchi, and Kris Hauser Rodrigo S. Jamisola Jr., Petar Kormushev, School of Informatics and Computing, Indiana Antonio Bicchi, and Darwin G. Caldwell University Italian Institute of Technology • Table-top teleoperation devices • Builds information map of that require near-zero training unknown objects • One-to-one mapping facilitates • Surfaces with sharp turns kinesthetic learning and abrupt dips • Uses 3D printing, inexpensive • Superposition of motion components and free software and force control • Cost < $100 • Rotation of control axes for force and motion control • Plans freely available • Implemented on KUKA LWR 7-DOF robot
16:07–16:10 MoD1.11 16:10–16:13 MoD1.12 Workspace Characterization for Concentric Tube Continuum Robots 1 2 1 J. Burgner , H. B. Gilbert , J. Granna , “ ! ” " # $ % $ $ # P. J. Swaney2 and R. J. Webster III2 1 2 • Leibniz University Hannover Vanderbilt University $ & ! $ ' (& • Compute and characterize workspace ' ) # $ $ ! • Monte Carlo random samples of # $ * $ # $ configuration space * $$ ! • Discrete volumetric representation for • * $ – Reachability & ) $ $ – Redundancy $ &$ ! • Experimental evaluation on 2 physical robot prototypes
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
122 Session MoD1 Grand Ballroom Monday, September 15, 2014, 15:20–16:40 Haptics / Surgical Robotics I Chair Jing Xiao, UNC-Charlotte Co-Chair
16:13–16:16 MoD1.13 16:16–16:19 MoD1.14 Preliminary Evaluation of a New Microsurgical Surgical Structured Light for 3D Robotic System for Head and Neck Surgery Minimally Invasive Surgical Imaging K. Olds1, P. Chalasani1, P. Pacheco-Lopez M.D.2, I. Austin Reiter, Alexandros Sigaras, Dennis Fowler Iordachita1, L. M. Akst M.D.2, R. H. Taylor1 and Peter K. Allen 1Johns Hopkins University 2Johns Hopkins Hospital Columbia University • Robotic Ear Nose and Throat Uses standard laparoscopes Microsurgery System (REMS) Builds 3D model of surgical site • Precision needle insertion Structured Light pattern is evaluation modeling invisible to the surgeon microlaryngeal phonosurgery User Interface allows 3D & 2D • REMS improves performance over side-by-side visualizations manual operation (p<0.01) System provides metrology, allowing precise measurement • Preliminary technical evaluation of anatomy in-vivo
16:19–16:22 MoD1.15 16:22–16:25 MoD1.16 Cooperative Teleoperation with Design of A Unified Active Locomotion Projection-Based Force Reflection for Mechanism for A Wireless Laparoscopic MIS Camera System Amir Takhmar, Ilia G. Polushin, Xiaolong Liu1, Gregory Mancini2, Jindong Tan1 Ali Talasaz, Rajni V. Patel 1UTK, Department of BME Western University 2UTK, Departmetn of Surgery • This work studies the effect of a • This paper proposes an active special type of force reflection locomotion mechanism for a wireless algorithms, called projection-based laparoscopic camera. force reflection, on the stability and • The mechanism consists of a 17 coil performance of a dual-arm haptics- stator and a rotor with 3 permanent enabled teleoperation system for magnets. minimally-invasive surgical • The design achieves 360 degree pan applications. motion and 127~164 degree tilt motion.
16:25–16:28 MoD1.17 16:28–16:31 MoD1.18 Toward Automated Intraocular Laser Quasi-Static Modeling of the da Vinci Surgery Using a Handheld Micromanipulator Instrument Sungwook Yang, Robert A, MacLachlan, Farshad Anooshahpour, Ilia G. Polushin, and Cameron N. Riviere Rajni V. Patel Carnegie Mellon University Western University, London, Ontario, Canada • Micron enables the automated scanning • Two simplified quasi-static models of a laser probe. for the da Vinci instrument are • Visual servoing of an aiming beam with proposed which take into account virtual-fixture and tracking eye movement distributed frictions and compliance by EyeSLAM. of the tendons • Reduces the average error and execution • The key parameters of the models time by 63.6% and 28.5%, respectively, are identified, and the performance of the models is compared to the unaided trials. experimentally evaluated.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
123 Session MoD1 Grand Ballroom Monday, September 15, 2014, 15:20–16:40 Haptics / Surgical Robotics I Chair Jing Xiao, UNC-Charlotte Co-Chair
16:31–16:34 MoD1.19 16:34–16:37 MoD1.20 Design and Evaluation of a Novel Flexible Robot for Design of a Spine-Inspired Kinematic for the Transluminal and Endoluminal Surgery Guidance of Flexible Instruments in MIS Carlo A. Seneci1, Jianzhong Shang1, Konrad Leibrandt1, Valentina Vitiello1, Nisha Patel1, Ara Darzi1, Julian Teare1 Mattias F. Traeger, Daniel B. Roppenecker, and Guang-Zhong Yang1, 1Imperial College London Matthias R. Leininger, Florian Schnoes and Tim C. Lueth MIMED, TU München, Germany • Snake-like robot for endoluminal • Laser sintered robotic system for endoscopic and transluminal surgeries surgery • KUKA LWR for insertion • Constant Curvature Model and Workspace Simulation • High dexterity, flexibility and stability • Actuation concept • Intuitive control algorithms • Triangulation and force application tests prototype for endoscopic • Precise and repetitive positioning interventions with the spine-inspired kinematic • Experiment simulating transoral structure actuated with gastric procedure push rods
16:37–16:40 MoD1.21 Hybrid Control of Master-slave Control and Admittance Control for Safe Remote Surgery Takayuki Osa1, Satoshi Uchida1, Naohiko Sugita1 and Mamoru Mitsuishi1 1The University of Tokyo • The system autonomously avoids the excessive contact force by switching master-slave control and admittance control. • Contact force between a surgical instrument and an object was limited within an acceptable range in a stable manner
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
124 Session MoD2 State Ballroom Monday, September 15, 2014, 15:20–16:40 Human-Robot Interaction I / Robot Learning II Chair Alessandro De Luca, Sapienza University of Rome Co-Chair
15:20–15:40 MoD2.1 15:40–15:43 MoD2.2 Keynote: Overview of Motor Interaction A peer pressure experiment: Recreation with Robots and Other Humans of Asch conformity study with robots Etienne Burdet J. Brandstetter,1, P. Racz2, C. Beckner2, E. Imperial College London, UK Sandoval1, J. Hay2, and C. Bartneck1. 1HITLabNZ 2NZILBB • Motor learning: in humans, for • Motor learning: in humans, for robot robot • Question: Can robot peers create conformity via group pressure (Asch 1951)? • A framework to analyze and • Tasks: Visual vs. verbal, ambiguous vs. design interactive control nonambiguous. between humans and robots • In contrast with human peers, robot peers did not prompt conformity in any task. • Sensory mechanism of motor interactions between humans
15:43–15:46 MoD2.3 15:46–15:49 MoD2.4 IRL Algorithms and Features for Robot % Navigation in Crowds "! # "! $ % &! ' ( )! * ( $! ) + )! , # 1,2 1 Dizan Vasquez , Billy Okal # , , $ " - " . % 1 & / & 0 0 and Kai O. Arras ( 1 / 2 -$ + " - 3 0 . 1University of Freiburg, 2Inria Grenoble • • IRL algorithm and feature $%&'() comparison. • • Objective/subjective evaluation metrics. • Open experimental platform: ! • Simulator (PedSim). • Algorithms. • " • Features. ! !
15:49–15:52 MoD2.5 15:52–15:55 MoD2.6 Determining Proper Grasp Using Spatial Language to Drive a Robot for Configurations for Handovers an Indoor Environment Fetch Task Wesley P. Chan, Yohei Kakiuchi, Zhiyu Huo, Tatiana Alexenko, Kei Okada, and Masayuki Inaba and Marjorie Skubic University of Tokyo University of Missouri Columbia • Grasp configuration affects handover • Using natural language to navigate text safety, efficiency, and comfort. a robot for a object fetch task in an • Proper grasp configuration depends indoor environment. on object affordances. • Spatial language grounding model • Learn affordances of everyday and robot behavior model proposed. objects from usage demonstrations. • Simulation Physical indoor • Generalize known handover grasp environment experiment were configurations for new objects based performed. on recognized affordances.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
125 Session MoD2 State Ballroom Monday, September 15, 2014, 15:20–16:40 Human-Robot Interaction I / Robot Learning II Chair Alessandro De Luca, Sapienza University of Rome Co-Chair
15:55–15:58 MoD2.7 15:58–16:01 MoD2.8 Speech-based Human-Robot Interaction Robust to Head-eyes system and gaze analysis Acoustic Reflections in Real Environment of the humanoid robot Romeo 1 1 1 Randy Gomez1, Koji Inoue2, Keisuke Nakamura1, Takeshi N.Pateromichelakis , A.Mazel , M.A.Hache , Mizumoto1 and Kazuhiro Nakadai1 T.Koumpogiannis1, R.Gelin1, 1Honda Research Institute Japan 2Kyoto University B.Maisonnier1 and A.Berthoz2 1Aldebaran Robotics 2Collège de France • Human-robot interaction • Sound source localization 4 DOF in based using video and audio • Robotic head with 4 DOF the eyes modalities Head Pitch • Experimental evaluation in • Eyes mechanism with 4 DOF real reverberant environment Head Roll conditions • Human-like gaze speed Neck Pitch • Robustness to acoustic reflection Neck Yaw
16:01–16:04 MoD2.9 16:04–16:07 MoD2.10 Development of a Rehabilitation Robot Modeling and Controller Design of Suit with Velocity and Torque-based Cooperative Robots in Human-Robot Mechanical Safety Devices Assembly Teams Y. Kai1, S. Kitaguchi1, S. Kanno1, Changliu Liu1, Masayoshi Tomizuka1, W. Zhang2, and M. Tomizuka2 1University of California, Berkeley 1Tokai University 2UC Berkeley Human workers and robots are two major workforces • In this paper, we develop a rehabilitation in modern factories, which are normally separated. It is robot suit with mechanical safety promising if we can combine human’s flexibility and devices to guarantee safety even when robot’s productivity in manufacturing. We investigates the computer fails to operate functionally. the modeling and controller design method in human- robot assembly teams. An integrated method concerning • The safety devices consist of only passive online learning of human behavior and receding horizon components without actuators, controllers, control in a safe set is proposed. Simulation results or batteries. Robot Suit confirm the safety and efficiency of the algorithm.
16:07–16:10 MoD2.11 16:10–16:13 MoD2.12
Adjutant: A Framework for Flexible Human- Efficient Policy Search with a Machine Collaborative Systems Parameterized Skill Memory (PSM) Kelleher Guerin and Gregory D. Hager Department of Computer Science, Johns Hopkins University, USA Felix Reinhart and Jochen Steil Jonathan Bohren CoR-Lab, Bielefeld University Department of Mechanical Engineering, Johns Hopkins University, USA Sebastian Riedel • PSMs organize motion Policy Search Dept. of Informatics, Technische Universitat Munchen, Germany primitives in low-dimensional roll-outs • Adjutant addresses the problem of reusable embedding spaces task information in the context of human robot Low-dimensional collaboration • PSMs link embeddings to Embedding Space • Adjutant introduces robot capabilities - motion primitive parameters reusable actions that can be generalized to novel tasks. and complete trajectories rewards • Capabilities are then mapped to specific user Instructing a robot • Low-dimensional skill PSM interfaces to fully enable task execution capability in Virtual Reality parameterization is beneficial • We demonstrate Adjutant on two real world Trajectory Motion Primitive industrial manufacturing tasks for efficient policy search Parameters
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
126 Session MoD2 State Ballroom Monday, September 15, 2014, 15:20–16:40 Human-Robot Interaction I / Robot Learning II Chair Alessandro De Luca, Sapienza University of Rome Co-Chair
16:13–16:16 MoD2.13 16:16–16:19 MoD2.14 Simultaneous On-line Discovery and Dimensionality Reduction and Motion Improvement of Robotic Skill Options Coordination in Learning with Dynamic Freek Stulp12, Laura Herlant3, Movement Primitives Antoine Hoarau12, and Gennaro Raiola1 Adrià Colomé1 and Carme Torras1, 1ENSTA-ParisTech 2INRIA 3CMU 1Inst. de Robòtica i Inf. Ind., CSIC-UPC, Spain • Key idea: Learn skill options for task • Reinforcement Learning with DMP variations autonomously and on-line may involve too many parameters • Cluster costs in learning curves, and and DoF to be of practical use. make new skill options for variations • We propose 3 speed-up strategies: • Optimize all skill options in parallel – detect unnecessary parameters with policy improvement – establish layers of parameters • Evaluation in simulation and on – automatically find couplings Meka humanoid with ball-in-cup task between joints
16:19–16:22 MoD2.15 16:22–16:25 MoD2.16
OrigamiBot-I: A Thread-Actuated Origami Robot Decoding sEMG into dynamic state to for Manipulation and Locomotion extract dynamic motor control strategy
Evan Vander Hoff, Donghwa Jeong, and Kiju Lee Seongsik Park1, Wan Kyun Chung1 Department of Mechanical and Aerospace Engineering, 1 Case Western Reserve University, USA POSTECH
• The OrigamiBot-I is developed based on an • Propose a method of decoding sEMG into the dynamic origami design called “twisted tower” state to extract dynamic motor control strategy • The kinematics for each twisting and bending motions is derived based on estimated • Dynamic state established in the augmented space parameters. characterizes the dynamic motor control of human • Stiffness and durability tests are performed to validate the paper-based structure as a robotic • Decoding result only from sEMG showed each dynamic manipulator and worm-like crawling robot. motion consisting of 2~4 states temporally • Physical demonstrations such as robotic manipulation and locomotion are provided. • Also, it can distinguish the difference of the temporal patterns of the state according to its speed of motion
16:25–16:28 MoD2.17 16:28–16:31 MoD2.18 Latent Space Policy Search Learning of Closed-Loop for Robotics Motion Control Kevin Sebastian Luck1, Gerhard Neumann1, Farbod Farshidian1, Michael Neunert1 Erik Berger2, Jan Peters1 and Heni Ben Amor3 and Jonas Buchli1 1TU Darmstadt 2TU Freiberg 3Georgia Tech 1ETH Zurich, Switzerland • PePPEr is a novel algorithm for • Simultaneous derivation of policy search in low-dimensional reference trajectory and latent spaces controller • Merges dimensionality reduction • Two-step design process: and reinforcement learning 1) Model-based approach leverages system • Experiments were done with a model knowledge NAO robot that learned to stand 2) Reinforcement learning method refines controller on one leg based on samples derived from real system
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
127 Session MoD2 State Ballroom Monday, September 15, 2014, 15:20–16:40 Human-Robot Interaction I / Robot Learning II Chair Alessandro De Luca, Sapienza University of Rome Co-Chair
16:31–16:34 MoD2.19 16:34–16:37 MoD2.20
Unsupervised Learning Approach to Attention-Path Planning Automatic Channel Selection and Neural Signal for Large-scale Environment Classification Estimation across Channels of Neural Probes Olga Vysotska1,2, Barbara Frank1, Istvan Ulbert3, Oliver Paul1, Hosun Lee1, Sungmoon Jeong1 and Nak Young Chong1 Patrick Ruther1, Cyrill Stachniss2, Wolfram Burgard1 1Japan Advanced Institute of Science and Technology 1University of Freiburg 2University of Bonn 3University of Budapest
• Visual attention planning for unknown area • Autonomous channel selection foforr Circuitry classification. high-resolution microprobes contact • Unsupervised sequential feature selection to • Gaussian process regression Electrode recursively plan the fixation and update the prior for predicting neural signals knowledge based on recorded neighboring sites • A near-optimal solution to the classification with • Greedy channel selection that aims at adaptive submodular optimization minimizing the overall prediction error • Demonstrated the effectiveness of the proposed • Evaluations on real neural data provide framework through large area classification under small field-of-view conditions Attention-Path Planning accurate results close to optimal solutionn Predicted neural signal
16:37–16:40 MoD2.21 Fast Planning of Well Conditioned Trajectories for Model Learning Cong Wang, Yu Zhao, Chung-Yen Lin, and Masayoshi Tomizuka University of California, Berkeley • An efficient procedure to generate well conditioned data for model learning in the feature space • Using low-discrepancy sequences and matrix subset selection • Can be applied to various problems with little ad hoc formulation • Does not require an initial design
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
128 Session MoD3 Red Lacquer Room Monday, September 15, 2014, 15:20–16:40 Formal Methods / Software and Architecture Chair Jana Tumova, Royal Institute of Technology Co-Chair
15:20–15:40 MoD3.1 15:40–15:43 MoD3.2
A Compositional Approach to Stochastic Optimal Keynote: Formal methods in robotics Control with Co-safe Temporal Logic Specifications George J. Pappas Matanya B. Horowitz, Eric M. Wolff, University of Pennsylvania Richard M. Murray California Institute of Technology • Formal task description logics for • Solve temporal logic planning DARPA Challenge like missions optional image problems using stochastic optimal • Provable translation of high control methods level symbolic tasks to low any text in the level real-time control image should • Complex tasks solved by efficient composition of reachability problems • Powerful computational tools for be the same plan generation and controller size as main • Linear Hamilton-Jacobi-Bellman Temporal solutions compositions text equation allows for composition via superposition via composition
15:43–15:46 MoD3.3 15:46–15:49 MoD3.4
Formal Verification of Maneuver Automata for How Behavior Trees Modularize Parameterized Motion Primitives Robustness and Safety in Hybrid Systems Daniel Heß1, Matthias Althoff2,Thomas Sattel1 1TU Ilmenau, Germany 2TU München, Germany Michele Colledanchise and Petter Ögren KTH -The Royal Institute of Technology • Formal verification of planned motions using reachability • Behavior Trees (BTs) make analysis hybrid systems modular. • Computations are • We study safety and mostly performed robustness of BT module offline, resulting in a compositions. fast online approach
15:49–15:52 MoD3.5 15:52–15:55 MoD3.6 Verification and testing of mobile robot Verifying and Validating navigation algorithms with SPARK Multirobot Missions Damian Lyons1, Ronald Arkin2, Piotr Trojanek, Kerstin Eder Shu Jiang2, Dagan Harrington1 & Tsung-Ming Liu1 University of Bristol 1Fordham Univ. NY, 2Georgia Tech. GA • Three open-source implementations of navigation • Formal process algebra method algorithms translated from C/C++ to SPARK – to verify performance guarantees a formally defined programming language for autonomous, behavior-based • Code annotated with pre- and postconditions multirobot mission software. • Bugs automatically detected by run-time checks • Predicted results successfully • Run-time safety can be proven automatically validated in multiple trials of bounding overwatch mission with • Conclusion: SPARK is as fast as C/C++ and is much a range of performance criteria easier to test and verify values.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
129 Session MoD3 Red Lacquer Room Monday, September 15, 2014, 15:20–16:40 Formal Methods / Software and Architecture Chair Jana Tumova, Royal Institute of Technology Co-Chair
15:55–15:58 MoD3.7 15:58–16:01 MoD3.8 Maximally Satisfying Optimal and Dynamic Planning for MDPs LTL Action Planning with Co-Safe LTL Specifications Jana Tumova, Alejandro Marzinotto, Bruno Lacerda, David Parker and Nick Hawes Dimos V. Dimarogonas and Danica Kragic School of Computer Science Royal Institute of Technology (KTH) University of Birmingham, United Kingdom • Problem: Planning under linear • Generation of cost-optimal policies temporal logic task with reactivity to for MDPs, with goals stated in the task infeasibility caused by the co-safe LTL robot’s action execution failures • Re-planning mechanism allows for • Solution: Maximally satisfying plan addition of tasks during execution synthesis and its implementation • Application example to motion through a behavior tree planning of a mobile service robot • Experiments: NAO humanoid
16:01–16:04 MoD3.9 16:04–16:07 MoD3.10 SafeRobots: A Model-Driven Framework Automated Composition of Motion for Developing Robotic Systems Primitives for Multi-Robot Systems from Arunkumar Ramaswamy12, Bruno Monsuez1, Safe LTL Specifications and Adriana Tapus1 I. Saha1,2, R. Ramaithitima2, 1ENSTA-ParisTech, 2Vedecom Institute, France V. Kumar2, G. J. Pappas2, S. A. Seshia1 •The core concepts behind our 1UC Berkeley, 2UPenn framework: Self Adaptive • Path planning problem for a group Problem Instance Framework for Robotic of robots with complex dynamics Systems (SafeRobots) is and complex specification Constraint Generator presented • Reduced to an SMT solving problem •System integration and Constraints knowledge representation • Decision variables represent the issues that are common in motion primitives SMT Solver robotic software development • Optimal trajectories for 4 UAVs are addressed. found in a few minutes Trajectory
16:07–16:10 MoD3.11 16:10–16:13 MoD3.12 A Stable Switched-System Approach to eTaSL/eTC: A constraint-based Task Obstacle Avoidance for Mobile Robots in SE(2) Specif. Language and Robot Controller Jingfu Jin and Nicholas Gans Erwin Aertbeliën1, Joris De Schutter1 The University of Texas at Dallas, USA • We divide the configuration space 1 KU Leuven – Dep. Of Mech. Eng. into two sub-regions on SE(2). • A language (eTaSL) for constraint-based • The switching signal is based on task specification of robot controllers. the robot position and orientation. • Flexible and composable, using: • Two switching signals are • Using expression graphs proposed to investigate chattering. • Using feature variables • Lyapunov analysis proves the robot will converge to goal pose. The avoidance region, which • Controller implementation (eTC) that depends on the distance and realizes specifications written in eTaSL. • Multiple simulations and the relative angle between a experiments are conducted robot and an obstacle. • Demonstrated with bi-manual task on PR2.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
130 Session MoD3 Red Lacquer Room Monday, September 15, 2014, 15:20–16:40 Formal Methods / Software and Architecture Chair Jana Tumova, Royal Institute of Technology Co-Chair
16:13–16:16 MoD3.13 16:16–16:19 MoD3.14 Enhancing software module reusability Robot Task Commander using port plug-ins (an experiment with the iCub robot) 1 2 S. Hart , P. Dinh , Ali Paikan1, Vadim Tikhanoff1, Giorgio Metta1 3 2 4 J.D. Yamokoski , B. Wightman , and N. Radford and Lorenzo Natale1 1 2 3 4 G.M. IHMC Oceaneering NASA-JSC 1Istituto Italiano di Tecnologia (IIT) • A novel framework & IDE for robot • Application–dependent functionalities application development are implemented using a scripting • Integrates distributed computational language and plugged into the ports nodes & control FSMs of components. • Usable by experts & non-experts • Port monitoring, data filtering and • Facilitates hierarchical composition arbitration & re-use of applications to different • Promoting simpler and more robots and different contexts reusable components
16:19–16:22 MoD3.15 16:22–16:25 MoD3.16 Simple Concurrency for Robotics A lightweight, cross-platform, multiuser with the Roboscoop Framework robot visualization using the cloud Andrey Rusakov, Jiwon Shin, Bertrand Meyer William Hilton1, Daniel M. Lofaro2 Chair of Software Engineering and Youngmoo Kim1 ETH Zürich, Switzerland 1Drexel University 2George Mason University Roboscoop: concurrent robotics framework: • Cloud based robot monitoring • Robotics library • Runs through a standard browser • Easy creation and coordination • No third-party software required of robotic tasks • Supported/Tested Systems: • Simple and safe concurrency Mobile - Android and iOS; • Easy translation of behaviors into code Computer - Mac, Linux, Windows • Support for external libraries and Cloud - Public and Private frameworks Monitor in Browser
16:25–16:28 MoD3.17 16:28–16:31 MoD3.18
RrFrESH: A Self-Adaptation Framework Speeding Up Rao-Blackwellized Particle Filter to Support Fault Tolerance in Robots SLAM with a Multithreaded Architecture 1 1 Yanzhe Cui , Richard Voyles , Bruno D. Gouveia, David Portugal and Lino Marques Joshua Lane1 and Mohammad Mahoor2 Insitute of Systems and Robotics, University of Coimbra, Portugal 1Purdue University 2University of Denver • Explore multiprocessor computer • Provision of fault detection and mitigation infrastructure architectures to solve the SLAM problem. support; • Multithreading was used to parallelize a • Built into the Port-Based Object real time operating Rao-Blackwellized Particle Filter (RBPF) approach. system; • Gain in efficiency enables to raise the • Management of task performance in the presence of number of particles, yielding higher localization precision and map accuracy. unexpected uncertainties; • Frequently used datasets in the Robotics • Provision of self-adaptation support for software and community validate our results. hardware functionality.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
131 Session MoD3 Red Lacquer Room Monday, September 15, 2014, 15:20–16:40 Formal Methods / Software and Architecture Chair Jana Tumova, Royal Institute of Technology Co-Chair
16:31–16:34 MoD3.19 16:34–16:37 MoD3.20 Developing Virtual Testbeds for Crowdsourcing as a methodology to Intelligent Robot Manipulators obtain large and varied robotic data sets Eric G. Kaigom, Jürgen Roßmann Guido de Croon1,2, Paul K. Gerke1,3, and Ida RWTH-Aachen University, Sprinkhuizen-Kuyper3 Institute for Man-Machine-Interaction 1European Space Agency 2TU Delft 3RUN • eRobotics lays the foundation for • First scientific crowdsourcing experiment involving real • cross-cutting, versatile multi-body robots. See: http://www.astrodrone.org/ systems simulation and control • holistic 3D simulation of robots endowed with compliance control • in-depth assessment of robots down to actuation Simulation of an • control by 3D simulation interaction maneuver
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
132 Session TuA1 Grand Ballroom Tuesday, September 16, 2014, 09:00–10:20 Manipulation and Grasping III / Parallel Robotics Chair Eugenio Guglielmelli, Universita' Campus Bio-Medico Co-Chair
09:00–09:20 TuA1.1 09:20–09:23 TuA1.2 Keynote: Grasping and Manipulation Characterization of the Precision Manipulation by Humans and by Robots Capabilities of Robot Hands via the Continuous Group of Displacements Oliver Brock Technische Universität Berlin Nicolas Rojas and Aaron M. Dollar Yale University • The manipulation performance of Precision manipulation: repositioning of a grasped robots is nowhere near that of object without breaking or changing contact humans • A method to characterize the precision • A comparison of human and robot manipulation capabilities of a robot manipulation reveals important hand regardless of the particularities and fundamental differences of the grasped object is presented • These differences should drive • The approach is general and can be robot hand design, manipulation applied to any finger/palm layout or planning, and perception subset of it
09:23–09:26 TuA1.3 09:26–09:29 TuA1.4 Encoderless Robot Motion Control Humanoid compliant whole arm dexterous using Vision Sensor manipulation: Control design and experiments and Back Electromotive Force M. Florek-Jasinska1,2, T. Wimboeck2 and Ch. Ott2
Akihiro Kawamura, Miyako Tachibana, 1AGH, Poland 2Inst. of Rob. and Mech., DLR Soichiro Yamate, Sadao Kawamura Ritsumeikan University, JAPAN • Use structural parts of the body to • A robotic arm system without support the grasp encoders that achieve precise • impedance controller on object level motion control is proposed. including contacts on the (passive) • Joint angles are calculated robot chest of a two-armed robot from estimation using back system electromotive force of motors. • Object frame at passive contact • The system allows errors on • Dexterous object manipulation camera and robot calibrations.
09:29–09:32 TuA1.5 09:32–09:35 TuA1.6
Analyzing Human Fingertip Usage in Dexterous Precision Adaptive Underactuated Anthropomorphic Manipulation: Implications for Robotic Finger Design Hand: ISR-SoftHand Ian M. Bullock1, Thomas Feix1, Mahmoud Tavakoli,Anibal T. de Almeida and Aaron M. Dollar1 Institute of Systems and Robotics, University of Coimbra, Portugal 1Yale University, New Haven, CT USA •Compliant joints: Adaptive Grasps- Adaptive Synergies • Finger surface use during manipulation rarely studied •Tendon based actuation of all fingers- 3 Actuators • Sphere manipulated in •Under 500$ (3D Printed Parts, Actuators, Drivers, etc.) fingertips by 19 participants •Natural Looking • Frequent human lateral •Achieves top 10 grasps with highest usage frequency surface use suggests robotic •frequency of usage by humans, with only three actuators fingertips which can be used on their sides could enhance robotic manipulation capability
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
133 Session TuA1 Grand Ballroom Tuesday, September 16, 2014, 09:00–10:20 Manipulation and Grasping III / Parallel Robotics Chair Eugenio Guglielmelli, Universita' Campus Bio-Medico Co-Chair
09:35–09:38 TuA1.7 09:38–09:41 TuA1.8 Coordinated Motion Control of A Hierarchical Fingertip Space for Nonholonomic Mobile Manipulator for Multi-fingered Precision Grasping Accurate Motion Tracking Kaiyu Hang, Johannes A. Stork and Danica Kragic Yunyi Jia, Ning Xi, Yu Cheng and Siyang Liang Centre for Autonomous Systems/CVAP, Electrical and Computer Engineering Department KTH Royal Institute of Technology, Sweden Michigan State University, East Lansing, USA • Fingertip Space: an integrated • Accurate motion control of the image representation considering nonholonomic mobile manipulator both object geometry and by considering the differences any text in the fingertip shape. between the mobile platform and the image should manipulator • A hierarchy of the Fingertip be the same Space for multilevel refinement • Adaptive motion distribution and size as main of grasps allowing for an coordination design between the text efficient search of stable mobile platform and the manipulator grasps.
09:41–09:44 TuA1.9 09:44–09:47 TuA1.10 Modeling of Skid-Steer Mobile Physically-Consistent Sensor Fusion in Manipulator and Experimental Validation Contact-Rich Behaviors S. Aguilera1, M. Torres-Torriti1 and F. Auat2 Kendall Lowrey1, Svetoslav Kolev1, Yuval Tassa1, 1Pontificia Universidad Católica de Chile Tom Erez1, Emanuel Todorov1 2Universidad Técnica Federico Santa María 1University of Washington • Skid-Steer mobile manipulator • Combining fixed-lag smoothing and model through spatial vector recursive estimation makes for a algebra. computationally expensive but • Arm-vehicle and vehicle-ground accurate robot state estimator dynamic interaction. without over-fitting. • Experimental verification using Cat® • A physics engine makes 262C compact-skid steer loader. accelerations and inferred contact forces physically consistent.
09:47–09:50 TuA1.11 09:50–09:53 TuA1.12 A Real-Time Distributed Architecture A New Extension of DCAL and its Real- for Large-Scale Tactile Sensing Time Application to RA-PKMs Emanuele Baglini1, Shahbaz Youssefi1, Moussab Bennehar, Ahmed Chemori and Fulvio Mastrogiovanni1 and Giorgio Cannata1 François Pierrot 1University of Genova, Italy LIRMM, Univ. Montpellier 2 - CNRS, France • A real-time EtherCAT-based • An Extended DCAL controller is networking infrastructure for large developed. scale tactile systems • Static feedback gains in DCAL are • Both theoretical and experimental replaced by nonlinear ones. analyses are carried out • This solution allows to achieve • We show real-time performance in a better tracking performance. network of distributed computational • Experiments on Dual-V show the nodes, each one managing a skin relevance of the contribution. Dual-V RA-PKM patch 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
134 Session TuA1 Grand Ballroom Tuesday, September 16, 2014, 09:00–10:20 Manipulation and Grasping III / Parallel Robotics Chair Eugenio Guglielmelli, Universita' Campus Bio-Medico Co-Chair
09:53–09:56 TuA1.13 09:56–09:59 TuA1.14 Study of Reconfigurable Suspended Cable- Structural Synthesis of Dexterous Hands Driven Parallel Robots for Airplane Maintenance Dinh Quan Nguyen1, Marc Gouttefarde1, Erol Özgür, Grigore Gogu, Youcef Mezouar 1Laboratoire d'Informatique, de Robotique et de Micro-électronique de Pascal Institute / IFMA Montpellier (LIRMM), CNRS - University of Montpellier 2, France
• Reconfigurable suspended CDPRs r r2 3 to replace telescopic platforms that
• Adapting the theory of structural r1 carry workers in airplane workshop r4
synthesis of parallel robots to thee r r6 • Systematic procedure to solve the 5 dexterous hands. CDPR reconfiguration as a multi- " ! objective optimization problem • Synthesis of dexterous hands withith • Two criteria are used to quantify desired mobility, connectivity, the CDPR performance in terms of overconstraint and redundancy. power consumption and stiffness
09:59–10:02 TuA1.15 10:02–10:05 TuA1.16 Workspace Analysis of Two Similar 3-DOF Improvement of the DKM of a haptic Axis-Symmetric Parallel Manipulators device for medical application in real Kristan Marlow, Mats Isaksson, time using an extra sensor Hamid Abdi and Saeid Nahavandi Houssem Saafi, Med Amine Laribi and Saïd Deakin University, Australia Zeghloul • This paper analyses two similar Pprime Institute, Poitiers France 3-DOF axis-symmetric parallel • An extra sensor is added in a manipulators. passive joint of a spherical parallel Extra • It presents an analysis of the manipulator (SPM) to simplify the sensor manipulators’ workspace calculation of the Direct kinematic properties, highlighting the model (DKM). locations and types of singularities. • This SPM will be used as a master Followed by an exanimation of workspace size and device for a medical tele-operation conditioning. system.
10:05–10:08 TuA1.17 10:08–10:11 TuA1.18
Switching Strategy for Flexible Task Execution using Vibration Control of 3P(S)4 Class Parallel Mechanisms for the Cooperative Dual Task-Space Framework High Speed Applications Using Quantitative Feedback Design
L.F.C. Figueredo1,3, B.V. Adorno2, J.Y. Ishihara3, and G.A. Borges3 Ebubekir Avci1, Masanori Kenmochi1, Michihiro Kawanishi1, 1Massachusetts Institute of Technology (MIT) 2Federal University Tatsuo Narikiyo, Shinji Kawakami2 and Yumi Saitou2 of Minas Gerais (UFMG) 3University of Brasilia (UnB) 1TTI, 2Omron Corporation
• New strategy for cooperative dual task-space manipulation • Residual vibration is the challenge framework. for the high speed parallel • Flexible task execution mechanisms. enriches the Jacobian null space with additional degrees of freedom • By using Lagrangian formulation, by relaxing control requirements inverse dynamics of the system is upon specific geometric task derived. objectives. • Quantitative Feedback Theory (QFT) • Hysteresis-based switching strategy ensures stability and is applied for the reduction of the convergence vibration as a robust control method. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
135 Session TuA1 Grand Ballroom Tuesday, September 16, 2014, 09:00–10:20 Manipulation and Grasping III / Parallel Robotics Chair Eugenio Guglielmelli, Universita' Campus Bio-Medico Co-Chair
10:11–10:14 TuA1.19 10:14–10:17 TuA1.20 Dimensional Synthesis of 4 DoFs (3T-1R) Actuatedly Active vibration canceling of a cable-driven Redundant Parallel Manipulator Based on Dual Criteria: Dynamics and Precision parallel robot using reaction wheels 1,2 2 2 S. SHAYYA , S. KRUT , O. COMPANY , C. Xavier Weber1, Loic Cuvillon1 BARADAT1, and F. PIERROT2 and Jacques Gangloff1 1Tecnalia France 2LIRMM-Université Montpellier 2- 1 France University of Strasbourg, Icube Laboratory • Presents Dimensional Synthesis of • Rapid prototyping of CDPR Redundant 4 dofs (3T-1R) PKM Z Lego Mindstorms, Raspberry Pi • Synthesis Based on Dynamic and Precision Criteria: Isotropic Linear and Simulink Coder Acceleration and Translational Resolution Amplification Factor • Active vibration damping (4 DoF) • Other Kinetostatic & Dynamic Measures are also evaluated for synthesized Z Robotized platform parameters... Z Embedded reaction wheels • Results show a highly performant PKM
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
136 Session TuA2 State Ballroom Tuesday, September 16, 2014, 09:00–10:20 Motion and Path Planning II / Localization and Mapping II Chair Steven M LaValle, Oculus VR Co-Chair
09:00–09:20 TuA2.1 09:20–09:23 TuA2.2 Keynote: Sampling-Based Planning: Proactive kinodynamic planning using the Foundations & Applications extended social force model and human Nancy M. Amato motion prediction in urban environments Texas A&M University Gonzalo Ferrer1, Alberto Sanfeliu1 1IRI (CSIC-UPC), Barcelona, Spain • Sampling-Based methods have dominated motion planning for • Autonomous navigation in dynamic nearly two decades urban environments. • Foundations: practically and often • Proactive: every robot propagation provably efficient and even optimal entails a prediction of the scene. • Applications: many & varied • Human motion prediction integrated ranging from robots, to CAD, to in the planning scheme. animation, to molecules • Kinodynamic robot constraints and strong time restrictions.
09:23–09:26 TuA2.3 09:26–09:29 TuA2.4 Recursive Non-Uniform Coverage of Unknown Terrains for UAVs Seyed Abbas Sadat, Jens Wawerla Richard Vaughan Autonomy Lab, Simon Fraser University ! " # $ • We use a coverage tree structure that can accommodate non-uniform % & &$ coverage of regions in the target area. ' (&)*%( • Three strategies are proposed to *( $ traverse the coverage tree. ' + # $ • In some situations our method can #$ cover the interesting regions with about ' ,& half the travel time of a naive regular &$ &, `lawnmower' coverage pattern.
09:29–09:32 TuA2.5 09:32–09:35 TuA2.6
Path Planning with Stability Uncertainty for Articulated Mobile Closed-Loop Global Motion Planning for Vehicles in Challenging Environments Reactive Execution of Learned Tasks M.Norouzi1, J. Valls Miro1, Chris Bowen and Ron Alterovitz G. Dissanayake1 and T. Vidal-Calleja1 University of North Carolina at Chapel Hill 1University of Technology, Sydney, Australia • A novel probabilistic tip-over • Problem: perform a learned task while stability criterion avoiding obstacles and reacting to the • Considers uncertainty in the movement of task-relevant objects localisation, the robot model • Sampling-based motion planner and the 3D terrain model maximizes similarity to demonstrations • Generates a dynamic safety • React to object movement in a global, constraint asymptotically optimal manner • Stable paths in rough terrains • Real-time replanning on Baxter robot
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
137 Session TuA2 State Ballroom Tuesday, September 16, 2014, 09:00–10:20 Motion and Path Planning II / Localization and Mapping II Chair Steven M LaValle, Oculus VR Co-Chair
09:35–09:38 TuA2.7 09:38–09:41 TuA2.8 An Empirical Study of The Lion and Man Game on Polyhedral Optimal Motion Planning Surfaces with Boundary
Jingru Luo, Kris Hauser Narges Noori, Volkan Isler Indiana University Bloomington University of Minnesota • Systematic benchmarking study • Sampling-based vs grid search vs • We study pursuit-evasion on trajectory optimization piecewise linear 2D surfaces. • Benchmarks vary dimensionality, • Players have the same speed. # homotopy classes, narrow They see each other at all times. passage geometry • Some surprising results • Our result: Three pursuers can capture the evader on • Recommendations made for surfaces that are homeomorphic to a disk with holes. future planning research Four Benchmark Problems • Such surfaces include terrains with holes (see figure).
09:41–09:44 TuA2.9 09:44–09:47 TuA2.10 Motion Planning under Uncertainty for A Sampling-Based Algorithm for Multi-Robot Medical Needle Steering Using Visibility-Based Pursuit-Evasion Optimization in Belief Space Nicholas M. Stiffler and Jason M. O'Kane Wen Sun, Ron Alterovitz, Computer Science and Engineering, University of South Carolina, USA University of North Carolina at Chapel Hill, USA • Goal is to compute a joint solution • New optimization-based motion strategy for the pursuers. planner for steerable needles explicitly considers uncertainty. • Introduce a graph that maintains a representation of the reachable • Formulate problem as POMDP. parts of the pursuers' joint I-space. • Solve POMDP by optimizing plan in • Utilizes an abstract sampler needle’s belief space. A locally generates points in the pursuers' A pursuer strategy • Our method outputs a locally optimal motion joint configuration space. generated by our algorithm. optimal plan and associated control plan in a liver • Probabilistically complete policy. 09:47–09:50 TuA2.11 09:50–09:53 TuA2.12 Online Learning of Task-Specific Towards Consistent Reconstructions of Dynamics for Periodic Tasks Indoor Spaces Based on 6D RGB-D Tadej Petrič, Andrej Gams, Leon Žlajpah and Odometry and Kinect Fusion Aleš Ude H. Dong1, N. Figueroa2 and A. El Saddik1 Jožef Stefan Institute (JSI), Ljubljana, Slovenia 1University of Ottawa 2EPFL • On-line learning of task-specific • A robust 6D RGB-D odometry dynamics with Dynamic Torque algorithm was proposed; Primitives (DTPs). • KinectFusion algorithm was improved • High tracking accuracy and by combining it with our proposed compliant behavior. odometry estimation; • Safe for interaction with • The proposed approach was humans. evaluated by publicly available RGB- • Demonstrated on crank turning. D benchmark datasets.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
138 Session TuA2 State Ballroom Tuesday, September 16, 2014, 09:00–10:20 Motion and Path Planning II / Localization and Mapping II Chair Steven M LaValle, Oculus VR Co-Chair
09:53–09:56 TuA2.13 09:56–09:59 TuA2.14 Biologically Inspired SLAM Point Cloud Registration using Using Wi-Fi Congruent Pyramids 1 2 Rafael Berkvens , Adam Jacobson , Michael Aravindhan K Krishnan, Srikanth Saripalli 2 1 1 Milford , Herbert Peremans and Maarten Weyn Arizona State University 1UAntwerp 2QUT • Idea : Find congruent structures We leverage the low quality sensory in the Point Clouds requirements and coarse metric properties of RatSLAM to localize • We find congruent pyramids using Wi-Fi fingerprints. We present a based on the properties of a novel sensor fusion technique that rigid body transformation integrates camera and Wi-Fi, and we • Initial alignment is computed show the use of compass sensor from the corresponding points data to remove orientation drift. of the congruent pyramids, which is then refined using ICP
09:59–10:02 TuA2.15 10:02–10:05 TuA2.16 On the formulation, performance and design Handling Perceptual Clutter for Robot Vision choices of Cost-Curve Occupancy Grids with Partial Model Based Interpretations Martim Brandao1, Ricardo Ferreira2, Grace Tsai and Benjamin Kuipers, Kenji Hashimoto1, Jose Santos-Victor2 and Atsuo Electrical Engineering and Computer Science, Takanishi1 1Waseda University 2IST, ULisboa University of Michigan, Ann Arbor Interpret indoor scene by a planar model + clutter • Occupancy grid formulation for stereo Present likelihood function to address 3-way trade-off • Uses likelihood model of all costs along the cost-curve among coverage, accuracy, and simplicity of the model • Evaluation of different likelihood models in different noise conditions • High precision, decreases with power of image noise
10:05–10:08 TuA2.17 10:08–10:11 TuA2.18 Modeling motion patterns of Fast Hybrid Relocation in Large Scale dynamic objects by IOHMM Metric-Topologic-Semantic Map Zhan Wang, Rares Ambrus, Romain Drouilly1,2 , Patrick Rives1, Patric Jensfelt and John Folkesson Benoit Morisset2 KTH Royal Institute of Technology 1INRIA Méditerranée, France 2ECA Robotics • New structured hybrid map model to Corridor speed up localization Bathroom Elevator Kitchen • Fast content request • Modeling motion patterns by capturing spatial through semantic correlation across IOHMM processes corresponding to graphs comparison different occupancy grids • High-level content • Improving each IOHMM process by incorporating request ability external information from neighboring IOHMMs
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
139 Session TuA2 State Ballroom Tuesday, September 16, 2014, 09:00–10:20 Motion and Path Planning II / Localization and Mapping II Chair Steven M LaValle, Oculus VR Co-Chair
10:11–10:14 TuA2.19 10:14–10:17 TuA2.20 Stereo-Vision Based Obstacle Mapping Meta-rooms: Building and Maintaining Long for Indoor/Outdoor SLAM Term Spatial Models in a Dynamic World Christoph Brand, Martin J. Schuster, Rares Ambrus1, Nils Bore1, Heiko Hirschmüller and Michael Suppa John Folkesson1 and Patric Jensfelt1 German Aerospace Center (DLR) 1KTH Royal Institute of Technology • Meta-rooms – local maps image representing the static structure of • Fast local obstacle mapping the environment; built incrementally any text in the • Adaptive to stereo error through a stable and convergent image should • Detection of negative edges method in long-term autonomy be the same • Integration in SLAM framework scenarios size as main Meta-rooms • 0.08% final position error text • Used to extract dynamic objects and dynamic which can be matched across objects observations
10:17–10:20 TuA2.21 Sponsor Talk: BRIN: Benchmark for Robotic Indoor Navigation Gershon Parent Microsoft Robotics • BRIN is an experimental protocol and tools for evaluating a mobile robot navigation system deployed in a real indoor environment. • BRIN provides detailed specifications and controls of the interactions and environment dynamics to ensure repeatability and reproducibility of experiments. • BRIN includes the use of a reference robot to allow comparison between different navigation systems at different experimentation sites.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
140 Session TuA3 Red Lacquer Room Tuesday, September 16, 2014, 09:00–10:20 Search, Rescue, and Audition / Field Robotics Chair Satoshi Tadokoro, Tohoku University Co-Chair
09:00–09:20 TuA3.1 09:20–09:23 TuA3.2 Keynote: Lessons Learned in Field The Response Robotics Robotics from Disasters Summer School 2013 Robin R. Murphy R. Sheh1,2,3, B. Collidge4, M. Lazarescu1, Texas A&M University H. Komsuoglu2,3 and A. Jacoff2 1Curtin University 2NIST 3Robolit 4WA Police • Data from field work differs • Co-located with Bomb Response Technology Seminar, from laboratory in terms of # bringing Responders and Researchers Together to authenticity, quantitative # " Advance Response Robotics measurability, and
#
! • Leveraged DHS-NIST-ASTM
!
#
repeatability "
International Standard Test Methods
• Helpful data: log of activity, for Response Robots as a common context, robot’s eye, robot ! language state, external view of robot, human-robot interaction • Disseminated Best-in-Class capabilities from RoboCup Rescue
09:23–09:26 TuA3.3 09:26–09:29 TuA3.4 Design of a Hybrid Exploration Robot for Approaches to Robotic Teleoperation in Air and Land Deployment (H.E.R.A.L.D) a Disaster Scenario K. Katyal, C. Brown, S. Hechtman, M. Para, T. McGee, Stella Latscha, M. Kofron, A. Stroffolino, K. Wolfe, R. Murphy, M. Kutzer, E. Tunstel, M. L. Davis, G. Merritt, M. Piccoli and M. Yim McLoughlin, M. Johannes University of Pennsylvania Johns Hopkins University Applied Physics Laboratory • Bimanual anthropomorphic • Joint system with two "snake" manipulation system robots and one quadrotor • 41 Total DOF • Combines snake cluttered • ROS-based perception and environment access with aerial path planning modules surveillance and mobility • Supervised autonomous • Potential for rapid USAR site manipulation capabilities in a exploration and victim location casualty evacuation scenario
09:29–09:32 TuA3.5 09:32–09:35 TuA3.6
Remote Vertical Exploration By Active Estimation of Ground Surface Radiation Sources from Scope Camera into Collapsed Buildings Dose Map Measured by Moving Dosimeter and 3D Map Junichi Fukuda1, Masashi Konyo1, Gaku Minamoto1,Eijiro Takeuchi1 Eijiro Takeuchi1 and Satoshi Tadokoro1 and Satoshi Tadokoro1 1Tohoku University 1Tohoku University • We developed the prototype of remote • Proposed method estimates vertical exploration system for collapsed intensities of sources from air buildings with Active Scope Camera (ASC). dose measured by moving • We confirmed this system had high dosimeters. 3-D map Air dose potential to get inserted in the deep area ASC • The estimation is based on MAP by experiments at the simulated probabilistic approach. collapsed building constructed with • Experiments in real temporary scaffolds of 6 m height. environments were conducted. Source map 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
141 Session TuA3 Red Lacquer Room Tuesday, September 16, 2014, 09:00–10:20 Search, Rescue, and Audition / Field Robotics Chair Satoshi Tadokoro, Tohoku University Co-Chair
09:35–09:38 TuA3.7 09:38–09:41 TuA3.8 Making a Robot Dance to Diverse Improvement in Outdoor Sound Source Detection Musical Genre in Noisy Environments Using a Quadrotor-Embedded Microphone Array Takuma Ohata1,Keisuke Nakamura2,Takeshi J. Oliveira1, K. Nakamura2, T. Langlois3, F. Gouyon4, Mizumoto2,Tezuka Taiki1,and Kazuhiro Nakadai1,2 2 5 1,6 5 K. Nakadai , A. Lim , L. Reis , H. Okuno 1Tokyo Institure of Technology 1 2 3 4 5 6 FEUP Honda ULisbon TEC Kyoto U UMinho 2Honda Research Institute Japan Co., Ltd. • Two state-of-the-art algorithms Proposed iGSVD-MUSIC with CMS • Six musical genres •Low computational cost • Multiple audio sources, including •High noise-robustness due to music and speech soft-whitening • Multiple noise sources •Achieved outdoor speech detected utterances • Improved genre recognition, by localization and detection with a 43.6 pp, when considering noisy 16ch quadrotor-embedded acoustic models microphone array time Direction
09:41–09:44 TuA3.9 09:44–09:47 TuA3.10 # Rapidly Learning Beats in the Presence of Environmental and Robot Ego Noise 1 1 Takahiro Iyama1, Osamu Sugiyama1, David Grunberg and Youngmoo Kim , Takuma Otsuka1, Katsutoshi Itoyama1, and Hiroshi G. Okuno1 1Department of Electrical & Computer 1Graduate School of Informatics, Kyoto University, Japan Engineering, Drexel University • We designed and developed # for auditory awareness • We enabled a robot to learn musical • beats given only 5 seconds of audio - Visualize MUSIC spectrum on RGB Image • Stacked spectrograms compactly • represent time-varying spectral - Visualize MUSIC spectrum on the clustered image characteristics of the signal on the basis of depth image • Probabilistic Latent Component • Analysis (PLCA) is used to extract - Visualize the saliency of the sound source which is the beat component the time differences of depth and sound distribution
09:47–09:50 TuA3.11 09:50–09:53 TuA3.12 Audio Ray Tracing for Position An Adaptive Basic I/O Gain Tuning Estimation of Entities in Blind Regions Method Based on Leveling Control Input Jani Even1, Yoichi Morales1, Srikanth Kallakuri2 Histogram for Human-Machine Systems Carlos Ishi1 and Norihiro Hagita1 Mitsuhiro Kamezaki, Hiroyasu Iwata, and 1ATR-IRC 2Carnegie Mellon University Shigeki Sugano • Detection of a noisy entity in the Research Inst. for Sci. and Eng. Waseda Univ. blind region of the line of sigh • A method to tune a basic input- ࡼ࢙ ࡼ࢈ sensors (LRFs). output gain (BIOG) is proposed. • Use the acoustic reflections that
• The tuning system is based on “leak” from the blind region. comprehensive features from the +,, histogram of control lever input. • Trace back audio rays to the sound
• The proposed system improves
origin in the blind region using
estimated normals to surfaces from time efficiency while increasing subjective usability. a point cloud generated 3D map. Tuning mechanism
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
142 Session TuA3 Red Lacquer Room Tuesday, September 16, 2014, 09:00–10:20 Search, Rescue, and Audition / Field Robotics Chair Satoshi Tadokoro, Tohoku University Co-Chair
09:53–09:56 TuA3.13 09:56–09:59 TuA3.14
Development and Field Test of Intelligent Slip-Optimization Control with Traction-Energy Teleoperated Mobile Robots for Active Trade-off for Wheeled Robots on Rough Terrain Volcano Observation Jayoung kim1 and Jihong Lee1, K.Nagatani1, K.Akiyama1, G.Yamauchi 1, 1Chungnam National University K.Yoshida 1,Y.Hada 2, S.Yuta 3, T.Izu 4, R.Mackay 5
1 2 3 • On rough terrain, there are important 250 Velocitye Trackingk Rate Tohoku Univ. Kogakuin Univ. Shibaura Inst of Tech. 0 0.10.1 0.20.2 0.30.3 0.40.4 0.50.5 0.60.6 0.70.7 0.80.8 0.90.9 1 200 ControlControl Point 4 5 characteristics on soil types and surface S S enRoute Co., Ltd. Japan Drones Co., Ltd. 150 E T shapes Optimalt Slip AArea 100 • Volcanic observation system Soil Strength, K • Robots should be able to control the wheels 50 S opt
0 0.1 0.2 0.3 0.4 0.5 0.6 that includes MUAV and UGV. for maximizing traction and minimizing Slip Ratio, S - Slip-Optimization - • A sky-crane mechanism is used to energy consumption, while tracking a desired velocity. deploy UGV from MUAV. • Intelligent Slip-Optimization Control is • Field test was conducted at Mt. proposed to meet the performance of Asama in September 2013. traction-energy trade-off on rough terrains - ISOC flow chart -
09:59–10:02 TuA3.15 10:02–10:05 TuA3.16 Novel Robot Mechanism Capable of 3D Autonomous Robotic System Differential Driving Inside Pipelines for Bridge Deck Data Collection and Analysis S.U. Yang1, H.M. Kim1, J.S. Suh1, Y.S. Choi1, Hung La1, Nenad Gucunski2, Seong-Hoon Kee3, Jingang Yi4, 5 6 1 1 1 1 Turgay Senlet , Luan Nguyen H.M. Mun , C.M. Park , H. Moon and H.R. Choi 1University of Nevada, Reno, Nevada, USA 1 2,4,5,6Rutgers University, Piscataway, New Jersey, USA Sungkyunkwan University, Korea 3Dong-A University, Busan, Korea • Multi-axial differential gear mechanism This paper presents an autonomous robotic system for bridge data collection and analysis. - Power transmission of MRINSPECT VI The robot is equipped with various non- - Extension of 3D differential gear destructive evaluation (NDE) sensors for simultaneous and fast data collection. • Active wall pressing mechanism Crack detection and mapping algorithm • Brake mechanism for anti-slip and NDE data analysis are presented.
• Rescue mechanism for emergency The presented robotic system has been The deployment of the robotic bridge inspection successfully deployed to inspect system on the Washington Memorial bridge, • Experiments Washington DC, USA in 2013. MRINSPECT VI numerous bridges in USA.
10:05–10:08 TuA3.17 10:08–10:11 TuA3.18 Road Surface Washing System for De- A Framework for Predicting the Mission- contaminating Radioactive Substances Specific Performance of Mitsuru Endo1, Mai Endo2 and Takao Kakizaki2 Autonomous Unmanned Systems 1College of Engineering, Nihon Univ. Phillip Durst1, Wendell Gray1, 2Graduated School of Engineering, Nihon Univ. Agris Nikitenko2, Joao Caetano3, Mike Trentini4, • Decontaminate radioactive sub- image and Roger King5 stances spread by the accident of 1U.S. Army Engineer Research and Development Fukushima Nu-clear power plant any text in the Center 2Riga Technical University 3Portuguese • Propose a washing mechanism and image should 4 control algorithm Air Force Defense Research and Development be the same Canada 5Mississippi State University • Valid the decontaminating effective- size as main ness by experiments text
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
143 Session TuA3 Red Lacquer Room Tuesday, September 16, 2014, 09:00–10:20 Search, Rescue, and Audition / Field Robotics Chair Satoshi Tadokoro, Tohoku University Co-Chair
10:11–10:14 TuA3.19 10:14–10:17 TuA3.20 Experimental Analysis of Models for Sonar-based Chain Following using an Trajectory Generation on Tracked Vehicles Autonomous Underwater Vehicle Jonathan Fink and Ethan Stump N.Hurtós1, N.Palomeras1,A.Carrera1,M.Carreras1, US Army Research Laboratory C.P.Bechlioulis2, G.C.Karras2, S.H-a2, K.K2 1University of Girona 2N.T.U. of Athens • Consider and compare three • Framework to perform chain kinematic motion models with following, combining perception, extensive experiments planning and control disciplines. Y m X m • Dynamic drivetrain model 1 2 3 4 • Detection of links on challenging 0.5 • Applications to motion planning and 1.0 forward-looking sonar images. 1.5 feedback control systems for off- Y m Ideal differential drive model • Detections are grouped in waypoints X m 1 2 3 4 road terrain 0.5 that the AUV follows while keeping 1.0 the orientation to upcoming links. 1.5
2.0 General slip model 10:17–10:20 TuA3.21
Sponsor Talk: Vision-Based Navigation
Chris Jones iRobot Corporation
• Leader in Practical Robot Technologies and Products • Strategic focus on Navigation and Visual Perception • Internships and Full-time Positions Available in Pasadena, CA and Bedford, MA (http://irobot.com/careers; [email protected])
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
144 Session TuB1 Grand Ballroom Tuesday, September 16, 2014, 10:50–12:10 Medical Robots and Systems I / Rehabilitation Robotics I Chair Nikos Papanikolopoulos, University of Minnesota Co-Chair
10:50–11:10 TuB1.1 11:10–11:13 TuB1.2 Keynote: Medical Robotics – Melding A Fast, Low-Cost, Computer Vision Clinical Need with Engineering Research Approach for Tracking Surgical Tools Pierre E. Dupont R. Dockter1, R. Sweet2 and T. Kowalewski1 Boston Children’s Hospital, Harvard Med School 1University of Minnesota Mechanical Engineering 2University of Minnesota Medical School • Engineering academia and clinical medicine are very • Robotic and Laparoscopic surgery different worlds. needs low-cost skill measures derived from tool motion • To bridge the gap, I have moved my engineering lab to a hospital. • 3D video footage widely available • In this talk, I will describe my • We present: Computer Vision group’s experience and provide algorithm for near real time, 3D an overview of our research. localization of surgical tool tips • 26 FPS, 3.05 mm accuracy
11:13–11:16 TuB1.3 11:16–11:19 TuB1.4 A Dynamically Consistent Hierarchical Control Extended Kinematic Mapping of Tendon- Architecture for Robotic-Assisted Tele-Echography Driven Continuum Robot for Luís Santos1, Rui Cortesão1, Neuroendoscopy 1 Institute of Systems and Robotics, University of T. Kato1,2, I. Okumura3, H. Kose3 , K. Takagi3 and Coimbra, Portugal N. Hata1 1Brigham and Women's Hospital • Explicit Cartesian force control arises 2Canon U.S.A., Inc. 3Canon, Inc. as the primary task while orientation • Developed and validated a control is designed in the null space new tendon-driven • Cartesian force control, driven by continuum robot for position errors, establishes interaction neuroendoscopy dynamics between probe and patient • Introduced an extended O.D. 3.4 mm • Probe orientation is controlled at joint level, where forward kinematic mapping task space orientation errors are converted into joint with hysteresis operation Distal Section velocity references Proximal Section 11:19–11:22 TuB1.5 11:22–11:25 TuB1.6 Dielectrophoresis-based Automatic 3D Cell A novel redundant motion control mechanism in Manipulation and Patterning through a Micro- accordance with medical diagnostic and electrode Integrated Multi-layer Scaffold therapeutic task functions for a NIUTS H. K. Chu1, Z. Huan1,2, J. K. Mills3, J. Yang2, and D. Sun1 Norihiro Koizumi, Dongjun Lee , Joonho Seo, Takashi Azuma, and Mamoru Mitsuishi 1 City University of Hong Kong 3University of Toronto School of Engineering, The University of Tokyo, Japan 2University of Science and Technology of China Hiroyuki Tsukihara, Akira Nomiya, and Yukio Homma School of Medicine, The University of Tokyo, Japan Schematic of the Scaffold Kiyoshi Yoshinaka 3D: Top: The National Institute of Advanced Industrial Science and Technology, Japan • A scaffold utilizing dielectrophoresis for cell • We have developed non-invasive manipulation and patterning was proposed. ultrasound theragnostic system (NIUTS). • In this report, we propose novel • Electric fields generated from the multi- redundant motion control mechanism of layer structure polarized the cells to HIFU focus, for therapeutics, that is facilitate 3D manipulation. Top layer independent of ultrasound probes for diagnostics. • 3D cellular patterns were formed which • Proposed mechanism enables noise spanned all scaffold layers. Cell patterns factors, which deteriorate image quality, to be reduced, thereby enhancing Focal Bottom layer Lesion Servo (FLS) performance. Redundant motion control mechanism.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
145 Session TuB1 Grand Ballroom Tuesday, September 16, 2014, 10:50–12:10 Medical Robots and Systems I / Rehabilitation Robotics I Chair Nikos Papanikolopoulos, University of Minnesota Co-Chair
11:25–11:28 TuB1.7 11:28–11:31 TuB1.8
Simultaneously Power & Control Many Simultaneous Catheter and Environment Modeling Actuators With a Clinical MRI Scanner for Trans-catheter Aortic Valve Implantation Aaron Becker, Ouajdi Felfoul, & Pierre E. Dupont Chaoyang Shi, Stamatia Giannarou, Boston Children’s Hospital & Su-Lin Lee and Guang-Zhong Yang Harvard Medical School, USA The Hamlyn Centre, Imperial College London, UK • Uses MRI to power & • 3D vessel reconstruction image multiple actuators ferrous sphereses fusing IVUS images and EM • Relies on inhomogeneities measurement data; e.g. no parallel rotors • Catheter shape reconstruction • Easily implemented based on FBG sensors; position & velocity actuator controllers—global • The method could facilitate needle intra-operative surgical guidance and minimize the use asymptotic convergence robot of contrast agent in TAVI procedures. • All code online (MATLAB) 3 Actuators workspace 11:31–11:34 TuB1.9 11:34–11:37 TuB1.10 $"%$%" # $" % Online Identification of Tissues In Vivo % $ "# ' $ " & $ $ for Injury-Avoiding Surgical Robots 1 1 H. Azimian1, P. Francis2, T. Looi1 and J. Drake1 Astrini Sie , Michael Winek , 1 1CIGITI, Hospital for Sick Children, Toronto and Timothy M. Kowalewksi 1 2University of Waterloo, Waterloo University of Minnesota • A new solution is proposed to • Presents a smart robotic surgical reduce torsion in concentric-tube grasper capable of identifying manipulators. abdominal soft tissues during the • Using composite structures with Cellular tubes early stages of a grasp higher torsional-to-bending can exhibit • Employed an estimation algorithmm stiffness ratios is suggested. negative based on extended Kalman filter • Results show up to 40% Poisson’s ratios • Algorithm verified in silico, in situ, improvement in stability margin. and in vivo on porcine models
11:37–11:40 TuB1.11 11:40–11:43 TuB1.12
Micro Laser Ablation System Integrated Preliminary Evaluation of a New Control Approach to Achieve with Image Sensor for Speed Adaptation in Robotic Transfemoral Prostheses
Minimally Invasive Surgery Tommaso Lenzi12, Levi J Hargrove12, and Jonathon W Sensinger3 1Rehabilitation Institute of Chicago 2Northwestern University Baiquan Su1, Zhan Shi1, Hongen Liao1 3University of New Brunswick 1Tsinghua University, Beijing, China • biologically accurate function at • A micro surgical system with a varying walking speeds micro laser ablation module and an imaging sensor for • quasi-stiffness modulation in minimally invasive surgery. stance phase • The diameter and the length • minimum jerk trajectory in swing of the module are 3.5 phase millimeters and 15 millimeters, • no need for subject-specific tuning respectively.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
146 Session TuB1 Grand Ballroom Tuesday, September 16, 2014, 10:50–12:10 Medical Robots and Systems I / Rehabilitation Robotics I Chair Nikos Papanikolopoulos, University of Minnesota Co-Chair
11:43–11:46 TuB1.13 11:46–11:49 TuB1.14
Development of Elbow-Forearm Interlock A Method for Predicting Personalized Pelvic Motion based on Body Joint Mechanism Toward an Exoskeleton Meta-Features for Gait Rehabilitation Robot for Patients with Essential Tremor Sung Yul Shina, Jisoo Hongb, Changmook Chuna, Seung-Jong Kima, and ChangHwan Kima aCenter for Bionics, Korea Institute of Science and Technology 1 1 1 Yuya Matsumoto , Motoyuki Amemiya , Daisuke Kaneishi , bDepartment of Mechanical & Aerospace Engineering, Seoul National University Yasutaka Nakashima1, Masatoshi Seki1,2, Takeshi Ando1,3, Yo Kobayashi1, 4 5 1 Pelvic Motion Generation for 14 Body Features 4 Movement Features Hiroshi Iijima , Masanori Nagaoka , Masakatsu G. Fujie Gait Rehabilitation Robot COWALK 1Waseda University 2Kikuchiseisakusho Co., Ltd. 3Panasonic 4Yokohama Rehabilitation Centor 5Juntendo University Graduate School • Development of elbow-forearm interlock joint mechanism to avoid occurrence of compensatory Pelvic Trajectory Prediction movement without using an actuator Body Meta-Features + k-NN • The mechanism will be applied for an exoskeleton to suppress an involuntary oscillation of patients with tremor
11:49–11:52 TuB1.15 11:52–11:55 TuB1.16 Towards Local Reflexive Control of a Analysis of Inertial Motion in Swing Powered Transfemoral Prosthesis for Phase of Human Gait and Its Application Robust Amputee Push and Trip Recovery to Motion Generation Method of Nitish Thatte1, Hartmut Geyer1 Transfemoral Prosthesis 1 Carnegie Mellon University T. Wada 1, H. Sano1, M. Sekimoto2 • Amputees often suffer from falls that 1Ritsumeikan University 2University of Toyama cause injuries and a fear of walking • A inertial motion index was • Neuromuscular models of walking proposed to evaluate closeness of produce robust and natural gaits given motion to inertial motion of • Using neuromuscular reflexes to multilink system control prostheses may improve • Inertial motion was effectively used amputee walking robustness mid-swing of human gait • A motion generation method of tf l thi 11:55–11:58 TuB1.17 11:58–12:01 TuB1.18 Contralateral Leg Response to Unilateral Mobile robotic gait rehabilitation system Stiffness Changes using Novel Device CORBYS Jeffrey Skidmore1, Andrew Barkan1 and S. Slavnić1, D. Ristić-Durrant 1,R. Tschakarow2, T. Panagiotis Artemiadis1 Brendel3, M. Tüttemann3, A. Leu1 and A. Gräser 1 1Arizona State University, USA 1IAT Bremen 2Schunk GmbH 3Otto-Bock • Unique research • System overview and first results on platform to the orthosis actuation investigate gait • Novel push-pull control cable control mechanisms actuation system of the orthosis • Investigation of • Actuation system identification sensory feedback • Control of the orthosis on inter-limb • Experimental results coordination CAD image of the CORBYS • Conclusion and future work mobile gait rehabilitation system
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
147 Session TuB1 Grand Ballroom Tuesday, September 16, 2014, 10:50–12:10 Medical Robots and Systems I / Rehabilitation Robotics I Chair Nikos Papanikolopoulos, University of Minnesota Co-Chair
12:01–12:04 TuB1.19 12:04–12:07 TuB1.20
Design and Control of an Exoskeleton System for Gait Integrated Control Method for Power- Rehabilitation Capable of Natural Pelvic Movement Assisted Rehabilitation 1 1 1 1 C.-Y. Jung1,2, J. Choi2, Jaemin Lee ,Minkyu Kim ,Sang-Rok Oh ,Keehoon Kim S. Park1, J. M. Lee2, C. Kim2, and S.-J. Kim2 1Interaction & Robotics Research Center 1Korea Univ. 2KIST Korea Institute of Science and Technology, Seoul, Korea • Exoskeleton system for Body weight support system • This research aims to offer the power image gait rehabilitation of – assisted rehabilitation for upper
stroke survivors Controller limb as guided by therapists. any text in the • Pelvic motion is allowed • The proposed method is based on image should for natural gait using 4 Exoskeleton the modified impedance controller be the same DOF • The desired position and assisting size as main Gravity compensator • Weight of exoskeleton is force are reproduced by ellipsoid text compensated by gravity Treadmill regression of training data with the compensator therapist 12:07–12:10 TuB1.21 reachMAN2: A compact rehabilitation robot to train reaching and manipulation L.Z. Tong1, J. Klein2, S.A. Dual1, C.L. Teo1 and E. Burdet2 1National University of Singapore, 2Imperial College of Science, Technology and Medicine, London, UK
This paper describes the reachMAN2, a simple rehabilitation robot providing assistance in essential functions for activities of daily living: arm flexion/extension, forearm supination/pronation and hand opening/closing.
A special feature is the handle built over load cells and using an innovative cam mechanism enables natural hand opening/closing movements.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
148 Session TuB2 State Ballroom Tuesday, September 16, 2014, 10:50–12:10 Human-Robot Interaction II / Robot Learning III Chair Jianwei Zhang, University of Hamburg Co-Chair
10:50–11:10 TuB2.1 11:10–11:13 TuB2.2 Keynote: Robots and Gaming – Therapy A Gesture Recognition System for for Children with Disabilities Mobile Robots That Learns Online Ayanna Howard Alan J. Hamlet1, Patrick Emami1, Georgia Institute of Technology and Carl D. Crane1 1 • Robots and gaming technologies University of Florida that provide non-contact assistance • Novice users can teach robot to to children for achieving their recognize new dynamic gestures therapy goals will be discussed • Requires only one training example • Quantitative assessment of the • Learns from experience, improving child’s performance is also derived recognition accuracy over time to provide feedback to the clinician • Uses Robot Operating System • These technologies have been (ROS), Kinect sensor deployed in various robot-child interaction scenarios
11:13–11:16 TuB2.3 11:16–11:19 TuB2.4 Cartesian Impedance Control of Estimation of Contact Forces Redundant Manipulators for using a Virtual Force Sensor Human-Robot Co-Manipulation
F. Ficuciello, A. Romano, L. Villani, B. Siciliano E. Magrini, F. Flacco, and A. De Luca Università degli Studi di Napoli Federico II, Italy DIAG, Sapienza University of Rome, Italy Dip. Ing. Elettrica e Tecnologie dell’Informazione • Detect physical contacts and estimate • The problem of controlling a robot the related joint torques by residuals arm executing a cooperative task • Localize the contact point(s) on the with a human is addressed. robot by an external depth sensor • The end effector comply according • Combine and obtain the contact force to a Cartesian impedance law. Snapshot of the vector(s) without tactile or F/T sensors • Redundancy is used to ensure a co-manipulation • Validation of estimates and safe HRI decoupled inertia at the end effector task control experiments on a KUKA LWR for stability and performance.
11:19–11:22 TuB2.5 11:22–11:25 TuB2.6 Multi-Muscle FES Control of the Human Pneumatic Tubular Body Fixture for Arm for Interaction Tasks Wearable Assistive Device Yu-Wei Liao1, Eric Schearer1, Yasuhisa Hasegawa1, Takaaki Hasegawa2, Eric Perreault1, Matt Tresch1, and Kevin Lynch1 and Kiyoshi Eguchi3, 1Nagoya Univ. 2Univ. of 1Northwestern University Tsukuba 3Tsukuba Univ. Hospital • An algorithm for feedforward control of the stiffness of a • Body holder, Active Cuff, of a human arm model is developed to ensure arm stability wearable assistive device in simple • Both effects of muscle co- wearing actions and comfort. contraction and postural • Pneumatic actuator modules adjustment are incorporated actively wrap and hold users’ limb with less effort in a short time. • A “pushing with a stick” task is simulated to demonstrate • Modeling of the actuators’ the strength of our controller deformations for holder design
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
149 Session TuB2 State Ballroom Tuesday, September 16, 2014, 10:50–12:10 Human-Robot Interaction II / Robot Learning III Chair Jianwei Zhang, University of Hamburg Co-Chair
11:25–11:28 TuB2.7 11:28–11:31 TuB2.8 Implementation and experimental Support Vector Machine Classification of validation of DMP for object handover Muscle Cocontraction to Improve pHRI Miguel Prada1, Anthony Remazeilles1, A. Moualeu1, W. Gallagher2 and Ansgar Koene2 and Satoshi Endo2 J. Ueda1 1Tecnalia 2Univ. Of Birmingham 1Georgia Institute of Technology 2NASA • Evaluation of a DMP-based • The goal of our study is to controller for human-robot improve performance in physical object exchange human-robot interaction. • Experimental setup with a car • This requires endpoint stiffness mechanic inspired scenario estimation and accurate modeling of operator dynamics. Figure. 1-DOF • Analysis of quantitative Haptic Device • This will ultimately allow us to measurements and subjective Experiment user feedback properly tune impedance gains of a novel haptic controller.
11:31–11:34 TuB2.9 11:34–11:37 TuB2.10 Oscillation Reduction Scheme for Joint Configuration Strategy for Serial- Wearable Robots Employing Linear chain Safe Manipulators Actuators and Sensors Seonghun Hong1,2, Woosub Lee2, Changhyun 1 1 Junghoon Choo , Junghoon Choo , Cho3, Sungchul Kang2 and Hyeongcheol Lee1 2 3 Dong-Hyun Jeong and Jong Hyeon Park 1Hanyang Univ. 2KIST 3Chosun Univ. 1,3Hanyang University 2DSME • A collision can happen anywhere • The moment arm of linear actuators is from the base to the end-effector. varied with joint angle, and sensed • After several case studies were pressure is changed by the variation. conducted, VTR:R configuration • An abrupt pressure change generates was selected as an appropriate oscillations in a particular range of joint configuration. joint angle. • We developed SS-Arm 3, for the VTR:R Configuration • For canceling the oscillation, three proposed configuration strategy and SS-Arm 3 kinds of method are proposed. with safety components.
11:37–11:40 TuB2.11 11:40–11:43 TuB2.12 Single Muscle Site EMG Interface for Using Haptics to Extract Object Shape Assistive Grasping from Rotational Manipulations Claudius Strub1,3, Florentin Wörgötter1, Jonathan Weisz1, Alex Barszap2, Sanjay Joshi2, Helge Ritter2 and Yulia Sandamirskaya3 1Georg- and Peter K. Allen1 August-Universität Göttingen 2Bielefeld 1Columbia University 2UC Davis University 3Ruhr-Universität Bochum • Presents an assistive grasping image • Rotating n-gons with a SDH-2 system which integrates real-time • Object pose and shape unknown grasp planning with novel sEMG device input device Electrodes • Building an object shape representation during manipulation • Recording from a single, site innervated from brainstem. • Requires to track the object orientation from tactile inputs and to • UI designed to handle cluttered correct for accumulating errors environments • Solved with Dynamic Neural Fields
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
150 Session TuB2 State Ballroom Tuesday, September 16, 2014, 10:50–12:10 Human-Robot Interaction II / Robot Learning III Chair Jianwei Zhang, University of Hamburg Co-Chair
11:43–11:46 TuB2.13 11:46–11:49 TuB2.14 Dynamic Attack Motion Prediction Integration of Various Concepts and for Kendo Agent Grounding of Word Meanings Using Multi-layered Multimodal LDA for Sentence Generation Muhammad Attamimi1, Muhammad Fadlil1, Kasumi Abe1, Yasufumi Tanaka1, Kazuhiro Kosuge1 Tomoaki Nakamura1,2, Kotaro Funakoshi2, and Takayuki Nagai1, 1University of Electro-Communications 2Honda Research Institute Japan
• A method to integrate various concepts Concept Formation • We propose a motion prediction considering the mutual interdependence Person concept method for Kendo Agent. among them in a hierarchical structure • Grammar learning based on Markov Place concept integrated • Human motions are modeled usin model learned from order of concepts in concept teaching utterances is proposed to Gaussian Mixture Models as Motion concept Scenes enable sentence generation “Doctor” (Job concept) The doctor is moving a stethoscope in the Object concept nonlinear dynamical systems. • Other abilities of proposed multi-layered hospital multimodal LDA: • Attack motion is predicted using the Word acquisition – Inference among different kinds of concepts model and the euler’ method. B Inference of unseen info. – Inference of unseen information Motion Place Sentence 1 Integrated Y. Tanaka and K. Kosuge, the Department of Bioengineering and – Grounding of word meanings in hierarchical Object E Generation Robotics, Graduate School of Engineering, Tohoku University structure of concepts Grammar Learning
11:49–11:52 TuB2.15 11:52–11:55 TuB2.16
A Machine Learning Approach Transfer of Sparse Coding Representations and for Real-Time Reachability Analysis Object Classifiers Across Heterogeneous Robots Ross Allen1, Ashley Clark1, Zsolt Kira1, Joseph Starek1 and Marco Pavone1 1Georgia Tech Research Institute, 1Stanford University Atlanta, GA 30318 USA • A regression and a classification • We examine the problem of transfer algorithm, trained with solutions to learning in a heterogeneous robot optimal control problems, can team when sparse coding feature accurately predict reachability of learning is used to classify objects. Robot 1 features novel reachability queries. • We propose a technique to align • These algorithms can solve a query features learned across different in <10ms with >90% accuracy robots and demonstrate transfer. • We further show that codebook schemes significantly improve transfer. Robot 2 features
11:55–11:58 TuB2.17 11:58–12:01 TuB2.18 A Perceptual Memory System for Actor-Critic Design using Echo State Grounding Semantic Representations in Networks in a Quadruped Robot Intelligent Service Robots Nico Schmidt, Matthias Baumgartner 1,3 1,3 1,2,3 M. Oliveira , G. H. Lim , L. Seabra Lopes , and Rolf Pfeifer 1,3 1,2,3 1,3 S. Kasaei , A. M. Tomé and A. Chauhan AI-Lab, University of Zurich, Switzerland 1University of Aveiro, Portugal 2DETI 3IEETA • Navigation of a simulated compliant Based on an analysis of require- quadruped robot is learnt from minimal ments for storing both semantic and prior knowledge through reinforcement perceptual data, a perceptual learning (actor-critic design). memory system was developed. • The complex action-behavior mapping The perceptual memory supports of the robot is captured by the anchoring of object symbols as well dynamic reservoir of the echo state as open-ended learning of object network that predicts future rewards categories. http://youtu.be/jLJqY2fKTdI and is used for action selection.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
151 Session TuB2 State Ballroom Tuesday, September 16, 2014, 10:50–12:10 Human-Robot Interaction II / Robot Learning III Chair Jianwei Zhang, University of Hamburg Co-Chair
12:01–12:04 TuB2.19 12:04–12:07 TuB2.20 Expensive Multiobjective Optimization for ! Robotics with Consideration of Heteroscedastic Noise 1 2 Ryo Ariizumi , Matthew Tesch , 1,4 2,4 3,4 Howie Choset2 and Fumitoshi Matsuno1 A. Iscen , A. Agogino , V. SunSpiral and K. 1 1Kyoto University 2Carnegie Mellon University Tumer • Expensive multiobjective optimization 1Oregon State University 2UARC 3SGT Inc based on response surface method 4NASA Ames Research Center through noisy observations • Use heteroscedastic Gaussian • Learning based, compliant rolling process regression to handle locomotion algorithm observation noise on robotic • Distributed and robust actuation experiments • Uses minimal sensory input • The method is tested on numerical • Can handle different terrain and real snake robot experiments conditions
12:07–12:10 TuB2.21 " &! " Franziska Meier1, Philipp Hennig2 and Stefan Schaal1,2 1University of Southern California 2Max-Planck-Institute for Intelligent Systems • Model-based control requires accurate, efficient and robust learning algorithmsalgorithms • We transform Bayesian regressionssion toto a localized inference procedure • This results in a robust learningg procedure that has low complexityexityy • $ # " "% " " ! !" "! # "
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
152 Session TuB3 Red Lacquer Room Tuesday, September 16, 2014, 10:50–12:10 Marine Robotics / Space Robotics Chair John Leonard, MIT Co-Chair
10:50–11:10 TuB3.1 11:10–11:13 TuB3.2 Keynote: Human-guided video data Predicting the Speed of a Wave Glider collection in marine environments ASV from Wave Model Data Gregory Dudek P. Ngo1, J. Das2, J. Ogle3, J. Thomas4, McGill University W. Anderson4 and R.N. Smith3 1QUT, 2USC, 3FLC, 4LRI • Issues in autonomous underwater data collection, a • Apply Gaussian process models to retrospective. WAVEWATCH III model data to • Issues for robots working at the predict the velocity of a Wave Glider behest of a human operator, • Train GP models with on-board data. collecting data for their use. • Compare multiple regression models • Combination of interactive across different spatiotemporal command execution, navigation scales to data collected during field and vision-based data trials. summarization 11:13–11:16 TuB3.3 11:16–11:19 TuB3.4 3D Trajectory Synthesis and Control for Compact, Tetherless ROV for In-Contact a Legged Swimming Robot Inspection of Underwater Structures David Meger1, Florian Shkurti1, David Cortés Poza1, Phipippe Giguère2 and S Bhattacharyya1, HH Asada2, Gregory Dudek1 1,2 Massachusetts Institute of Technology 1McGill University 2Université Laval • Dynamic 3D legged • EVIE: An ellipsoidal tetherless swimming motions appendage free underwater vehicle • Feedback control with in for in contact inspection of situ parameter learning submerged surfaces. • Trajectory synthesis HRI • Preliminary design with angled jets intuitive for scuba divers and analysis of the hybrid system. • Validated via open ocean • Demonstration of closed loop control ship-wreck inspection on a horizontal underwater plane.
11:19–11:22 TuB3.5 11:22–11:25 TuB3.6 I-AUV Docking and Intervention in a 3D Reconstruction of Bridge Structures Subsea Panel above the Waterline with an USV N. Palomeras1, A. Peñalver2, M. Massot-Campos3, J. Han, J. Park and J. Kim G.V1, P.N3, J.J.F2, P.R1, P.J.S2, G.O3, A.P1 Division of Ocean Systems Engineering, KAIST, 1Universitat de Girona 2Universitat Jaume I 3Universitat Korea Illes Balears • The paper presents an autonomous • GPS signals are severely deteriorated intervention on a friendly underwater image near or underneath bridge structures. panel with a light-weight I-AUV. • A parameterized SLAM is introduced any text in the • Autonomous intervention steps are: image should which estimates geometric parameters docking, valve turning, and hot stab be the same of detected bridge piers to achieve plugging/unplugging. size as main improved SLAM performance. • The mission has been successfully text • 3D reconstruction of bridge structures tested on a water tank with the is implemented by sensor fusion. Girona 500 I-AUV.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
153 Session TuB3 Red Lacquer Room Tuesday, September 16, 2014, 10:50–12:10 Marine Robotics / Space Robotics Chair John Leonard, MIT Co-Chair
11:25–11:28 TuB3.7 11:28–11:31 TuB3.8 Active Range-Only Beacon Autonomous Vehicle Localization in a Vector Localization for AUV Homing Field: Underwater Vehicle Implementation 1 1 Guillem Vallicrosa1, Pere Ridao1, Zhuoyuan Song and Kamran Mohseni 1 David Ribas1 and Albert Palomer1 University of Florida 1 • A background vector field based localization method is Universitat de Girona discussed and implemented in an underwater scenario • Sum of Gaussian (SOG) filter for image • Background flow velocity maps with time stamps are Range-Only beacon localization. predicted by ocean models and preloaded on to vehicles • Active Localization by taking the any text in the • Vehicles measure local flow movement leading to the smaller image should velocities and estimate their uncertainty after SOG filter update. be the same locations by comparing the • Tested in a harbor environment with size as main measurements with map Girona500 AUV and an underwater text prediction using particle panel with a beacon. filters, which results in convergent localization error
11:31–11:34 TuB3.9 11:34–11:37 TuB3.10
Underway Path-planning for an USV Experimental Validation of Performing Cooperative Navigation Robotic Manifold Tracking in Gyre-Like Flows Matthew Michini and M. Ani Hsieh 1 2 SAS Lab, Mechanical Engineering & Mechanics, Drexel University, USA Jonathan Hudson , Mae L. Seto Eric Forgoston 1Dalhousie University 2Defence R&D Canada Department of Mathematical Sciences, Montclair State University, USA Ira B. Schwartz • USV used as a communications and Naval Research Lab, USA image navigations aid (CNA) for UUVs • Experimental validation of a collaborative control strategy for distributed tracking of • objective to reduce UUVs’ IVER2 UUVs coherent structures in ocean-like flows positioning error through optimal • Novel multi-robot experimental test-bed used for in- capable of creating controllable ocean-like path-planning for USV CNA water validation flows • USV path-planning adapts to • Experimental results for time-independent and time-dependent flow fields using a fleet of changes in planned UUV paths micro-autonomous surface vehicles (mASVs) Three mASVs in the Multi- Robot (MR) Tank with • implementation in MOOS-IvP show the feasibility and robustness of the PIV/PTV tracer particles approach.
11:37–11:40 TuB3.11 11:40–11:43 TuB3.12 Trajectory Planning with Adaptive Control Primitives Inchworm Style Gecko Adhesive for Autonomous Surface Vehicles Operating in Congested Civilian Traffic Climbing Robot Brual C. Shah, Petr Švec, and Satyandra K. Gupta Simon Kalouche12, Nicholas Wiltsie2, Maryland Robotics Center, College Park, USA 2 2 Ivan R. Bertaska, Wilhelm Klinger, Armando J. Sinisterra, Hai-jun Su and Aaron Parness 1 2 Karl von Ellenrieder, and Manhar Dhanak Ohio State University JPL/Caltech Ocean & Mechanical Engineering, Florida Atlantic University, USA • Two oppositional gecko • Developed 5D lattice-based trajectory planner for unmanned surface vehicle (USV) adhesive pads provide omni- that reasons about reciprocal behaviors of directional anchoring for civilian boats in congested traffic climbing in any orientation • Planner incorporates contingency maneuvers into trajectory to be used in case • Inchworm gait is realized with any of civilian vessels breaches COLREGs a rack and pinion mechanism • Its computational efficiency is increased by dynamically time scaling motion primitives A scenario with an USV and civilian • Turning and plane changes based on scene congestion vessels moving to their respective are also possible. destinations in a harbor region
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
154 Session TuB3 Red Lacquer Room Tuesday, September 16, 2014, 10:50–12:10 Marine Robotics / Space Robotics Chair John Leonard, MIT Co-Chair
11:43–11:46 TuB3.13 11:46–11:49 TuB3.14 Backup State Observer Based on Optic Experimental Evaluation of On-board, Flow Applied to Lunar Landing Visual Mapping of an Object Spinning in G. Sabiron1,2, L. Burlion2, G. Jonniaux3, E. Kervendal3, E. Micro-Gravity aboard the International Bornschlegl4, T. Raharijaona1, and F. Ruffier1 1 Space Station Aix-Marseille University, CNRS, Institute of Movement Science, Biorobotics Dept., 1 1 UMR7287, 13288, Marseille, France, 2ONERA, The French Aerospace Lab, Brent Tweddle , Timothy Setterfield , 3Airbus Defence and Space, 4European Space Agency Alvar Saenz-Otero1, David Miller1, and John Leonard2 1MIT SSL 2MIT CSAIL • SLAM of an object spinning about its intermediate axis in microgravity • Incorporates Dynamics into Factor Graph Model • First ever run of SLAM algorithm onboard a computer in space (to the best of our knowledge)
11:49–11:52 TuB3.15 11:52–11:55 TuB3.16 Small Body Surface Mobility with a On Controller Parametric Sensitivity of Limbed Robot Passive Object Handling in Space by Daniel Helmick1, Bertrand Douillard1, Robotic Servicers and Max Bajracharya1 Georgios Rekleitis1, Evangelos Papadopoulos1, 1Jet Propulsion Laboratory 1National Technical University of Athens • Goal: Develop, demonstrate, and • Passive object manipulation by evaluate small body (asteroids and orbital servicers in zero gravity comets) mobility with a limbed robot • Parametric sensitivity analysis of a • Results: Have demonstrated in a model-based control, in terms of micro-gravity gantry various mobility parametric uncertainties behaviors with a prototype limbed • Linearization methodology used to provide a scheme robot including: landing, blind for a-priori ensuring controller robust behavior walking, hopping, and path following • Verification by simulations of realistic 3D scenarios
11:55–11:58 TuB3.17 11:58–12:01 TuB3.18 Design of a Hopping Mechanism Soft Landing of Capsule by Casting using Permanent Magnets for Manipulator System Small-scale Exploration Rovers Hitoshi Arisumi1, Masatsugu Otsuki2, and Masamitsu Kurisu Shinichiro Nishida3 1AIST 2JAXA 3Tottori Univ. Tokyo Denki University • Design of a hopping mechanism • Control method of capsule’s flight by using permanent magnets for mutual tension of wires is proposed small-scale exploration rovers is Magnets • Motion planner, launcher, & energy presented. dissipation device were developed • An example of the design • Landing impact of the capsule was procedure for deriving the Motor decreased by 97.8% in experiments potential ability of the mechanism • Capsule floated for 0.4s and its soft is introduced. Hopping mechanism landing was successfully realized
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
155 Session TuB3 Red Lacquer Room Tuesday, September 16, 2014, 10:50–12:10 Marine Robotics / Space Robotics Chair John Leonard, MIT Co-Chair
12:01–12:04 TuB3.19 12:04–12:07 TuB3.20 Particle Filter based 3D Position Tracking for A Real-time Recognition Based Drilling Terrain Rovers using Laser Point Clouds Strategy for Lunar Exploration Peshala G. Jayasekara1, Genya Ishigami2 and Takashi Kubota3 Quanqi Quan and Junyue Tang 1AIST 2Keio University 3ISAS, JAXA Harbin Institute of Technology, China
• A state variable extension (SVE) rover with rocker • Proposed a concept of LRD (lunar method is proposed to establish a suspension regolith drillability); connection between (z, roll, pitch) • Adopted pattern recognition method and (x, y, yaw) state variables, given of SVM to recognize the LRD online; the knowledge of the terrain in the form of laser point clouds. • Verified real-time recognition based drilling strategy which can adapt to • SVE is employed in a particle filter to uneven terrain complicated drilling media well. estimate the full 3D pose of a rover with rocker suspension.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
156 Session TuC1 Grand Ballroom Tuesday, September 16, 2014, 13:30–14:50 Dynamics and Control / Manipulation and Grasping IV Chair Jonas Buchli, ETH Zurich Co-Chair
13:30–13:50 TuC1.1 13:50–13:53 TuC1.2
Keynote: Highly dynamic, energy-aware, Robust Control of Flexible Joint Robots Based On Motor-side biomimetic robots Dynamics Reshaping using Disturbance Observer (DOB)
Stefano Stramigioli Min Jun Kim1 and Wan Kyun Chung1 University of Twente 1POSTECH • Reproducing highly dynamic • Use flexible joint model(motor dynamics+link dynamics) behaviour happening in nature can only be achieved by energy- • Apply DOB only on the motor-side dynamics aware modelling and control • Studies the stability issue of DOB-based structure • This keynote will present some • Estimated signal is fed back into controller activities, ideas, theory and arguments on the subject • Biomimetic robots presented are a peregrine falcon and a cheetah
13:53–13:56 TuC1.3 13:56–13:59 TuC1.4 A Novel RISE-Based Adaptive Constrained Directions as a Path Feedforward Controller for RA-PKMs Planning Algorithm for Mobile Robots Moussab Bennehar, Ahmed Chemori Rana Soltani-Zarrin, Suhada Jayasuriya, and François Pierrot Drexel University LIRMM, Univ. Montpellier 2 - CNRS, France
e2
• Dynamic modeling of a 2wheeled d
• A RISE-based adaptive controller a β L Ф G for RA-PKMS is developed. differential drive mobile robot e1 c
subject to slipping with a novel slip R • An adaptive feedforward term is j
characterizing model k i added to RISE control scheme. o • More realistic results compared to • A projection operator is applied to existing models in literature reduce internal forces. • Path finding algorithm based on • Experimental results show the constrained directions subject to improved control performances. Dual-V RA-PKM actuator limitations
13:59–14:02 TuC1.5 14:02–14:05 TuC1.6 Partially Analytical Extra-Insensitive Terminal Sliding-Mode Based Force Shaper for a Lightly Damped Flexible Arm Tracking Control of Piezoelectric Actuators for Variable Physical Damping Chul-Goo Kang1 and Manh-Tuan Ha1 Jinoh Lee1, Maolin Jin2, Nikolaos G. Tsagarakis1 1Konkuk University, Korea and Darwin G. Caldwell1 • In order to suppress residual vibration for a lightly 1Istituto Italiano di Tecnologia, 2RIST damped flexible arm, we introduce an EI shaper which • A robust force tracking controller
is represented by a partially cl- 1.5 for Piezoelectric actuator (PEA) = 4.8Hz, = 0.03 n = 4Hz, = 0.03 m m 20% modeling error in osed form with one parameter, n • Terminal SMC incorporating 1 with an efficient model-free motor instead of a numerical solution. es d u lit dynamics compensation for
mp link
• The validity of the partially an- A 0.5 Partially analytical EI input shaping control hysteresis and creep effects. ZVD input shaping control alytical EI shaper is shown by 1.05 line 0.95 line • Application on physical variable contact PEAs Force simulations and experiments. 0 0 1 2 3 damping system driven by PEA. Time (s) surface Sensor
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
157 Session TuC1 Grand Ballroom Tuesday, September 16, 2014, 13:30–14:50 Dynamics and Control / Manipulation and Grasping IV Chair Jonas Buchli, ETH Zurich Co-Chair
14:05–14:08 TuC1.7 14:08–14:11 TuC1.8
Development of a Single Controller for A Reverse Priority Approach the Compensation of Several Types of to Multi-Task Control of Redundant Robots Disturbances During Task F. Flacco and A. De Luca Luis Canete1, Takayuki Takahashi1, DIAG, Sapienza University of Rome, Italy 1Fukushima University • Inverse differential kinematics for • Presenting the Inverted PENdulum multiple tasks free of algorithmic Type Assistant Robot (I-PENTAR) singularities • Development of “a single controller • Contributions by high priority tasks for multiple tasks” method added after those of lower priority • Improved disturbance compensation (reverse) method • Rank loss in prioritized task Jacobians does not affect the original hierarchy • Validation with numerical simulations and 14:11–14:14 TuC1.9 14:14–14:17 TuC1.10 Dynamic modeling of continuum robots Fast and Reasonable Contact Force using the Euler-Lagrange formalism Computation in Forward Dynamics Based on Momentum-Level Penetration Compensation Valentin Falkenhahn1, T. Mahl1, A. Hildebrandt2, R. Neumann2 and Oliver Sawodny1 Naoki Wakisaka1, Tomomichi Sugihara1, 1University of Stuttgart 2Festo AG & Co. KG 1Osaka University • Aim: Model of continuum robots with multiple sections for model-based MIMO controller design • Kinetic model based on kinematic model (constant curvature) • Results validated with simulations and experiments
14:17–14:20 TuC1.11 14:20–14:23 TuC1.12 Recursive Dynamics and Feedback Grasp Planning Linearizing Control of Serial-Chain for Constricted Parts of Objects Manipulators Approximated with Quadric Surfaces 1 1 2 1 Matthew Travers and Howie Choset T. Tsuji , S. Uto , K. Harada , R. Kurazume , T. Hasegawa3 and K. Morooka1 • We derive closed form feedback linearizing controllers 1Kyushu University 2AIST 3Kumamoto-NCT for N-link serial chain manipulators • We develop a grasp planner • The analytical expressions which allows a robot to grasp the make it possible to accurately constricted parts of objects. control these complex-coupled • We propose a method for grasp systems, even in the presence stability evaluation based on the of significant joint elasticity stress distribution applied to an object by the fingers.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
158 Session TuC1 Grand Ballroom Tuesday, September 16, 2014, 13:30–14:50 Dynamics and Control / Manipulation and Grasping IV Chair Jonas Buchli, ETH Zurich Co-Chair
14:23–14:26 TuC1.13 14:26–14:29 TuC1.14 Fast grasping of unknown objects using Robotic Nonprehensile Catching: force balance optimization Initial Experiment Masahito Yashima1 and Tasuku Yamawaki1 Qujiang Lei, Martijn wisse Delft University of Technology 1National Defense Academy of Japan • A novel grasping algorithm is • Initial efforts to achieve robotic presented for unknown object nonprehensile catching grasping. Force balance calculation • The importance of nonprehensile on XOY and XOZ plane makes sure catching in a robotic catching task is the grasping very reliable and shown stable. The robot can quickly work • Control strategies for nonprehensile out the grasping position and catching are proposed orientation with one point cloud or • Demonstration through experiments two point clouds.
14:29–14:32 TuC1.15 14:32–14:35 TuC1.16
Changing Pre-Grasp Strategies With Increasing Object Location Uncertainty 1 1 2 Boris Illing , Tamim Asfour and Nancy S. Pollard • -. # " # ! #& # '#! "## " 1 #! ( "!$ # ( # 1 Karlsruhe Institute of Technology " # "#!$#$! ( ""#" # "0 # ! 2 # ' ! $# ! " % !0 Carnegie Mellon University '# " #! 54 ! ! " "" 1 • # # !# 2$#&! %3 ## # • Presenting a set of human pre- # " # # " # 0 %!( ! " "# "" % 1 grasp strategies commonly used
when dealing with various amounts • Due to the robot’s structure that makes do &#$# ! '# ! of object location uncertainty " #0 # $#! " $ ) #!$ !!& " " "# $( • Mostly used: direct grasp (low $#1 • " $#! # " $ #( uncertainty) and tapping (high) " #" % !( & # • Both strategies compared with a #$!)#1 “ ” Shadow Dexterous Hand 24 January 2014, King’s College London, UK
14:35–14:38 TuC1.17 14:38–14:41 TuC1.18 Guided Locomotion in 3D for Snake Push Resistance in In-hand Manipulation Robots Based on Force Optimization
Hugo Ponte, Matt Travers, and Howie Choset Junhu He, Jianwei Zhang Carnegie Mellon University University of Hamburg (TAMS)
We apply contact force optimization, • The object and fingers are in combination with gain scheduling, considered as a black box; to perturb existing gait controllers (on • Thumb is controlled to push a simulated snake robot) to perform slightly along different better in rugged three-dimensional directions; environments. • The contact force feedback is collected to estimate the robot object interaction state.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
159 Session TuC1 Grand Ballroom Tuesday, September 16, 2014, 13:30–14:50 Dynamics and Control / Manipulation and Grasping IV Chair Jonas Buchli, ETH Zurich Co-Chair
14:41–14:44 TuC1.19 14:44–14:47 TuC1.20 Online Interactive Perception of Articulated Using Environment Objects as Tools: Objects with Multi-Level Recursive Estimation Unconventional Door Opening Based on Task-Specific Priors Martin Levihn and Mike Stilman Roberto Martín Martín and Oliver Brock Georgia Institute of Technology Robotics and Biology Lab, Technische Universität Berlin
• Perceptual skill for the online perception • Robots should be able to utilize of degrees of freedom environment objects as tools • Perceives type and parameters • We present the concept of physical (orientation, position) of joints constraint propagation • Estimates uncertainty of perceived dofs • Demonstrate application to the problem of opening a jammed door • Tracks rigid bodies and joint values • Algorithm finds lever for prying the • Useful to control and monitor robot door or configurations for ramming manipulation and detect failures it with a cart
14:47–14:50 TuC1.21 Sponsor Talk: Components for Mobile Manipulation: Light-Weight Arms and Robotic Hands Christopher Parlitz SCHUNK • Modular approach and integrated components for robot applications • Open control architecture • Low power consumption • Products for today’s research and industrial service robot solutions
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
160 Session TuC2 State Ballroom Tuesday, September 16, 2014, 13:30–14:50 Humanoids and Bipeds II / Domestic and Interactive Robots Chair C. S. George Lee, Purdue University Co-Chair
13:30–13:50 TuC2.1 13:50–13:53 TuC2.2 Keynote: Human-Robot Interaction Perturbation Recovery of Biped Walking Socially Assistive Robotics by Updating the Footstep
Brian Scassellati Chenglong Fu Yale University Tsinghua University • Robots tutors take on a variety of roles: teacher, • This paper presented a strategy of student, and peer updating the footstep for humanoid • We show results for these walking to recover balance from a roles in: large perturbation. • Nutrition Education • The footstep calculator consists of three stages: perturbation detection, • Teaching ESL rapid adaption, and capturabililty • Bullying Prevention inspection. • Social Skills Training
13:53–13:56 TuC2.3 13:56–13:59 TuC2.4 Swing-Leg Retraction Efficiency in Falling Prevention of Humanoid Robots Bipedal Walking by Switching Standing Balance and S. J. Hasaneini1,2, Chris J.B. Macnab2, Hopping Motion Based on MOA Set John .E.A. Bertram2 and Henry Leung2 Ko Yamamoto1 1Cornell University 2University of Calgary 1University of Tokyo Swing-leg retraction is not always energetically favorable • The Maximal Output Admissible (MOA) set is extended to a hopping motion. • Based on the MOA set, we can adaptively switch the two types of controllers. • The falling prevention control is validated with simulations.
13:59–14:02 TuC2.5 14:02–14:05 TuC2.6 Preliminary Walking Experiments with Running into a Trap: Numerical Design Underactuated 3D Bipedal Robot MARLO of Task-Optimal Preflex Behaviors B. G. Buss1, A. Ramezani1, K. Akbari Hamed1, J. Van Why1, C. Hubicki1, M. Jones1, M. Daley2 B. A. Griffin1, K. S. Galloway 2 and J. W. Grizzle1 and J. Hurst1 1Oregon State University 2Royal 1University of Michigan, 2U.S. Naval Academy Veterinary College • Preflexes are • MARLO has 13 DOF (single-support) and 6 actuators. Feet are passive. pre-reflex behaviors • Control based on virtual constraints. for disturbance rejection in • Experiments initiated from free the presence of feedback delays standing position. • Lateral stabilization inspired by • We introduce a method for designing energy-optimal SIMBICON enabled 3D walking preflexes via trajectory optimization for efficient indoors and outdoors. legged locomotion on unpredictable terrain
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
161 Session TuC2 State Ballroom Tuesday, September 16, 2014, 13:30–14:50 Humanoids and Bipeds II / Domestic and Interactive Robots Chair C. S. George Lee, Purdue University Co-Chair
14:05–14:08 TuC2.7 14:08–14:11 TuC2.8
SLIP with swing leg augmentation as Quantifying the Trade-Offs Between Stability versus a model for running Energy Use for Underactuated Biped Walking Aida Mohammadinejad, Maziar A. Sharbafi Cenk Oguz Saglam, Katie Byl and Andre Seyfarth University of California, Santa Barbara Lauflabor locomotion lab, TU Darmstadt • We measure stability by average steps-to-failure (MFPT) • We quantify energy consumption by Cost of Transport (COT) ? • By switching between multiple controllers, we • Achievements: increase stability by Stability and robustness 129% while decreasing Similarity to humans energy consumption by Stability vs Energy Use running pattern SLIP + pendulum like swinging 29%.
14:11–14:14 TuC2.9 14:14–14:17 TuC2.10
Highly Robust Running of Articulated From Template to Anchor: A Novel Control Strategy Bipeds in Unobserved Terrain for Spring-Mass Running of Bipedal Robots
1 2 1 1 Behnam Dadashzadeh , Hamid Reza Vejdani , Albert Wu , Hartmut Geyer and Jonathan Hurst2 1 Carnegie Mellon University 1School of Engineering-Emerging Technologies, University of Tabriz, 2Dynamic Robotics Laboratory, Oregon State University • We embed the robust behavior of an abstract gait • Full dynamic model of a ݑ model in the control of a higher order robot model. Ԣ Ԣ ݍ ݍ ݍ multibody real biped robot. ݑ ܭܵܮܫܲ ݑ Ԣ ܲܫܮܵܭ ݍ ݍ Ԣ • In the spring-mass running gait model, ݍ • The active SLIP model tracks leg placement gives near-deadbeat
the SLIP model. SLIP rejection of large, unobserved Active SLIP ATRIAS CoM
• The multibody model tracks the 1.4
changes in ground height. 1.2 toe force profile of the active 1 0.8
• Simulation shows that the bipedal 0.6 y (m) SLIP model. 0.4 robot inherits this stability despite 0.2 0 • Stable and Steady Running. 0.2 0.5 0 0.5 1 1.5 2 2.5 3 3.5 modeling error and sensor noise. x (m)
14:17–14:20 TuC2.11 14:20–14:23 TuC2.12
An Estimation Model for Footstep Finding and Navigating to Household Objects with Modifications of Biped Robots UHF RFID Tags by Optimizing RF Signal Strength
Robert Wittmann1, Arne-Christoph Hildebrandt1, Travis Deyle, Matthew S. Reynolds, & Charles C. Kemp Alexander Ewald1 and Thomas Buschmann1 1Technische Universität München • Three mass estimation model with two unactuated DoFs • Stabilization unit and compliant unilateral contacts are included • Calculation of footstep modifications with the prediction results • Real-time application and PR2 robot’s final configurations after navigating to experimental results tagged objects in the Georgia Tech Aware Home
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
162 Session TuC2 State Ballroom Tuesday, September 16, 2014, 13:30–14:50 Humanoids and Bipeds II / Domestic and Interactive Robots Chair C. S. George Lee, Purdue University Co-Chair
14:23–14:26 TuC2.13 14:26–14:29 TuC2.14 RGB-D Sensor Setup for Multiple Tasks of Enhanced Robotic Cleaning Home Robots and Experimental Results with a Low-cost Tool Attachment P. de la Puente1, M. Bajones 1, P. Einramhof1, Zhe Xu and Maya Cakmak D. Wolf1, D. Fischinger1 and M. Vincze1 Computer Science & Engineering Department 1Technical University of Vienna University of Washington • Two RGB-D sensors to cover conflicting needs • Designed a universal • Adaptation of ROS navigation for the proposed setup attachment, called Griple, • Data preprocessing that makes human tools • Parameter tuning more robot-friendly. • Solving blind area problems • Demonstrated significant • Rooms and places improvements in grasping, applying, and placing 10 • SMACH-based behaviour different cleaning tools.
14:29–14:32 TuC2.15 14:32–14:35 TuC2.16
CHARM: A Platform for Algorithmic Development of a Comic Mark Based Expressive Robotics Education & Research Robotic Head Adapted to Japanese Cultural Background Surya P. N. Singh, Hanna Kurniawati, Kianoosh Tatsuhiro Kishi1,2, Hajime Futaki2, Gabriele Trovato2, Nobutsuna Endo3, Matthieu Destephe2, Sarah Cosentino2, S. Naveh, Joshua Song & Tyson Zastrow Kenji Hashimoto2 and Atsuo Takanishi2 Uni. Queensland – Robotics Design Lab 1JSPS research fellow 2Waseda university 3Osaka university • Fast Money: Autonomously • Flexible LED display and image sort moving coins to bins mechanisms are designed for
• Profitable: a diverse displaying the cartoon marks any text in the mezzanine robotics project on the robotic head image should • Low-Cost: Based on simple, • Experimental evaluation be the same widely obtainable parts shows comic marks increased size as main Engineering + Computation the emotion expression ability text Algorithmic Robotics Education of the robotic head
14:35–14:38 TuC2.17 14:38–14:41 TuC2.18 Effects of Bodily Mood Expression of a Real-Time Recognition of Pointing Robotic Teacher on Students Gestures for Robot to Robot Interaction Junchao Xu1, Joost Broekens1, Polychronis Kondaxakis1, Joni Pajarinen1, Koen Hindriks1 and Mark A. Neerincx1,2 and Ville Kyrki1 1Delft University of Technology 2TNO 1Intelligent Robotics Group, Aalto University • A robot gave a 30 minutes lecture in a • The detection is based on RGB-D university class setting. and a NAO robot is used as the • Robot mood was expressed by 41 pointing agent in the experiments. modulated coverbal gestures. • Algorithms implemented under ROS • Students’ own valence/arousal and • Developed system operates
ratings of the lecturing quality and the efficiently in Real-Time Figure 8. Robot to robot interaction scenario where NAO points at red wooden car and gesture quality were significantly Kinova’s JACO arm grasps and relocates the • Results indicate a 73% success rate object. higher in the positive mood condition. out of 330 pointing gesture attempts
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
163 Session TuC2 State Ballroom Tuesday, September 16, 2014, 13:30–14:50 Humanoids and Bipeds II / Domestic and Interactive Robots Chair C. S. George Lee, Purdue University Co-Chair
14:41–14:44 TuC2.19 14:44–14:47 TuC2.20 Adaptive Spacing Determining the Affective Body Language of in Human-Robot Interactions Older Adults during Socially Assistive HRI P. Papadakis1, P. Rives1 and A. Spalanzani2 Derek McColl and Goldie Nejat 1 Autonomous Systems and Biomechatronics Laboratory, INRIA, Sophia Antipolis, France Department of Mechanical and Industrial Engineering, 2Univ. Grenoble, LIG, France, INRIA University of Toronto, Canada • Goal: Spatially situated Human-Robot • Our work focuses on developing a socially assistive robot designed to engage older adults in the interaction. important meal-eating activity.
• A novel automated affect recognition and • Contribution: Generative model of classification system using body language features atomic/global social spacing, accounting and learning-based classifiers is developed to allow the robot to interpret affective body language during for uncertainty and perception capacity. one-on-one assistive interactions. The socially assistive
• Results from meal-time experiments with older robot Brian 2.1 and an • Experiments: Socially-compliant adults showed that the system was able to classify elderly user during the navigation in populated scenes. natural body language displays at rates up to meal-eating activity. 93.6% for arousal and 77.9% for valence.
14:47–14:50 TuC2.21 Sponsor Talk: The Eyes: A History of Baxter’s Personification Kyle Maroney Rethink Robotics
• Origin
• The Power of Personification • Indicate State • Convey Intent • Provide Comfort
• Rethink Robotics Brand
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
164 Session TuC3 Red Lacquer Room Tuesday, September 16, 2014, 13:30–14:50 Localization and Mapping III / Visual Servoing and Tracking Chair José Neira, Universidad de Zaragoza Co-Chair
13:30–13:50 TuC3.1 13:50–13:53 TuC3.2 Keynote: The SLAM Problem - A Fifteen Direction-Driven Navigation Using Year Journey ….. Cognitive Map for Mobile Robots Gamini Dissanayake Vui Ann Shim1, Bo Tian1, Miaolong Yuan1, Huajin University of Technology, Sydney Tang 1,2 and Haizhou Li1 1Institute for Infocomm Research, Singapore 2Sichuan University, China The SLAM problem has revealed many surprises since the first • To propose a direction-driven navigation system. A grid- “solutions” emerged in the late 90’s. based direction planner (as global planner) is devised This talk will chronicle the author’s to extract direction instructions journey in looking for solutions to • To propose a local planner with asymmetrical multi- SLAM through extended Kalman layered module filters, information filters, non-linear • To implement simultaneous localization and mapping optimisers and most recently linear (SLAM) and navigation of a mobile robot in an indoor least-squares. environment
13:53–13:56 TuC3.3 13:56–13:59 TuC3.4 iSPCG: Incremental SPCG for Online Real Time RGB-D Registration and SLAM with Many Loop-Closures Mapping in Texture-less Environments Yong-Dian Jian and Frank Dellaert Khalid Yousif1, Alireza Bab-Hadiashar1 and Georgia Institute of Technology Reza Hoseinnezhad1 1RMIT University, Australia • Use iSAM to solve a subgraph to • Real time 3D SLAM for texture-less obtain an approx. solution scenes using depth information only • If iSAM’s solution is unsatisfactory,y, • Developed a novel sampling method use SPCG to solve the full graph using Ranked Order Statistics to obtain the optimal solution • Extracts points carrying the most • Use SPCG’s solution to regularizee useful information for registration iSAM in the next steps • Reduces computational time while • iSPCG is efficient, consistent, andd achieving high accuracy can deliver the optimal solution
13:59–14:02 TuC3.5 14:02–14:05 TuC3.6
Online Global Loop Closure Detection Selecting Good Measurements via l1 for Multi-Session Graph-Based SLAM Relaxation: a Convex Approach for Robust Estimation over Graphs Mathieu Labbé and François Michaud 1 2 1 Université de Sherbrooke Luca Carlone , Andrea Censi , Frank Dellaert 1Georgia Institute of Technology, 2Massachusetts Institute of Technology
• Maps are merged by detecting • Outliers are not observable loop closures between sessions. if one does not assume a • Memory management approach generative model (Working Memory, Long-term • We frame outlier rejection as Memory) is used to respect real- selection of the maximal set time constraints independently of coherent measurements of the size of the environment. • We focus on pose graph optimization: measurement • RGB-D mapping. selection can be formulated as a linear program, which entails fast computation and scalability. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
165 Session TuC3 Red Lacquer Room Tuesday, September 16, 2014, 13:30–14:50 Localization and Mapping III / Visual Servoing and Tracking Chair José Neira, Universidad de Zaragoza Co-Chair
14:05–14:08 TuC3.7 14:08–14:11 TuC3.8 Hybrid Inference Optimization for Robust Robust Graph SLAM: A Comparative Pose Graph Estimation Analysis
Aleksandr Segal1 and Ian Reid2, Y. Latif 1, C. Cadena2, and J. Neira1 1University of Oxford 2University of Adelaide 1University of Zaragoza 2University of Adelaide
• New optimization algorithm for pose • Dataset for Robust SLAM evaluation based on KITTI graph estimation dataset, a total of 7 x 21 sequences • Approximate Discrete-Continuous • Comparative analysis of Robust Methods and their Inference replaces Least-Squares effect on the underlying Graph-SLAM representation solver in Gauss-Newton algorithm • Can infer outlier loop closures significantly better than competing robust techniques
14:11–14:14 TuC3.9 14:14–14:17 TuC3.10 Graph SLAM with Signed Distance Credibilist Simultaneous Localization Function Maps on a Humanoid Robot and Mapping with a LIDAR G. Trehard1, Z. Alsayed1, 1 2 1 René Wagner , Udo Frese and Berthold Bäuml E. Pollard1, B. Bradai2 and F. Nashashibi1 1German Aerospace Center (DLR) 2University of Bremen 1INRIA 2Valeo • Dense truncated signed distance A new SAM solution based on the function (TSDF) mapping/ICP Transferable Belief Model (TBM) (KinectFusion) integrated with framework is proposed in this article. sparse graph SLAM The paper aims at proving that the • SLAM optimizer moves local TSDF use of this new theoretical context sub-maps attached to reference opens a lot of perspectives for the nodes for global map deformation SLAM community • High quality large-scale maps due to improved sensor model
14:17–14:20 TuC3.11 14:20–14:23 TuC3.12 Novel Insights into the Impact of Graph Robust Model Predictive Control for Structure on SLAM Visual Servoing Kasra Khosoussi, Shoudong Huang Akbar Assa, Farrokh Janabi-Sharifi Gamini Dissanayake Department of Mechanical and Industrial Engineering CAS, University of Tech. Sydney Ryerson University
0.4 • A model predictive controller is 0.3 Graph Connectivity Achievable Accuracy 0.2
0.1
exploited for trajectory generation 0 • Number of Spanning Trees y (m) -0.1 considering the system constraints. -0.2 • Algebraic Connectivity -0.3 -0.4 -0.4 -0.2 0 0.2 0.4 • The uncertainties of the system are x (m) • Average Degree Uncompensated 0.4 estimated and compensated. 0.3 0.2 0.1
• An online controller is employed to 0 y (m) • Applications: Graph Pruning, Active SLAM -0.1 control the robot towards the goal -0.2 -0.3
-0.4 • Applicable to Estimation Problems in Sensor Networks -0.4 -0.2 0 0.2 0.4 using the generated trajectories. x (m) Compensated
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
166 Session TuC3 Red Lacquer Room Tuesday, September 16, 2014, 13:30–14:50 Localization and Mapping III / Visual Servoing and Tracking Chair José Neira, Universidad de Zaragoza Co-Chair
14:23–14:26 TuC3.13 14:26–14:29 TuC3.14 Prescribed Performance Image Based Visual Monocular Template-based Vehicle Servoing under Field of View Constraints Tracking for Autonomous Convoy Driving
Shahab Heshmati-alamdari, Charalampos P. Bechlioulis, Minas V. Liarokapis and Kostas J. Kyriakopoulos Carsten Fries and Hans-Joachim Wuensche National Technical University of Athens University of the Bundeswehr Munich
• A novel IBVS scheme that imposes prescribed • Main goal: Vision-based autonomous convoy driving transient and steady state response on the image feature coordinate errors. • Paper-specific goal: Monocular vehicle tracking • Providing an error transformation that converts • 3D template models the original constrained problem of IBVS into an equivalent unconstrained one. • Cascade classifiers • Satisfying the Visibility constraints. • Haar, LBP, HOG • Very low computational complexity which makes implementation on fast embedded • Unscented Kalman filter control platforms straightforward. • Dynamic region growing
14:29–14:32 TuC3.15 14:32–14:35 TuC3.16 Real-time Object Pose Recognition and Robust Ground Surface Map Generation Tracking with an Imprecisely Calibrated Using Vehicle-Mounted Stereo Camera Moving RGB-D Camera Kouma Motooka1, Shigeki Sugimoto1, Karl Pauwels1, Vladimir Ivan2, Masatoshi Okutomi1 and Takeshi Shima2 Eduardo Ros1 and Sethu Vijayakumar2 1Tokyo Institute of Technology 2Hitachi Ltd. 1 2 Incremental ground surface Univ. of Granada, Spain Univ. of Edinburgh, UK •A direct approach to ground & ego-motion estimation surface map generation. • 40 Hz pose updates tracking • Combinational use of with >100 objects result feature- and area-based • multi-object and methods for robustness. manipulator pose with • Friendly to off-road mobile- implicit occlusion robot applications: e.g. handling traversable area detection. Ground surface map
14:35–14:38 TuC3.17 14:38–14:41 TuC3.18 RGB-D Fusion: Real-time Robust Bearings-only Path Following with a Tracking and Dense Mapping with Vision-based Potential Field RGB-D Data Fusion Deon Sabatta1,2 and Roland Siegwart2 Seong-Ohor Two Lee, LinesHwasup Lim, 1CSIR, South Africa 2ETH Zurich, Switzerland Hyoung-Gon Kim and Sang Chul Ahn Korea Institue of Science and Technology • We present a vision-based teach- image and-replay path following algorithm. • We present RGB-D Fusion which robustly • The algorithm uses feature any text in the tracks and reconstructs bearings to construct a potential image should dense textured field which is then minimised by be the same surfaces of scenes by a controller. size as main integrating both color • The algorithm is demonstrated on text and depth images. RGB-D Fusion KinectFusion a 400m outdoor urban path.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
167 Session TuC3 Red Lacquer Room Tuesday, September 16, 2014, 13:30–14:50 Localization and Mapping III / Visual Servoing and Tracking Chair José Neira, Universidad de Zaragoza Co-Chair
14:41–14:44 TuC3.19 14:44–14:47 TuC3.20 Event-based, 6-DOF Pose Tracking Learning Visual Feature Descriptors for for High-Speed Maneuvers Dynamic Lighting Conditions Elias Mueggler, Basil Huber Nicholas Carlevaris-Bianco and Ryan M. Eustice and Davide Scaramuzza University of Michigan University of Zurich • Method to learn visual feature • Event-based tracking during descriptors that are robust to high-speed maneuvers such as changes in lighting quadrotor flips Feature Tracks • Improves performance • Rotational speeds of 1200/s compared to SIFT and SURF on challenging long-term dataset Descriptor Learning
14:47–14:50 TuC3.21 Detection of Small Moving Objects Using a Moving Camera
Moein Shakeri1, Hong Zhang1, 1University of Alberta, Edmonton, Canada
• Steps: image (1) Motion compensation by two
kinds of registration methods on any text in the Wavelet components in two levels, image should (2) GMM algorithm with a be the same combination of a component-based size as main technique and pixel based learning text framework, and (3) Particle filter to optimize the performance.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
168 Session TuD1 Grand Ballroom Tuesday, September 16, 2014, 15:00–16:20 Actuators / Kinematics and Mechanism Design II Chair Venkat Krovi, University at Buffalo (SUNY Buffalo) Co-Chair
15:00–15:20 TuD1.1 15:20–15:23 TuD1.2 Keynote: Robots for Interaction with Soft Pneumatic Actuator Skin with Humans and Unknown Environments Embedded Sensors Alin Albu-Schäffer Chansu Suh1, Jordi Condal Margarit2, DLR, Institute of Robotics and Mechatronics Yun Seong Song1 and Jamie Paik1 1École Polytechnique Fedérale de Lausanne • The talk will discuss how robot design evolves to enable safe and robust interaction with humans and The Soft Pneumatic Actuator skin (SPA-skin) is an ultra-thin (< 1 mm) image how robotics and biomechanics can benefit from distributed actuator. As various each other. actuation points can have embedded any text in the sensors, the SPA-skin can work as image should both input and output hardware for be the same diverse wearable robotics application size as main including human machine interfacing, text vibro-tactile feedback device and distributed soft surface sensor.
15:23–15:26 TuD1.3 15:26–15:29 TuD1.4
Towards Variable Stiffness Control of A Multiplex Pneumatic Actuator Drive Method Based Antagonistic Twisted String Actuators on Acoustic Communication in Air Supply Line Dmitry Popov, Igor Gaponov, Koichi Suzumori1, Naoto Osaki2, Jumpei Misumi2, and Jee-Hwan Ryu Akina Yamamoto2 and Takefumi Kanda2 Korea University of Technology and Education 1Tokyo Institute of Technology, 2Okayama University • A new type of variable stiffness actuator powered by • A new control method for pneumatic twisted string is introduced. system is proposed, which removes • Simultaneous position/tension control law is proposed. electrical control lines in pneumatic mechatronics. • Acoustic communication and power supply device for each local module are developed. • The prototype works very well.
15:29–15:32 TuD1.5 15:32–15:35 TuD1.6 A Low-Friction Passive Fluid Transmission Intermittent self-closing mechanism for a and Fluid-Tendon Soft Actuator MACCEPA-based SPEA John P. Whitney1, Matthew F. Glisson1, Glenn Mathijssen, R. Furnémont, B. Brackx, R. Eric L. Brockmeyer1, and Jessica K. Hodgins1 Van Ham, D. Lefeber, and B. Vanderborght 1Disney Research, Pittsburgh, PA, USA Vrije Universiteit Brussel, Belgium • Passive hydrostatic transmission: • Self closing guides provide antagonist pairs of leak-free, low- intermittent motion to recruit parallel stiction rolling diaphragm cylinders, springs in succession. air or water working fluid • Motor torque and energy • Water-filled: stiff, completely consumption lowered due to variable backdrivable, high force bandwidth, load cancellation. zero backlash, haptic qualities • Bi-directional output torque and • Soft-actuator design demonstrated variable stiffness.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
169 Session TuD1 Grand Ballroom Tuesday, September 16, 2014, 15:00–16:20 Actuators / Kinematics and Mechanism Design II Chair Venkat Krovi, University at Buffalo (SUNY Buffalo) Co-Chair
15:35–15:38 TuD1.7 15:38–15:41 TuD1.8 Resonant Parallel Elastic Actuator for Smart Braid: Air Muscles that Measure Biorobotic Applications Force and Displacement Angelo Sudano1, Nevio Luigi Tagliamonte1, Wyatt Felt1, C David Remy1, Dino Accoto1 and Eugenio Guglielmelli1 1University of Michigan 1Università Campus Bio-Medico di Roma • In several biorobotic applications it • By making the mesh of an Air is necessary to efficiently produce Muscle out of conductive fibers, we oscillatory motions can detect the contraction and force • We developed a compact axial flux output. miniature motor integrating a • The inductance increases with the
parallel magnetic spring 10 mm changing alignment of the fibers • The motor can oscillate at 8.5 Hz, • The resistance increases with the with an amplitude of 40, absorbing strain from the force and pressure 860 mW.
15:41–15:44 TuD1.9 15:44–15:47 TuD1.10 Variable Stiffness Fabrics with A Flexible Passive Joint for Embedded Shape Memory Materials for Robotic Fish Pectoral Fins Wearable Applications 1 1 Thomas P. Chenal1,2, Jennifer C. Case1, Sanaz Bazaz Behbahani and Xiaobo Tan 1 Jamie Paik2 and Rebecca K. Kramer1 Michigan State University 1Purdue University 2EPFL • Novel design of a flexible joint that • New, fast and simple way enables the pectoral fin to sweep back of producing thermally passively to minimize the drag activated variable stiffness fibers/fabrics. • Dynamic modeling of the robotic fish propelled by the novel flexible joint • One order of magnitude change in bending • Comparison of the performance of the stiffness within less than robotic fish between the novel flexible 15 seconds. joint and traditional rigid joint
15:47–15:50 TuD1.11 15:50–15:53 TuD1.12 Formulation and optimization of pulley-gear-type Design, Principles, and Testing of a SMA heat engine toward microfluidic MEMS motor Latching Modular Robot Connector H. Aono1, R. Imamura1, O. Fuchiwaki1, Y. Yamanashi1, K. F Böhringer2 Nick Eckenstein, Mark Yim 1 Dept. of Mechanical Engine., Yokohama National University (YNU) 2 Dept. of Electrical Engine., University of Washington (UW). University of Pennsylvania
Idle gear Nut • New 2D Latching Connector Design • Smaller gear A for high error tolerance reconfigurationn Fix Larger gear B Fix of modular robots Pulley A Pulley B • Design parameters of interest Coil spring SMA • looped over pulleys examined Housing • Force characteristics tested and Bearing Axis (Screw) analyzed !! %" • Reconfiguration of multiple types #& "& " performed with modular robots $&!
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
170 Session TuD1 Grand Ballroom Tuesday, September 16, 2014, 15:00–16:20 Actuators / Kinematics and Mechanism Design II Chair Venkat Krovi, University at Buffalo (SUNY Buffalo) Co-Chair
15:53–15:56 TuD1.13 15:56–15:59 TuD1.14
Long and Slim Continuum Robotic Kinetostatic Optimization for an Adjustable Four-Bar Cable Based Articulated Leg-Wheel Subsystem
Manas Tonapi1, Isuru Godage1 and Aliakbar Alamdari, Javad Sovizi, Ian Walker1 1Clemson University Seung-kook Jun and Venkat Krovi State University of New York at Buffalo • Novel design for constructing multi- • Articulated leg-wheel design based section continuum robots on adjustable four-bar mechanism. • Thin (less than 1 cm diameter) and • Kinematic optimization to match relatively long length (more than 100 desired wheel-axle motion profile.
Stretch ratio and Joint Angular displacement
cm) Stretch ratio K • Subsequent static optimization of 1 0.8 (rad)
0.6 • Compact actuation assembly spring assist to reduce actuation. 0.9 (rad)
0.4 • New 2D forward kinematic model • Evaluation of multiple alternate 0.8
0.2 Stretch ratio K, Crank Link Adjustment and its validation active-adjustment configurations. 0.7 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Time (sec)
15:59–16:02 TuD1.15 16:02–16:05 TuD1.16 A Single DOF arm for transition of climbing Design of Variable Release Torque-based robots between perpendicular planes Compliant Spring-clutch 1 1 Carlos Viegas , Mahmoud Tavakoli , Jushin Seok1, Sungchul Kang2 and Woosub Lee2 1 Institute for Systems and Robotics, University of Coimbra, 1 Portugal University of Science and Technology 2 • An innovative transmission Korea Institute of Science and Technology mechanism driving simultaneously • VCSC is a safe joint of robot. two joints with a single actuator • VCSC has a release mechanism.
• An electromagnet adhesion unit • VCSC has a constant release adaptable to both flat and curved torque without gravity compensator. structures. • VCSC can estimate an external torque by using distance sensor. • VCSC is designed for small and Prototype of light robot like a mannequin. VCSC
16:05–16:08 TuD1.17 16:08–16:11 TuD1.18 Principles of Microscale Flexure Hinge Strengthening of 3D Printed Robotic Parts Design for Enhanced Endurance via Fill Compositing Ronit Malka2, Alexis Lussier Desbiens1, Yufeng Joseph T. Belter & Aaron M. Dollar Chen2, and Robert J. Wood2 Yale University 1Université de Sherbrooke, 2Harvard University • 3D printed part strength was increased by up to ● Laminated flexure hinges are 45% compared to standard ABS FDM Printing increasingly popular in image microrobotics. • Simple process of fill compositing and testing any text in the results are presented • This paper evaluates various image should techniques to increase their be the same lifespan. size as main • The Robobee wing hinge text lifespan was increased from 70,000 to 2,000,000+cycles
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
171 Session TuD1 Grand Ballroom Tuesday, September 16, 2014, 15:00–16:20 Actuators / Kinematics and Mechanism Design II Chair Venkat Krovi, University at Buffalo (SUNY Buffalo) Co-Chair
16:11–16:14 TuD1.19 16:14–16:17 TuD1.20 Cogeneration of Mechanical, Electrical, and Design of a robotic finger using series Software Designs for Printable Robots gear chain mechanisms Ankur Mehta1, Joseph DelPreto1, Yuuki Mishima1, Ryuta Ozawa1, Benjamin Shaya1 and Daniela Rus1 1Ritsumeikan University 1Massachusetts Institute of Technology • Allow novices to quickly generate • An underactuated finger is designed image robots from structural descriptions by using special gear chains.
• Modularize electronics and • These chains enables the finger to any text in the mechanical structures to create an realize coupling motions and image should integrated electromechanical library adaptive curling. be the same • Hierarchically compose blocks • The mechanisms are useful in size as main • Automatically generate layout, decreasing the size and weight and text software, and user interface in simplifying the assembly.
16:17–16:20 TuD1.21 Sponsor Talk: The Next Research Revolution with KUKA’s Robotic Reference Platforms Corey T. Ryan KUKA Robotics Corp
• KUKA’s technology is changing the focus of some research • New technologies and different product development plans can add functionality and capabilities suited to different research strategies
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
172 Session TuD2 State Ballroom Tuesday, September 16, 2014, 15:00–16:20 Reasoning and AI Planning / Path and Task Planning Chair Sam Ade Jacobs, ABB Inc Co-Chair
15:00–15:20 TuD2.1 15:20–15:23 TuD2.2 Keynote: Symbiotic Mobile Robot Prior-Assisted Propagation Of Spatial Autonomy in Human Environments Information for Object Search Manuela Veloso Malte Lorbach1, Sebastian Höfer1, Oliver Brock1 Carnegie Mellon University 1Technische Universität Berlin
• Robust Episodic Non-Markov • Improve object search efficiency by Localization in varying indoor reasoning about possible locations (with Joydeep Biswas) spaces • We suggest five priors that capture • Multirobot task scheduling with structure of the physical world transfers (with Brian Coltin) • A probabilistic inference model • Learning from human interaction propagates prior knowledge across locations and and the web (with Vittorio Perera) generates consistent beliefs over object locations • Autonomous data acquisition • Experiments in a simulated environment demonstrate and mapping (with Richard improved search efficiency Wang) 15:23–15:26 TuD2.3 15:26–15:29 TuD2.4
Combining Top-down Spatial Reasoning and Bottom-up Learning Relational Affordance Models Object Class Recognition for Scene Understanding for Two-Arm Robots
1 1 2 2 L. Kunze , C. Burbridge , M. Alberti , A. Tippur , Bogdan Moldovan1, Luc De Raedt1 J. Folkesson2, P. Jensfelt2, N. Hawes1 1 1University of Birmingham, UK 2KTH Royal Institute of Technology, SW KU Leuven, Belgium
• Understanding scenes based on • Extend relational affordance model perception only is a difficult task to continuous domain • Spatial background knowledge can • Develop pipeline for table-top two- provide additional information arm manipulation • We combine a 3D object class • Build two-arm model from single- recognition system with learned, spatial arm babbling data, symmetry Two-arm actions models of object relations assumptions, and background rules for object • Experiments show that our approach placement can improve the task performance • Two-arm action prediction task
15:29–15:32 TuD2.5 15:32–15:35 TuD2.6 Cognitive Factories with Multiple Teams of Incorporating Kinodynamic Constraints Heterogeneous Robots: Hybrid Reasoning to Automated Design of Simple Machines for Optimal Feasible Global Plans Can Erdogan Mike Stilman Zeynep G. Saribatur, Esra Erdem and Volkan Patoglu Georgia Institute of Technology Sabanci University, Istanbul, Turkey • Each team can compute task plans with minimum total • Manipulation of multi-body objects action cost, and makespan. Heterogeneity of robots and for mechanical lever feasibility checks are considered during planning. • Robot joint and torque limits
• An optimal feasible global plan is computed with a semi- • Levernberg-Marquardt optimization distributed approach: (i) A neutral mediator finds an using factor graph representation optimal coordination of the teams, (ii) all teams compute • Results: Lever-fulcrum systems their own optimal local feasible plans in parallel, (iii) local that overturn 100 kg loads and plans are decoupled into an optimal feasible global plan. push 240 kg obstacles
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
173 Session TuD2 State Ballroom Tuesday, September 16, 2014, 15:00–16:20 Reasoning and AI Planning / Path and Task Planning Chair Sam Ade Jacobs, ABB Inc Co-Chair
15:35–15:38 TuD2.7 15:38–15:41 TuD2.8 Unifying Multi-Goal Path Planning for Stochastic Collection and Replenishment Autonomous Data Collection (SCAR) Optimisation for Persistent Autonomy Jan Faigl1, Geoffrey A. Hollinger2 Andrew W Palmer1, Andrew J Hill1, 1Czech Technical University, Czech Republic and Steven J Scheding1 2Oregon State University, United States 1Australian Centre for Field Robotics, USyd, AUS • Prize-Collecting Traveling • Combinatorial schedule optimisation Salesman Problem with of a refuelling robot with uncertainty Neighborhoods (PC-TSPN) • Ratio objective function better than • Novel self-organizing map existing methods based optimization algorithm • Minimises risk of running empty • Improved solution quality • Examples include mining vehicles • Lower computational and water/fuel trucks, aerial requirements Evaluation scenario based on Ocean refuelling, surveillance, etc. Observatories Initiative Endurance Array
15:41–15:44 TuD2.9 15:44–15:47 TuD2.10 Coverage Planning with Coordination in Human-Robot Teams Using Finite Resources Mental Modeling and Plan Recognition Kartik Talamadupula1, G. Briggs2, T. Chakraborti1, Grant P Strimel1, Manuela M Veloso1, M. Scheutz2 and S. Kambhampati1 1Carnegie Mellon University 1Arizona State University 2Tufts University • Introduce a new sweeping planning • Coordination is essential in human-robot teaming algorithm BC Sweep • Beliefs can be used to infer an agent’s intentions • Builds on boustrophedon cellular • Intentions can be used along with a domain model to decomposition coverage predict the plan and goals of an agent • Accounts for fixed fuel/battery capacity of • Information extracted from the predicted plan is used the robot and service station recharges to coordinate the robot’s actions with human agents • Provably complete and illustrate method • Plan recognition used to fold in action observations with real maps • Implemented and evaluated on a PR2 robot
15:47–15:50 TuD2.11 15:50–15:53 TuD2.12 A Framework for Formal Specification of Robotic Synthesizing Manipulation Sequences for Constraint-based Tasks and their Concurrent Execution with Online QoS Monitoring Under-Specified Tasks using Unrolled MRFs E. Scioni1,2, G. Borghesan1, Jaeyong Sung, Bart Selman, Ashutosh Saxena 1,3 2 H. Bruyninckx and M. Bonfè Cornell University 1University of Leuven 2University of Ferrara 3Eindhoven University of Technology • Inferring the sequence of • Formulation of Quality of Service steps where the goals are (QoS) as online criteria to monitor under-specified and have to and evaluate a constraint-based task be inferred from the context. execution • Task classification to aid the • An attribute-based coordination model synthesis (FSM). representation of the • Concurrent tasks execution while environment for task planning. QoS is preserved. • A graph-based representation • Experiments using KUKA youBot of a dynamic plan by unrolling mobile platform on pick&place the loop into a MRF. application
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
174 Session TuD2 State Ballroom Tuesday, September 16, 2014, 15:00–16:20 Reasoning and AI Planning / Path and Task Planning Chair Sam Ade Jacobs, ABB Inc Co-Chair
15:53–15:56 TuD2.13 15:56–15:59 TuD2.14 Multi-Goal Path Planning based on the A Probability-based Path Planning Method Using Fuzzy Logic Generalized TSP with Neighborhoods 1 1 Jaeyeon Lee Kevin Vicencio , Brian Davis , and Electrical engineering, University of Texas at Dallas, USA. Iacopo Gentilini1 Wooram Park 1 Mechanical engineering, University of Texas at Dallas, USA. Embry-Riddle Aeronautical University • The path-of-probability(POP) method has • Multi-goal path planning problems been successfully used for robot path with non-connected or clustered plannning. • One drawback of POP is discrete search for target domains. each intermediate path. • Novel disjunctive formulation for the • The fuzzy logic converts the discrete search Generalized TSP with to a continuous one. • We verified the performance of the POP Neighborhoods (GTSPN). combined with fuzzy logic. A path planning method using POP and fuzzy logic • Solution procedure via genetic algorithm and crossover operators. GTSPN Instance
15:59–16:02 TuD2.15 16:02–16:05 TuD2.16 A Multi-Tree Extension of Informed RRT*: Optimal Sampling-based Path the Transition-based RRT Planning Focused via Direct Sampling of an Admissible Ellipsoidal Heuristic Didier Devaurs, Thierry Siméon and Jonathan D. Gammell1,
Juan Cortés Siddhartha S. Srinivasa2 and Timothy D. Barfoot1 LAAS-CNRS and Univ de Toulouse, France 1University of Toronto 2Carnegie Mellon University • Multi-T-RRT: multiple-tree variant • RRT* asymptotically finds the of the Transition-based RRT optimal paths from the start to every state in the problem domain. • Anytime behavior: useful cycles • For shortest-path problems, the • Solve ordering-and-pathfinding states that can improve a solution problems in continuous cost form an ellipse. spaces (visit a set of waypoints) • We present a method to directly • Ex.: industrial inspection with an sample these ellipses, improving aerial robot in a large workspace performance across a wide-range of problems and state dimensions.
16:05–16:08 TuD2.17 16:08–16:11 TuD2.18 Integrating multiple soft constraints for Sampling-based Trajectory Imitation in planning practical paths Constrained Environments using Laplacian-RRT* Jing Yang, Patrick Dymond, Thomas Nierhoff1, Sandra Hirche1 and Michael Jenkin Yoshihiko Nakamura2 York University 1TU Munich 2University of Tokyo • Optimization of sampling-based • Goal: Find similar trajectories planners is complex due to the large while avoiding obstacles range of potential optimizers. • Approach: Incremental RRT*- • An auction-based scheme is based method with a novel developed that allows potential metric for velocity/acceleration optimizers to compete. differences • Approach is validated on high DOF • Result: Successful evaluation tentacle robots. on HRP-4 for a pick-and-place scenario
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
175 Session TuD2 State Ballroom Tuesday, September 16, 2014, 15:00–16:20 Reasoning and AI Planning / Path and Task Planning Chair Sam Ade Jacobs, ABB Inc Co-Chair
16:11–16:14 TuD2.19 16:14–16:17 TuD2.20 The Anatomy of a Distributed Motion Safest Path Adversarial Coverage Planning Roadmap Sam Ade Jacobs1 and Nancy Amato2
1ABB 2Texas A&M University R. Yehoshua, N. Agmon, G. A. Kaminka Computer Science Dept., Bar Ilan University • Parallel and distributed systems are ubiquitous (including robots) • Robot must visit every point in a • Parallel and distributed motion target area that contains threats planning algorithms are needed • Goal: find a coverage path that • We present a comparative study of maximizes robot’s survivability roadmaps from sequential and parallel • Real-world applications: demining, planners hazardous fields exploration • Results show that heterogeneous • Suggested two heuristic algorithms Coverage paths in an evironments are appropriate for spatial for finding a safest coverage path adversarial environment subdivision parallel processing
16:17–16:20 TuD2.21
Planning with the STAR(s) K. Karydis1, D. Zarrouk2, I. Poulakakis1, R. Fearing3 and H. Tanner1 1Univ. of Delaware, USA; 2Ben Gurion Univ., Israel; 3Univ. of California, Berkeley, USA • Enabling motion planning methods to the novel robot STAR • Experimental validation of unicycle models for the STAR • Characterization of the open-loop performance of the robot executing pre-computed motion plans
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
176 Session TuD3 Red Lacquer Room Tuesday, September 16, 2014, 15:00–16:20 Sensing I / Sensing for Human Environments Chair Dezhen Song, Texas A&M University Co-Chair
15:00–15:20 TuD3.1 15:20–15:23 TuD3.2
Keynote: Life In a World of Ubiquitous Augmenting Bayes filters with the Relevance Vector Machine Sensing for time-varying context-dependent observation distribution Greg Hager Alexandre Ravet1, Simon Lacroix1, Johns Hopkins University and Gautier Hattenberger2 1LAAS-CNRS 2ENAC Sensing technology is becoming smaller, more granular, more • Explicitly introduce context capable and nearly pervasive. influence in Bayes filters Where will this take us? What are • 'Intelligent' measurement selectionn the implications for robotics? Will + observation noise prediction this lead to new opportunities to • Contrasts with typical state- aid the aged, the sick or disabled, dependent models as well as all of the rest of us? Can we benefit from data but preserve privacy?
15:23–15:26 TuD3.3 15:26–15:29 TuD3.4 Audio Visual Classification and Detection Object Shape Categorization in RGBD Images using of Human Manipulation Actions Hierarchical Graph Constellation Models based on Unsupervisedly Learned Shape Parts described by a Alessandro Pieropan, Giampiero Salvi, Set of Shape Specificity Levels Karl Pauwels and Hedvig Kjellström C. A. Mueller, K. Pathak and A. Birk Royal Institute Of Technology, Sweden Jacobs University Bremen, Germany Dataset • Shape parts are classified to a set of symbols • Classifying human overview on different specificity levels based on their actions using multiple surface-structural appearance sensor modalities outperforms single • Hierarchical graphical models source classification are generated which reflect the constellation of classified parts • New publicly available for different shape categories evaluation dataset • Experiments show an enhanced classification compared to a flat approach
15:29–15:32 TuD3.5 15:32–15:35 TuD3.6 sEMG-based Decoding of Human Multi-Target Visual Tracking Intentions robust to the Change of with Aerial Robots Electrode Position changes Pratap Tokekar1, Volkan Isler1 and Antonio Franchi2 Myoung Soo Park1, 1University of Minnesota, U.S.A 2 1Korea Inst. of Science and Technology (KIST) LAAS-CNRS, France • Performance of an sEMG decoder is • Scenario: Aerial robots tasked with dependent on electrode positions tracking mobile ground targets. when it is trained, so the changes • Problem 1: Track all targets while may make the decoder useless one. maintaining an upper bound on the • A new supervised feature extraction deviation from the optimal tracking based on the ICA is proposed, using quality. Shown to be infeasible. Simulations and which the old decoder performs well • Problem 2: Maximize the number of Experiments with only after matching old/new feature tracks with a given bound on quality. a team of from electrode position changes. We present a 2 approximation. quadrotor UAVs
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
177 Session TuD3 Red Lacquer Room Tuesday, September 16, 2014, 15:00–16:20 Sensing I / Sensing for Human Environments Chair Dezhen Song, Texas A&M University Co-Chair
15:35–15:38 TuD3.7 15:38–15:41 TuD3.8 Opportunistic Sampling-based Planning Ear-based Exploration on Hybrid for Active Visual SLAM Metric/Topological Maps S. Chaves1, A. Kim2, and R. Eustice1 Qiwen Zhang 1, David Whitney 1, Florian Shkurti 1, 1University of Michigan, 2ETRI S. Korea and Ioannis Rekleitis1 1School of Computer Science, McGill University • Gaussian process for saliency prediction and probabilistic • Ear-based exploration facilitates modeling of loop-closure utility loop-closures • Sampling-based planning with • GVG is used to navigate through the information filtering for path search environment and to identify distinct and evaluation places for localization • Opportunistic optimization process • Localizing only at meetpoints for selecting loop-closure revisit ensures computational efficiency actions during SLAM • Code available online
15:41–15:44 TuD3.9 15:44–15:47 TuD3.10 Fast and Effective Visual Place Recognition A linear approach to visuo-inertial fusion using Binary Codes and Disparity Information for homography filtering and estimation R. Arroyo1, P. F. Alcantarilla2, L. M. Bergasa1, Alexandre Eudes1, Pascal Morin1 J. J. Yebes1 and S. Bronte1 1ISIR, UPMC/CNRS UMR 7222, France 1University of Alcalá 2Toshiba Research Europe • Novel visual loop closure • Context: Real-time planar visual detection method (ABLE-S) tracking from one camera and IMU using D-LDB descriptor. • Objectives: Homography filtering, • Tested on the challenging estimation of velocity, direction of KITTI Odometry dataset. gravity, normal and scale factor • Precision superior in 25% to • Main results: Linear formulation, FAB-MAP, 23% to WI-SURF uniform observability and stability and 16% to BRIEF-Gist. analysis, luenberger linear observer
15:47–15:50 TuD3.11 15:50–15:53 TuD3.12 Fusion of Optical Flow and Inertial Meas. Cameraman Robot: Dynamic Trajectory Tracking for Robust Egomotion Estimation with Final Time Constraint using State-time Space Stochastic Approach Bloesch, Omari, Fankhauser, Sommer, Gehring, Igi Ardiyanto and Jun Miura Hwangbo, Hoepflinger, Hutter, Siegwart Toyohashi University of Technology, Japan Autonomous Systems Lab, ETH Zürich • Visual-inertial state estimation with • We present an algorithm for a optical flow cameraman robot as the dynamic trajectory tracking problem. • Focus on velocity and inclination • The task is to follow a trajectory angle estimation for taking the video of an actor. • Only frame-to-frame tracking and no • Our approach generates tree- landmark estimation based robot control considering • Unscented Kalman filtering obstacles, trajectory cost, and actor’s visibility in a 3D time- space.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
178 Session TuD3 Red Lacquer Room Tuesday, September 16, 2014, 15:00–16:20 Sensing I / Sensing for Human Environments Chair Dezhen Song, Texas A&M University Co-Chair
15:53–15:56 TuD3.13 15:56–15:59 TuD3.14
Automatic Detection and Verification of Pipeline Grasping Point Selection on an Item of Crumpled Clothing Construction Features with Multi-modal data Based on Relational Shape Description 1 1 T. Vidal-Calleja , J. Valls Miro , Kimitoshi Yamazaki, Shinshu University, Japan F. Martin2, D. Lingnau3 and D. Russell3 1 2 3 UTS:CAS Carlos III Univ. Russell NDE Inc. • We propose a method to select • A framework to locate two grasp points from an item of clothing that is randomly placed. pipeline’s Construction • The method is not influenced by Features (CF) for inspection any variety of appearance such with NDT sensors as color or texture. • Independent CF detection • The method makes it possible to with NDT sensor and camera simplify the manipulation • Verification based on both procedure for picking up and Input data Sought similar spreading a wrinkled cloth & selected shape from modalities grasp points learning data
15:59–16:02 TuD3.15 16:02–16:05 TuD3.16 A Solution to Pose Ambiguity of Visual On Leader Following and Classification Markers Using Moiré Patterns Hideyuki Tanaka1, Yasushi Sumi1 Procopio Stein1, Anne Spalanzani12, and Yoshio Matsumoto1 Vitor Santos3 and Christian Laugier1 1AIST, Japan 1INRIA 2Univ. Grenoble Alpes 3Univ. Aveiro
• Novel visual marker “LentiMark” • Leader following can enhance robot which uses lenticular lenses navigation in dynamic environments. • World’s first small planar marker • But who should the robot follows? solving pose ambiguity problem • This works uses machine learning • Design and performance of the to classify leaders and to study marker are described their characteristic features • LentiMark brings great benefits to many applications
16:05–16:08 TuD3.17 16:08–16:11 TuD3.18 Complexity–based Motion Features and Enhancement of Layered HMM Their Applications to Action Recognition by by Brain-inspired Feedback Mechanism Hierarchical Spatio–temporal Naïve Bayes Classifier Woo Young Kwon 1 and Il Hong Suh1, Sang Hyoung Lee, Min Gu Kim, and Il Hong Suh 1Hanyang University, Korea Hanyang University, Seoul, Korea
• This paper presents complexity– • To further enhance the performance based motion feature and of a LHMM, we propose a brain- hierarchical spatio–temporal inspired feedback mechanism. naïve Bayes classifier. • For this achievement, the semantic • A certain part of the trajectory is information (i.e., labels of data) is more important than other parts. used to improve the performances • The amount of importance can be by the feedback mechanism. [Feedback Process computed by complexity measure. • This LHMM is validated using of LHMM] several cooking activities of a human.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
179 Session TuD3 Red Lacquer Room Tuesday, September 16, 2014, 15:00–16:20 Sensing I / Sensing for Human Environments Chair Dezhen Song, Texas A&M University Co-Chair
16:11–16:14 TuD3.19 16:14–16:17 TuD3.20 Guiding Computational Perception Classification and Identification of Robot through a Shared Auditory Space Sensing Data based on Nested Infinite GMMs Yoko Sasaki1, Naotaka Hatao1, Eric Martinson, Ganesh Yalla Shogo Tsurusaki2 and Satoshi Kagami1 Toyota InfoTechnology Center, USA 1AIST 2Tokyo University of Science
• Combining human and Sound Source Pointing Speech • demonstrates experimental robot audition to improve Localization Detection Recognition proofs of the classification LeftLeft sound source localization Right and identification of robot ForwardForward • Demonstrated sensing data using nested infinite GMMs. improvement with • Test three different data: multiple sources human trajectories, 3D objects and audio events Improved • Useful for Blind users Target • The results show the model naturally describes the makes queries about the Localization needed numbers of Gaussians and classes for varied environment sensor data from the observed vectors
16:17–16:20 TuD3.21 Localization of Multiple Sources from a Binaural Head in a Noisy Environment Alban Portello1,2, Gabriel Bustamante1,2, Patrick Danès1,2 and Alexis Mifsud2 1Univ Toulouse 3 UPS 2LAAS-CNRS France Maximum Likelihood Estimator of multiple sources azimuths under W-Disjointness Orthogonality • EM algorithm, • to handle scattering, • left & right HRTFs • environment noise statistics
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
180 Session TuE1 Grand Ballroom Tuesday, September 16, 2014, 16:50–17:55 Constrained and Underactuated Robots / Legged Robots I Chair Martin Buehler, Vecna Technologies Co-Chair
16:50–17:10 TuE1.1 17:10–17:13 TuE1.2 A Novel Continuum-Style Robot with Keynote: Robot Motion Optimization Multilayer Compliant Modules Frank C. Park Peng Qi, Chen Qiu, Hongbin Liu, Jian S. Dai, Seoul National University Lakmal Seneviratne, Kaspar Althoefer King’s College London The state-of-the-art in dynamics- based robot motion optimization, • Novel design of continuum-style and more generally the use of robot decoupling contraction and optimal control techniques in bending motion is presented. robotics, is reviewed. Dimension • Large linear bending motion and reduction techniques, and recent avoidance of friction between joints work on statistical learning-based achieved. approaches to optimal robot motion • Screw theory based analytical generation, are also described. Double-layer module method to study the compliance & Robot assembly. characteristics applied.
17:13–17:16 TuE1.3 17:16–17:19 TuE1.4 A Fish-like Locomotion Model in an Ideal Fluid with MR Compatible Continuum Robot Based on Lateral-line-inspired Background Flow Estimation Closed Elastica with Bending and Twisting Yiming Xu1 and Kamran Mohseni2 Atsushi Yamada1, Shigeyuki Naka1, 1MAE, University of Florida 2MAE, ECE, Institute for Shigehiro Morikawa1 and Tohru Tani1 Networked Autonomous Systems, University of Florida 1Shiga University of Medica Science • Locomotion model of deforming • A novel continuum robot fish-like swimmer • Combination of a flexible pipe and a closed loop arm • Lateral-line-inspired background • Prototype features are flow estimation *MR compatible • Internal force for quantitative *3mm outer radius control effort and efficiency *0.2 mm wall thickness analysis
17:19–17:22 TuE1.5 17:22–17:25 TuE1.6 Trajectory Optimization of Flapping The Use of Unicycle Robot Control Wings Modeled as A Three Degree-of- Strategies for Skid-Steer Robots Freedoms Oscillation System Through the ICR Kinematic Mapping Jesse Pentzer1, Sean Brennan1, Yi Qin1, Bo Cheng1, Xinyan Deng1 and Karl Reichard1 1Purdue University 1The Pennsylvania State University • The wing is modeled as a rigid body • Trajectory control strategies for with three degree-of-freedoms. unicycle robots are well developed.d. • One actuator and one torsional spring • The ICR kinematic mapping from at the stroke angle act as the power skid-steer to unicycle movements muscles. can leverage these strategies. • Two torsional springs at the rotation • The adapted unicycle robot angle and the deviation angle mimic trajectory controller has been testeded the control muscles. on two skid-steer robotic platforms.s
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
181 Session TuE1 Grand Ballroom Tuesday, September 16, 2014, 16:50–17:55 Constrained and Underactuated Robots / Legged Robots I Chair Martin Buehler, Vecna Technologies Co-Chair
17:25–17:28 TuE1.7 17:28–17:31 TuE1.8 Open-Source, Affordable, Modular, Light- Modeling of Wheeled Mobile Robots as Weight, Underactuated Robot Hands Differential-Algebraic Systems A. Zisimatos1, M. Liarokapis1,
C. Mavrogiannis2 and K. Kyriakopoulos1 Alonzo Kelly, Neal Seegmiller, 1National Technical University of Athens, Greece Carnegie Mellon University 2Cornell University, USA • Detailed, useful, complete • A new open source design for formulation of WMR dynamics and the development of affordable, kinematics as a differential algebraic modular, lightweight, compliant, system. under-actuated robot hands. • Experiments show formulation is both more accurate • Robot hands can be developed and more efficient than traditional approaches. using off-the-shelf materials. • Introduces the concept of “constrained” kinematics • Robot hands efficiently grasp a where Lagrange multipliers are used to enforce plethora of everyday life objects. kinematic constraints on WMRs.
17:31–17:34 TuE1.9 17:34–17:37 TuE1.10 Practical Identification and Flatness Partial Force Control of based Control of a Terrestrial Quadrotor Constrained Floating-Base Robots Sylvain Thorel1, Brigitte d’Andréa-Novel1, A. Del Prete1, N. Mansard1, F. Nori2, 1MINES Paristech, PSL-Research University, G. Metta2 and L. Natale2 Centre for robotics 1LAAS/CNRS, Toulouse, France 2IIT, Genoa, Italy
Context: Indoor exploration with a terrestrial quadrotor • Multi-task motion/force control capable of flying and sliding on the ground to save energy • Exploit structure of problem to derive analytical sparse Terrestrial mode : solution of constraints • 2D xy plane trajectory tracking • Reduce computational based on a flatness approach complexity • Identification and experimental • ~19x speed-up with respect to results of the control law classical formulation
17:37–17:40 TuE1.11 17:40–17:43 TuE1.12 Balancing Control Algorithm for a 3D On the Convergence of Fixed-point Iteration in Under-actuated Robot Solving Complementarity Problems Arising in Robot Locomotion and Manipulation Morteza Azad1 and Roy Featherstone2 1University of Birmingham, UK Ying Lu1, Jeff Trinkle1 2Istituto Italiano di Tecnologia, Italy 1Rensselaer Polytechnic Institute • A novel decomposition of 3D balancing • Model-based approaches into: to the planning or control - balancing in the plane, and of robot locomotion or - keeping the plane vertical manipulation requires the solution of CPs • A novel robot mechanism that decouples the dynamics of 3D balancing • We studied the factors that affect how fixed-point • Balancing while following a commanded iteration method trajectory converges
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
182 Session TuE1 Grand Ballroom Tuesday, September 16, 2014, 16:50–17:55 Constrained and Underactuated Robots / Legged Robots I Chair Martin Buehler, Vecna Technologies Co-Chair
17:43–17:46 TuE1.13 17:46–17:49 TuE1.14 Quadruped Bounding Control with Balance Control for Humanoid Robots in Variable Duty Cycle via Vertical Impulse Multi-Contact Scenarios based on MPC Scaling Bernd Henze, Christian Ott and Hae-Won Park1, Meng Yee (Michael) Chuah1, Maximo A. Roa and Sangbae Kim1 German Aerospace Center (DLR) 1 Massachusetts Institute of Technology • Force based balancing with an • Dynamic quadruped bounding arbitrary number of end effectors gait with variable duty cycle is in contact obtained experimentally on MIT • Prediction allows a reaction to Cheetah 2. future reference signals • The algorithm prescribes vertical • Control of COM position and hip impulse by generating scaled orientation ground reaction forces at each step to achieve the • Task prioritization by weightings desired stance and total stride duration.
17:49–17:52 TuE1.15 17:52–17:55 TuE1.16 Optimal Gaits and Motion Quadratic Programming-Based Inverse for Legged Robots Dynamics Control for Legged Robots with Sticking and Slipping Frictional Contacts Weitao Xi, C. David Remy University of Michigan Samuel Zapolsky1, Evan Drumwright2 1,2George Washington University • Explored a trajectory optimization method for unspecified contact sequences as a tool to identify optimal gaits and motions • Improved the existing algorithm • The proposed method discovered walking and running gaits at different speed automatically
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
183 Session TuE2 State Ballroom Tuesday, September 16, 2014, 16:50–17:55 Human-Robot Interaction III / Grasp Learning Chair Nicholas Wettels, NASA-JPL Co-Chair
16:50–17:10 TuE2.1 17:10–17:13 TuE2.2
Keynote: Perception-Action-Learning Remote Control System for Multiple Mobile Robots and Associative Skill Memories using Touch Panel Interface and Autonomous Mobility Stefan Schaal Yuya Ochiai1, Kentaro Takemura2, Atsutoshi Ikeda1, MPI Intelligent Systems & Univ. of S. California Jun Takamatsu1 and Tsukasa Ogasawara1 1Nara Inst. of Science and Technology, 2Tokai University • Robotics needs more research on perception-action-learning • Propose the remote control system loops: that uses touch panel interface • Interactive perception • Achieves autonomy of mobile robots by using SLAM, motion planning, • Automatic creation of beha- and object tracking. vior graphs for complex skills • Reduce the user’s concentration • Prediction, recovery, switchingg against each robots and total time to based on sensory information complete navigation • Machine learning techniques
17:13–17:16 TuE2.3 17:16–17:19 TuE2.4 Modeling of Human Velocity Habituation Ridesharing with Passenger Transfers for a Robotic Wheelchair
Brian Coltin and Manuela Veloso Morales Y., Abdur-Rahim J.A., Even J., Kondo T., Carnegie Mellon University Ogawa T., Hagita N., and Ishii S.
• In ridesharing, passengers • Model for Human Habituation while request rides from non- riding a robotic wheelchair in terms professional drivers. of preferred velocity • We introduce three algorithms to • Preferred velocity is selected based schedule rides, with passenger on user experience transfers. • Evaluation with skin conductance • We compare and evaluate the and questionnaires show preference algorithms on maps with real- for habituation velocity control over world data. fixed velocity control 17:19–17:22 TuE2.5 17:22–17:25 TuE2.6 Physical Embodied Communication Using social cues to estimate possible between Robots and Children: destinations when driving a wheelchair An Approach for Relationship Building by Holding Hands Arturo Escobedo1, Anne Spalanzani2, Chie Hieida1, Kasumi Abe1, Muhammad Attamimi1, and Christian Laugier1 2 1 2 Takayuki Shimotomai , Takayuki Nagai and Takashi Omori 1 2 1 The University of Electro-Communications, INRIA Rhone-Alpes Univ. Grenoble Alpes, Lab. 2 Tamagawa Universitysity LIG, Grenoble, France. Inria • Our hypothesis is “physical embodied • A method to estimate the user communication between robots and intended destination to alleviate the children” improves the relationship user involvement when driving a between them robotic wheelchair is presented. • An experiment was carried out using 37 • Meeting points to join a group of 5-6 year-old children people and frequent goals are • The children in the experimental (holdingg considered. hands) group were closer to the robot than those in the control (non holding • Personal and interaction spaces are hands) group as in the graph respected by the navigation system.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
184 Session TuE2 State Ballroom Tuesday, September 16, 2014, 16:50–17:55 Human-Robot Interaction III / Grasp Learning Chair Nicholas Wettels, NASA-JPL Co-Chair
17:25–17:28 TuE2.7 17:28–17:31 TuE2.8 A Novel User-Guided Interface Contextual Task-Aware Shared Autonomy for Robot Search for Assistive Mobile Robot Teleoperation Ming Gao, Jan Oberlaender, Shahar Kosti, David Sarne and Gal A. Kaminka Thomas Schamm and J. Marius Zoellner Bar Ilan-University, Israel Forschungszentrum Informatik • An asynchronous interface for • Robot provides assistance by image human operators of robotic search. recognizing the on-going task
• The interface presents the operator any text in the • Task features are defined to with highly-relevant images, based image should describe the context information on selected POIs (Point Of Interest). be the same •A unified framework using machine • We show improved performance size as main learning method is proposed over the state-of-the-art system- text • Simulation results verify the effect guided approach. of the proposed approach
17:31–17:34 TuE2.9 17:34–17:37 TuE2.10 Personalizing Vision-based Gestural Multimodal Real-Time Contingency Interfaces for HRI with UAVs: a Transfer Detection for HRI Learning Approach Vivian Chu1, Kalesha Bullard1, G. Costante1, E. Bellocchio1, P. Valigi1, E. Ricci1,2 Andrea L. Thomaz1 1University of Perugia,2Fondazione Bruno Kessler 1Georgia Institute of Technology • We address the problem of vision- • Implemented real-time controller to mediated HRI with flying robots. detect initial human engagement • Our system recognizes the user • Based on human cognition: solved identity to invoke a personalized as a contingency detection problem gesture recognition model, improving • Trained three Support Vector accuracy over generic models. Machines; Evaluated with two
• A novel transfer learning algorithm for creating user- separate experiments Curi performing
specific classifiers is proposed, which exploits data Best F score, with participants: 0.72 “Wave” signal from other users or downloaded from the web. 1
17:37–17:40 TuE2.11 17:40–17:43 TuE2.12
&) )0"$0"&% "% !3)"# 1$%6!"% Learning of Grasp Adaptation through %0(0"&%) 2"0! ''#"0"&% 0& "3# ""% Experience and Tactile Sensing 1 2 "4!" !% 75 Miao Li , Yasemin Bekiroglu , Danica Kragic2 and Aude Billard1 ! " # 1LASA, EPFL 2CVAP, KTH •: / • A grasp stability estimator is learnt based on an object-level impedance controller. • • Once a grasp is predicted to be unstable by the stability • estimator, a grasp adaptation strategy is triggered according to the experience and tactile sensing.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
185 Session TuE2 State Ballroom Tuesday, September 16, 2014, 16:50–17:55 Human-Robot Interaction III / Grasp Learning Chair Nicholas Wettels, NASA-JPL Co-Chair
17:43–17:46 TuE2.13 17:46–17:49 TuE2.14 Construction of an Object Manipulation Evaluating Efficacy of Grasp Metrics for Database from Grasp Demonstrations Utilization in a Gaussian Process-Based Grasp Predictor David Kent1, Sonia Chernova1 Alex Goins1, Ryan Carpenter1, 1Worcester Polytechnic Institute Weng-Keen Wong1 and Ravi Balasubramanian1 1 • Crowdsourcing-based grasp Oregon State University demonstration system • We collect a large grasp data set (522 grasps) and • Grasp success rates learned from evaluate twelve grasp metrics and compare their outlier filtering and online epsilon- ability to classify grasp performance using physical greedy grasp training algorithm shake test data. After evaluating the grasp metrics, we use a machine learning technique to combine the • Compared usefulness of non- metrics to create a new grasp predictor which is able expert and expert demonstrated to out perform the individual metrics and provide an grasps absolute measure of grasp quality.
17:49–17:52 TuE2.15 17:52–17:55 TuE2.16 Learning Robot Tactile Sensing for Object Manipulation Yevgen Chebotar1, Oliver Kroemer1, Oliver Kroemer1, Jan Peters 1,2, and Jan Peters1,2 1 IAS, TU Darmstadt 2 MPI Intelligent Systems 1IAS, TU Darmstadt 2MPI Intelligent Systems • Interactions between objects • Tactile feedback is needed for more imageimmaagge depend on contact distributions robust manipulation
• Define a kernel function for • Evaluate three methods for in-hand anyaanny texttetextxt inin thetthhe computing similarity between localization with tactile information imageiimmaagge shsshouldhoouulldd contact distributions • Learn tactile manipulation from be thethehe samesamame • Use kernel methods to predict demonstration and self- sizesiizeze asas mainmmaaiinn interactions from contacts improvement texttetexxtt • Successfully evaluated on both • Efficient learning is possible using grasping and block stacking tasks dimensionality reduction
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
186 Session TuE3 Red Lacquer Room Tuesday, September 16, 2014, 16:50–17:55 Unmanned Aerial Systems I / Localization and Pose Estimation Chair Christopher M. Clark, Harvey Mudd College Co-Chair
16:50–17:10 TuE3.1 17:10–17:13 TuE3.2 Frequency-Domain Dynamics Model Keynote: Aerial Robot Swarms Identification of Miniature Quadcopters Vijay Kumar Guowei Cai, Guowei Cai, Hind Al Mehairi, Hanan University of Pennsylvania Al-Hosani, Jorge Dias, and Lakmal Seneviratne Khalifa University This talk will This work presents a complete introduce aerial system identification process of robotics, the identifying miniature quadcopter opportunities in the flight dynamics model using field. and the key CIFER identification programme. challenges in Various validations have been control, perception conducted to proof the efficiency and planning for of the method and the fidelity of developing swarms of autonomous micro aerial the identified model. vehicles. 17:13–17:16 TuE3.3 17:16–17:19 TuE3.4 Simulating Quadrotor UAVs in Outdoor Health Aware Stochastic Planning For Persistent Scenarios Package Delivery Missions using Quadrotors Andrew Symington, Renzo De Nardi, Simon Ali-akbar Agha-mohammadi 1, N. Kemal Ure 1, Julier, and Stephen Hailes Jonathan P. How 1 and John Vian2 University College London 1MIT 2 Boeing Research and Technology Matlab Toolbox • Extending the health-aware • General quadrotor dynamics planning (HAP) problem to • Advanced GPS model partially-observable domains • Military wind models • Proposing a proactive-reactive • Noisy sensors method for the problem of • Barometric pressure package delivery under • AHRS uncertainty and health degradation github.com/UCL-CompLACS/qrsim Method architecture
17:19–17:22 TuE3.5 17:22–17:25 TuE3.6 High-throughput study of flapping wing Computational morphology for a soft micro aerodynamics for biological and robotic air vehicle in hovering flight applications Christine Chevallereau, Vincent Lebastard, Nick Gravish1, Yufeng Chen1, Frédéric Boyer Stacey Combes2 and Robert J. Wood1 IRCCyN, CNRS, Ecole des Mines de Nantes 1 2 SEAS, Harvard University OEB, Harvard • Bio-inspired MAV with actuated flapping University motion of soft wings with passive Here we present twisting a high-throughput • Depending on stiffness, and geometric measurement characteristic, hovering flight can be system for study naturally stable or not. and optimization • Mathematical tools and methodologies of micri-aerial are proposed to find an appropriate vehicle design and reduce the computational aerodynamics cost of control.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
187 Session TuE3 Red Lacquer Room Tuesday, September 16, 2014, 16:50–17:55 Unmanned Aerial Systems I / Localization and Pose Estimation Chair Christopher M. Clark, Harvey Mudd College Co-Chair
17:25–17:28 TuE3.7 17:28–17:31 TuE3.8 Towards Valve Turning using a Control of a Multirotor Outdoor Dual-Arm Aerial Manipulator Aerial Manipulator Christopher Korpela1, Matko Orsag2, G. Heredia, A.E. Jimenez-Cano, I. Sanchez, D. and Paul Oh1 Llorente, V. Vega, J. Braga, J.A. Acosta 1Drexel University 2University of Zagreb and A. Ollero, GRVC-University of Seville • Aerial manipulator endowed with • Design and control of a multirotor- image dual 2-DOF arms and grippers based aerial manipulator developed
for outdoor operation. • Ellipsoid detection and compliance any text in the control facilitate task completion • Backstepping-based controller for image should • Coupling between arms and valve is multirotor that uses the coupled full be the same evaluated to ensure system stability dynamic model. size as main Valve turning • Flight tests and validation using a • Experimental results compared to text flight test test rig confirm dynamic model baseline PID controller.
17:31–17:34 TuE3.9 17:34–17:37 TuE3.10 Reinforcement Learning for Autonomous Vision-based Absolute Localization for Dynamic Soaring in Shear Winds Unmanned Aerial Vehicles A. Yol1, B. Delabarre1, Corey Montella, and John Spletzer A. Dame, J.-E. Dartois and E. Marchand1 Lehigh University 1Inria/Irisa Rennes, Lagadic Team • Reinforcement learning (RL) • Direct Pose Estimation for a dynamic soaring task (DS) is demonstrated in • Vision-based approach simulation. using image registration relying on the Mutual • Teaching controller Information. demonstrates correct (DS) strategies. • Drift effects avoided by Absolute localization using georeferenced • RL controller improves on of the UAV images. performance by almost 50%
17:37–17:40 TuE3.11 17:40–17:43 TuE3.12 Variable impedance control for aerial Improving object tracking through distributed interaction exploration of an information map Abeje Y. Mersha,1 Stefano Stramigioli,2 Izaak Neveln1, Lauren Miller1, and Raffaella Carloni2 Malcolm MacIver1 and Todd Murphey1 1Saxion University of Applied Science 1Northwestern University 2University of Twente • Maximizing Information (I) results in image poor tracking • Versatile control architecture for free-flight and interaction • Modifying Information to include any text in the • Unified variable impedance sensor history information (I*) results image should and time-varying interaction in distributed trajectories be the same force controller • Distributed trajectories size asI main give better estimates of • Performance demonstrated I* text
object position with more information by experiments position certainty in 1D
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
188 Session TuE3 Red Lacquer Room Tuesday, September 16, 2014, 16:50–17:55 Unmanned Aerial Systems I / Localization and Pose Estimation Chair Christopher M. Clark, Harvey Mudd College Co-Chair
17:43–17:46 TuE3.13 17:46–17:49 TuE3.14
Topometric Localization on a Road Pose Estimation of Servo-Brake-Controlled Network Caster Units Arbitrarily Located on a Mobile Base Danfei Xu1, Hernán Badino1, Masao Saida1, Yasuhisa Hirata1 and Daniel Huber1 and Kazuhiro Kosuge1 1Carnegie Mellon University Robotics Institute 1Tohoku University, Japan • This paper presents an • Estimation of the geometrical algorithm for localizing a relationships between caster units vehicle on an arbitrary • Recursive Estimation using only the GPS-denied road velocity information of each caster network using vision, unit by the Extended Kalman filter road curvature • A simple pattern that enables users estimates, or a to provide sufficiently rich information combination of both. for relationship estimates
17:49–17:52 TuE3.15 17:52–17:55 TuE3.16 Rail-Guided Robotic End-Effector Position-Error A Multi-AUV State Estimator for 3D Due to Rail Compliance and Ship Motion Localization of Tagged Fish D.J. Borgerinka,b, J. Stegengab, Y. Lin 1, H. Kastein1, D.M. Brouwera, H.J. Wörtcheb and S. Stramigiolia T. Peterson1, C. White2, C. G. Lowe2 , C. Clark1 aUniversity of Twente bINCAS3 Harvey Mudd College1, CSU Long Beach2 A 3D state-estimator part of a multi- AUV shark tracking system is presented. Experimental results show significant tracking performance compared to previous works. The system has also been successfully • Inspection robot for ballast water tanks in ships used to track a tagged leopard shark • Influence of rail compliance on the end-effector position over a span of 4 days. • Alternative design strategy is recommended
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
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192 Session WeA1 Grand Ballroom Wednesday, September 17, 2014, 09:00–10:20 Medical Robots and Systems II / Rehabilitation Robotics II Chair Russell H. Taylor, The Johns Hopkins University Co-Chair
09:00–09:20 WeA1.1 09:20–09:23 WeA1.2 Keynote: Towards Intelligent Robotic Task-space motion planning of MRI-actuated Surgical Assistants catheters for catheter ablation of atrial fibrillation
M. Cenk Cavusoglu Tipakorn Greigarn1, Cenk Çavuşoğlu1, Case Western Reserve University 1Case Western Reserve University This talk will introduce the current state of our research towards • An MRI-actuated catheter is steered development of intelligent robotic by applying currents to the coils surgical assistants. I will present attached to the catheter under MRI our latest results on robotic magnetic field. sensing, active perception, • Main difficulty is kinematic planning, and manipulation redundancy and underactuation Input terminals for Needle driver SMA actuator
algorithms towards autonomous Linear actuator Outer casing made of Celazol material • Control trajectory is calculated in the Linear actuator Screw SMA actuator Needle driver execution of low-level surgical task space to avoid the problems tasks.
09:23–09:26 WeA1.3 09:26–09:29 WeA1.4 Using Lie algebra for shape estimation Modeling and Control of Robotic Surgical of medical snake robots Platform for Single-Port Access Surgery Rangaprasad Arun Srivatsan1, Jusuk Lee1, J. Kim1, K. Lee2, S. Hyung1, Matthew Travers1 and Howie Choset1 Y. Kim3, W. Kwon1, K. Roh1, and J. Choi1 1Carnegie Mellon University 1 Samsung Electronics, 2 KIST, 3 KOREATECH Using Lie algebra in the state vector • The surgical robot consists of a 6- of an extended Kalman filter, DOF guide tube, two 7-DOF tools, a the shape of a highly articulated robot 3-DOF stereo camera, and a 5-DOF is estimated. slave arm. • We propose a Cartesian-level This approach provides a more controller to position and orient the accurate estimation of the shape compared to guide tube. approaches using conventional parameterization of • We compensate for the backlash in SE(3). the tool joints for accurate motion.
09:29–09:32 WeA1.5 09:32–09:35 WeA1.6
Semi-Autonomous Navigation for Robot Assisted Tele-Echography using State Recognition of Bone Drilling With Audio Signal Generalized Shape Models and Co-Registered RGB-D cameras in Robotic Orthopedics Surgery System Lin Zhang1, Su-Lin Lee1, Yu Sun, Haiyang Jin, Ying Hu*, Peng Zhang, Jianwei Zhang 1 1 Guang-Zhong Yang and George P. Mylonas Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1Imperial College London ShenZhen,China (1) For analyzing the audio signal in the bone drilling Bone Drilling EMA & HE Experiments • Proposed a navigation system with a process, the power spectral density caculated in the FFT method is used to determine an effective band master-slave setup for robot-assisted with less noise. remote ultrasound examination using (2) Two features, EMA and HE, are proposed for illust- rating the drilling process. a deformable shape model of patient Signal Analysis (3) A drilling state recognition algorithm is developed Two Features • A patient specific customized model to monitor the drilling process. (4) A embedded state monitor is developed for real-time ROSS System is generated and updated based on recognition. EDSM System patient’s motion (5) A robotic orthopedics surgery system is used to con- duct an experiment to demonstrate the algorithm. Several Tests • Experiments show the effectiveness Medical Images of the shape model and system
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
193 Session WeA1 Grand Ballroom Wednesday, September 17, 2014, 09:00–10:20 Medical Robots and Systems II / Rehabilitation Robotics II Chair Russell H. Taylor, The Johns Hopkins University Co-Chair
09:35–09:38 WeA1.7 09:38–09:41 WeA1.8 Estimating Contact Force for Steerable Shape Prediction for a Nonconstant Ablation Catheters based on Shape Analysis Curvature Snake-like Manipulator Mahta Khoshnam1,2, Rajni V. Patel1,2, R Murphy1,2, Y Otake1, R Taylor1 and M Armand1,2 1Canadian Surgical Technologies and Advanced 1Johns Hopkins University Robotics (CSTAR), 2 Western University, Canada 2Johns Hopkins University Applied Physics Lab
• Feasible to estimating 3 • Developed two-stage algorithm to F
tip/tissue contact force from 2.5 predict the kinematic configuration catheter shape. 2 of a snake-like manipulator from string length • Defining an index to denote 1.5 the range of contact forces. 1 • Compared to experimental data, Force Index: Index: Force results demonstrate successful • The index correctly detects 10 20 30 40 prediction for tip position and force ranges in 80% of cases. Force Magnitude (gf) manipulator shape Example predicted configuration (green)
09:41–09:44 WeA1.9 09:44–09:47 WeA1.10
Comparison of Methods for Estimating the Position of Robust Forceps Tracking Using Online Calibration of Hand-Eye Actuated Instruments in Flexible Endoscopic Surgery Coordination for Microsurgical Robotic System
Shinichi Tanaka1, Young Min Baek1, Kanako Harada1, Naohiko Sugita1, Akio Morita2, P. Cabras, D. Goyard, Shigeo Sora3, Hirofumi Nakatomi4, Nobuhito Saito4 and Mamoru Mitsuishi1 1. The University of Tokyo, Department of Mechanical Engineering F. Nageotte, P. Zanne, C. Doignon 2. Nippon Medical School Hospital ICUBE – University of Strasbourg, CNRS 3. Tokyo Metropolitan Police Hospital 4. The University of Tokyo, Department of Neurosurgery • Robotic Endoscopic Surgery with flexible instruments. • Forceps tracking method for microsurgical robotic system is • Measuring the position of instruments using the proposed. embedded endoscopic camera. • The kinematic data and microscopic • Model-based approach with image are used for the tracking. tolerance on geometrical model. • The hand-eye coordination is updated online to handle the • Learning-based approach. repositioning of the microscope.
09:47–09:50 WeA1.11 09:50–09:53 WeA1.12 MRI-powered Closed-loop Control for Development and Evaluation of an Multiple Magnetic Capsules Operation Interface for Physical Therapy Alina Eqtami, Ouajdi Felfoul Devices based on Rehab Database and Pierre E. Dupont Toshiaki Tsuji, Chinami Momiki, and Sho Sakaino Boston Children's Hospital, Harvard Medical School Saitama University, Japan • Use of Clinical MRI for powering and tracking. For joystick operation • Goal: Closed-loop control of a group of millimeter interfaces, the operator can scale magnetic capsules. freely control the device by • Optimal switching between actuation & tracking recognizing the direction and as these are interleaved. magnitude of the applied force. An appropriate degree of rigidity • Consideration of all the for the joystick is needed to practical issues: delays enable operations involving fine constraints & disturbances. and large motions.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
194 Session WeA1 Grand Ballroom Wednesday, September 17, 2014, 09:00–10:20 Medical Robots and Systems II / Rehabilitation Robotics II Chair Russell H. Taylor, The Johns Hopkins University Co-Chair
09:53–09:56 WeA1.13 09:56–09:59 WeA1.14 EMG-based Continuous Control Method NTUH-II Robot Arm with Dynamic Torque for Electric Wheelchair Gain Adjustment Method for Frozen Shoulder Rehabilitation Giho Jang and Youngjin Choi 1 1 1 Hanyang University, South Korea C.-H. Lin , W.-M. Lien , W.-W. Wang , S.-H. Chen 1, C.-H. Lo 1, S.-Y. Lin 1, L.-C. Fu 1, Fellow, 2 • Conventional methods have IEEE and J.-S. Lai provided intermittent commands. 1National Taiwan University(NTU) 2 NTU Hospital • Facial muscles are utilized as • A new 8 degrees of freedom (DOFs) inputs to replace the conventional rehabilitation robot arm named joystick interface. NTUH-II has been developed. • The effectiveness of the proposed • A dynamic gain adjustment method control scheme is verified through based on stiffness model for frozen several experiments. shoulder rehabilitation is proposed.
09:59–10:02 WeA1.15 10:02–10:05 WeA1.16 Involuntary Movement during Haptics- A Framework for Supervised Robotics- enabled Robotic Rehabilitation Assisted Mirror Rehabilitation Therapy S. Farokh Atashzar1, A. Saxena1,M.Shahbazi1 Mahya Shahbazi1,2, S.F. Atashzar1,2,R.V. Patel1,2 and Rajni V. Patel1 1Canadian Surgical Technologies and Advanced 1Western University (UWO), Canada Robotics (CSTAR), 2Western University, Canada
• Safety of patient-robot interaction in • Novel robotics-assisted framework the presence of pathological tremors for bilateral mirror-image therapy: to for haptics-enabled rehabilitation. facilitate brain neuro-plasticity in post-stroke patients.
• Control architecture to provide a 0 • Customized dual-user teleoperation modulated force field that can damp -0.05
Y(m) architecture incorporated with out hand tremor and -0.1 Guidance Virtual Fixtures (GVFs).
assist/coordinate voluntary actions. 0.1 0.15 0.2 X(m) • Closed-loop stability using the Test bed & Results small-gain theorem.
10:05–10:08 WeA1.17 10:08–10:11 WeA1.18 Development of an Upper Limb Exoskeleton A Novel Customized Cable-Driven Robot Powered via Pneumatic Electric Hybrid for 3-DOF Wrist and Forearm Actuators with Bowden Cable Xiang Cui1, Weihai Chen1, Tomoyuki Noda1, Tatsuya Teramae1, Barkan Sunil K. Agrawal2 and Jianhua Wang1 Ugurlu1, and Jun Morimoto1 1Beihang University 2Columbia University 1ATR Computational Neuroscience Labs • Powered by a hybrid way • Features of the system: (PAMs with Bowden Cable + a Cable-driven, cost-effective, low- small electromagnetic motor) weight, and easy-to-reconfigure • Implementable multi-DOF • System design generates precise large torque • Workspace analysis of a crossed-
with agility and backdrivability cable-driven structure • Prototyped light weight right • Fast-convergent Parameter arm exoskeleton (5kg) identification algorithm
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
195 Session WeA1 Grand Ballroom Wednesday, September 17, 2014, 09:00–10:20 Medical Robots and Systems II / Rehabilitation Robotics II Chair Russell H. Taylor, The Johns Hopkins University Co-Chair
10:11–10:14 WeA1.19 10:14–10:17 WeA1.20 Identifying Inverse Human Arm A Risk Assessment Infrastructure for Dynamics Using a Robotic Testbed Powered Wheelchair Motion Commands E. Schearer1, Y. Liao1, E. Perreault1, M. Tresch1, without Full Sensor Coverage W. Memberg2, R. Kirsch2, and K. Lynch1 P. TalebiFard, J. Sattar, I. M. Mitchell 1Northwestern U. 2Case Western Reserve U. The University of British Columbia • We want to use functional electrical • Risk assessment for collaborative stimulation to control a human arm control of a powered wheelchair paralyzed by spinal cord injury. • Estimate collision risk using a • Robot moves hand along smooth dynamic egocentric occupancy map reaching trajectories and measures and a neural network model of force required to move hand. joystick control of PWC • Gaussian process regression predicts • Demonstrate under two scenarios mapping from shoulder and elbow using single RGB-D sensor on an positions and velocities to torque. actual PWC 10:17–10:20 WeA1.21 LINarm: a Low-cost Variable Stiffness Device for Upper-limb Rehabilitation Matteo Malosio1,2, Marco Caimmi1,2, Giovanni Legnani2 and Lorenzo Molinari Tosatti1 1CNR-ITIA, Italy 2UNIBS, Italy • Device to perform linear rehabilitation exercises of the human arm • Variable stiffness actuator • Force estimation • Low-cost design • Control aspects • 3D-printable
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
196 Session WeA2 State Ballroom Wednesday, September 17, 2014, 09:00–10:20 Motion and Path Planning III / Planning, Failure Detection and Recovery Chair Torsten Kroeger, Google, Inc. Co-Chair
09:00–09:20 WeA2.1 09:20–09:23 WeA2.2 Keynote: Planning for Complex Nonlinear Dimensionality Reduction for High-Level Missions Kinematic Cartography Lydia E. Kavraki Tony Dear1, Ross Hatton2, and Howie Choset1 Rice University 1Carnegie Mellon University Office Map 2Oregon State University • The goal is to produce low- • Non-Euclidean metrics for level motion plans that satisfy motion planning often distort a high-level specification or a robot’s shape manifold. mission. • Goal: “Relax” the distortions • How can the mission be so that trajectory lengths are specified? better visually represented. • How can the motion plans be • Isomap finds the manifold’s generated for a general best projection for preserving hybrid system? Janitor Robot point-to-point distances.
09:23–09:26 WeA2.3 09:26–09:29 WeA2.4 Orienting in Mid-Air … to Achieve a Motion planning for non-holonomic mobile robots using Rolling Landing for Reducing Impact … the i-PID controller and potential field
Jeffrey Bingham, Jeongseok Lee, Yingchong MA1, Gang Zheng1,2,
Ravi Haksar, Jun Ueda and Karen Liu Wilfrid Perruquetti1,2 and Zhaopeng Qiu1 Georgia Institute of Technology 1Ecole Centrale de Lille 2INRIA-Lille Nord Europe
• Using -PID controller to track the desired velociy • New potential field function improves the performance of obstacle avoidance and can produce smooth forces
09:29–09:32 WeA2.5 09:32–09:35 WeA2.6 Spherical Parabolic Blends Trajectory Planning for Car-Like Robots for Robot Workspace Trajectories in Unknown, Unstructured Environments Dennis Fassbender1, André Mueller1, Neil Dantam and Mike Stilman and Hans-Joachim Wuensche1 Georgia Institute of Technology 1University of the Bundeswehr Munich • Goal: Navigation under adverse • Multiple Workspace Waypoints conditions, e.g. off-road, poor GPS • Smooth, Nonstop Motion • Figure: GPS road data in cyan, • Constant-Axis Segments generated trajectory in green • Blending of Spherical Linear • Costs determined by path’s shape Interpolation and terrain it crosses (e.g. slopes) • 1st place at euRathlon 2013 Screw Alignment and Insertion (Autonomous Navigation scenario)
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
197 Session WeA2 State Ballroom Wednesday, September 17, 2014, 09:00–10:20 Motion and Path Planning III / Planning, Failure Detection and Recovery Chair Torsten Kroeger, Google, Inc. Co-Chair
09:35–09:38 WeA2.7 09:38–09:41 WeA2.8 Risk-aware Trajectory Generation with Application to Safe Quadrotor Landing
Michael Shomin and Ralph Hollis Jörg Müller and Gaurav S. Sukhatme Carnegie Mellon University University of Southern California
• Ballbot: a balancing, person sized • State uncertainty and closed-loop mobile robot control cause deviations form the • Presented is a method for desired trajectory generating dynamically feasible trajectories amongst obstacles in • Optimize trajectory wrt. smoothness milliseconds and risk of collision or failure • Tractable and experimentally • Trade off risk against duration verifiedPictured: the ballbot • Encode constraints in efficient executing a trajectory through clutter at .7 m/s polynomial trajectory representation
09:41–09:44 WeA2.9 09:44–09:47 WeA2.10 Hierarchical Robustness Approach for 0 Nonprehensile Catching of Rigid Objects Alexander Pekarovskiy1, Ferdinand Stockmann1, Masafumi Okada2 and Martin Buss1 1TUM, LSR 2TITECH, MEP • • Nonprehensile catching of • arbitrarily shaped rigid objects ! " ! • Multi-level approach and action • # sequence for robust task planning "
• Catching strategies classification
09:47–09:50 WeA2.11 09:50–09:53 WeA2.12 Extending Equilibria to Periodic Orbits Global Registration of Mid-Range 3D Observations for Walkers using Continuation Methods and Short Range Next Best Views Jacopo Aleotti, Dario Lodi Rizzini1, Nelson Rosa Jr.1 and Kevin M. Lynch1, Riccardo Monica1 and Stefano Caselli1 1Northwestern University 1University of Parma, Italy •A simple method for generating time • Exploration of unknown objects by image walking gaits. sensor fusion of 3D range data
using two eye-in-hand sensors • Generates passive and powered any text in the gaits. • First sensor operates at mid-range state image should • Method applies to multi-degree-of- be the same • Second sensor provides short-range freedom bipeds. size as main data from next best view planning • Geometric interpretation of gaits as text • Global registration of all object points on a manifold. controls observations
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
198 Session WeA2 State Ballroom Wednesday, September 17, 2014, 09:00–10:20 Motion and Path Planning III / Planning, Failure Detection and Recovery Chair Torsten Kroeger, Google, Inc. Co-Chair
09:53–09:56 WeA2.13 09:56–09:59 WeA2.14 Model-free robot A constraint-based method for solving anomaly detection sequential manipulation planning problems Rachel Hornung1, H. Urbanek1, J. Klodmann1, Tomas Lozano-Perez and Leslie Pack Kaelbling C. Osendorfer2 and P. van der Smagt2,3 MIT 1DLR 2TUM 3Fortiss
• Learns anomalies from valid • Presents and approach to integrated data task and motion planning. • Generalizes to unseen data • Task planner produces plan skeleton with variables for geometric • Handles high-dimensional data parameters. • Can be adjusted to new setups • Geometric parameters are chosen • Applicable for online use by solving a constraint-satisfaction Train problem (CSP). Test
09:59–10:02 WeA2.15 10:02–10:05 WeA2.16 Attack Resilient State Estimation for A Metric for Self-Rightability and Its Autonomous Robotic Systems Relationship to Simple Morphologies Nicola Bezzo, J. Weimer, M. Pajic, Chad C. Kessens1, Craig T. Lennon1, O. Sokolsky, G. J. Pappas, and I. Lee and Jason Collins2 University of Pennsylvania 1US Army Research Lab 2Engility Corp.
• Development of a Recursive • Metric enables comparison across disparate designs Adaptive Estimator based • Demonstrated metric utility for analyzing: on the Linear Quadratic • Range of motion Regulator to shield against • Relative mass malicious attacks on sensors. • Mass location • Validation via extensive simulations and • Relative limb length experiments on two ground vehicles running cruise • Body aspect ratio control. • Validated in physical hardware
10:05–10:08 WeA2.17 10:08–10:11 WeA2.18 Sampling-Based Motion Planning with Reachable Probabilistically Complete Kinodynamic Planning Volumes : Application to Manipulators and Closed Chain Systems for Robot Manipulators with Acceleration Limits
Troy McMahon, Shawna Thomas and Nancy M. Amato Parasol Lab, Dept of Computer Science and Engineering, Tobias Kunz, Mike Stilman Texas A&M University, USA Georgia Tech Reachable volumes are a geometric representation of the regions the joints of a robot can reach. They can be used to generate constraint satisfying samples for problems including complicated linkage robots (e.g. image closed chains and graspers). • Joint acceleration limits instead of
We show that reachable volumes have an O(1) full robot dynamics complexity in unconstrained systems and in many constrained systems. We also show that reachable any text in the volume can be computed in linear time and that • RRT with steering method image should reachable volume samples can be generated in linear time in problems without constraints. be the same • Multiple orders of magnitude We evaluate the reachable volume sampler over a wide size as main variety of systems including linkages, closed chains and faster than a standard tree-like robots with as many as 262 dof. Our results text show that reachable volume sampling produces better kinodynamic RRT connected roadmaps and requires less computation time than existing methods.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
199 Session WeA2 State Ballroom Wednesday, September 17, 2014, 09:00–10:20 Motion and Path Planning III / Planning, Failure Detection and Recovery Chair Torsten Kroeger, Google, Inc. Co-Chair
10:11–10:14 WeA2.19 10:14–10:17 WeA2.20
Run-time Detection of Faults in Autonomous Mobile Robots Sampling-Based Tree Search with Discrete Abstractions for Based on the Comparison of Simulated and Real Robot Behaviour Motion Planning with Dynamics and Temporal Logic
Alan G. Millard1, Jon Timmis1 and James McMahon1,2, Erion Plaku1, Alan F.T. Winfield2 1Catholic University of America 1University of York 2University of the West of England 2US Naval Research Laboratory
• Non-faulty robot behaviour predicted 200 • Plan collision-free, low-cost, via simulation of controller code 150 and dynamically-feasible • Observed behaviour ≠ expected 100 trajectories that satisfy tasks behaviour b Faulty robot 50 given as co-safe LTL formulas Predicted
y 0 Non−Faulty • Periodically reinitialise simulation to Faulty • Incorporate physics-based −50 prevent drift due to reality gap engines for accurate −100 simulations of rigid-body • Trade-off between minimising drift −150 and detecting faulty behaviour dynamics −200 100 150 200 250 300 350 400 x
10:17–10:20 WeA2.21
Distributed fault detection and recovery for networked robots
Filippo Arrichiello Università degli Studi di Cassino e del Lazio Meridionale, Cassino, Italy Alessandro Marino Università degli Studi di Salerno, Salerno, Italy Francesco Pierri Università degli Studi della Basilicata, Potenza, Italy % % %
% .
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
200 Session WeA3 Red Lacquer RoomWednesday, September 17, 2014, 09:00–10:20 Networked Robots / Swarm Robotics Chair Richard Vaughan, Simon Fraser University Co-Chair
09:00–09:20 WeA3.1 09:20–09:23 WeA3.2 Autonomous Wireless Backbone Deployment Keynote: Networked Robots with Bounded Number of Networked Robots Daniela Rus Elerson R. S. Santos, Marcos A. M. Vieira CSAIL, MIT Computer Science Department Universidade Federal de Minas Gerais, Brazil • Challenges in networked robots We propose a methodology to interconnect a set of clients: • New capabilities at the 1. An Obstacle Avoidance Steiner intersection of communication, Tree sets the preliminary path. perception, and control 2. A state machine (CEFSM) autonomously guide networked • Coverage robots to create the network.
Our methodology needs a bounded number of robots to create the network.
09:23–09:26 WeA3.3 09:26–09:29 WeA3.4 Point Cloud Culling for Robot Vision Robust Routing and MCTP: Connectivity Tasks Under Communication Constraints Management of Mobile Robotic Teams James Stephan1, Jonathan Fink2, Benjamin William J. Beksi and Nikolaos Papanikolopoulos Charrow1, Alejandro Ribeiro1, and Vijay Kumar1 University of Minnesota, USA 1University of Pennsylvania 2U.S. A.R.L. • Algorithms for controlling data • We examined robust routing solutions and developed transmission in a robotic network the Multi-Confirmation Transmission Protocol (MCTP). Transmission Protocol Comparision using a cloud infrastructure • We showed that by using a 1 • Highly efficient transfer of RGB-D combination of robust routing 0.8 data from a client (robot) to a server and MCTP a mobile robotic 0.6 (cloud) team can successfully 0.4 • Reduction of network congestion Microvision Robot navigate complex Success Rate 0.2 MCTP environments, with minimal Simple thus allowing a robot to perform UDP 0 8 10 12 14 16 18 20 22 24 26 vision tasks in real-time communication overhead. Distance (m) 09:29–09:32 WeA3.5 09:32–09:35 WeA3.6 A Centralized-equivalent Decentralized From Autonomy to Cooperative Traded Implementation of Extended Kalman Control of Humanoid Manipulation Tasks Filters for Cooperative Localization Jim Mainprice1, Calder Phillips-Grafflin1, Halit Bener Suay1, Daniel Lofaro2, Dmitry Berenson1, Solmaz Kia1, Stephen Rounds2, Sonia Martinez3 Sonia Chernova1, Robert W. Lindeman1 and Paul Oh2 1UC Irvine 2John Deere ISG 3UC San Diego 1Worcester Polytechnic Institute 2Drexel University • Report lessons learned and system • A novel recursive decentralized design of a teleoperation framework cooperative localization (CL) algorithm for manipulation tasks with • Equivalent to a centralized EKF for CL unreliable communication • Small communication message size • Manipulation framework produces • Communication only at update stage fullbody statically-stable trajectories • Time-varying connectivity with the only • System was applied successfully to DRC-Hubo requirement of existence of a spanning the valve turning task of the DRC turning a valve tree rooted at robots taking measurements 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
201 Session WeA3 Red Lacquer RoomWednesday, September 17, 2014, 09:00–10:20 Networked Robots / Swarm Robotics Chair Richard Vaughan, Simon Fraser University Co-Chair
09:35–09:38 WeA3.7 09:38–09:41 WeA3.8 Route Swarm: Wireless Network Cooperative Dynamic Behaviors in Networked Optimization through Mobility Systems with Decentralized State Estimation R. K. Williams1, A. Gasparri2 and B. Krishnamachari1 Lorenzo Sabattini, Cristian Secchi, 1Univerisity Southern California and Cesare Fantuzzi 2Roma Tre University Univ. of Modena and Reggio Emilia (Italy) • Control strategy to implement dynamic complex • A novel hybrid architecture for behaviors in multi-robot systems, divided into leaders coordinating networked robots in followers sensing and information routing and • Decentralized estimation procedure for letting the • Mobile robotic network is dynamically leaders estimate the state of the system reconfigured to ensure high quality routes between static wireless nodes.
• High-level centralized routing coupled seamlessly with distributed swarming
09:41–09:44 WeA3.9 09:44–09:47 WeA3.10 Adding Transmission Diversity through Effective Compression of Range Data Streams Radio Switching and Directivity for Remote Robot Operations using H.264 Fabrizio Nenci1, Luciano Spinello2, Christopher Lowrance1, Adrian Lauf1, Cyrill Stachniss1 1University of Louisville 1University of Bonn 2University of Freiburg • Intelligent directional radio activation • Remotely operating robots often while maintaining omni-presence have limited communication abilities • Fuzzy logic controller used to make radio • Approach to stream depth images selection process through low bandwidth networks • Simulation results show that radio • Use of H.264 and demultiplexing to switching can improve throughput when reduce the effects of compression conditions unfavorable for omni-antenna, artifacts on range data despite delay incurred in switching • Used on Kinect and Velodyne data process
09:47–09:50 WeA3.11 09:50–09:53 WeA3.12 Network Lifetime Maximization in Task Assignment and Trajectory Optimization for Mobile Visual Sensor Networks Displaying Stick Figure Animations with Multiple Mobile Robots 1 2 Shengwei Yu , and C. S. George Lee 1 1 1 2 Katsu Yamane , Jared Goerner Marvell Semiconductor Inc. Purdue University 1Disney Research, Pittsburgh • Simultaneously design • Motion planning for multiple mobility, routing, source rate, mobile robots displaying and video encoding strategies stick figure animations for robotic visual sensor • Consistent body part nodes. representation across • The method shows an edge frames, including occlusions on lifetime maximization of • Demonstrated in simulation visual sensor networks. with up to 75 robots
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
202 Session WeA3 Red Lacquer RoomWednesday, September 17, 2014, 09:00–10:20 Networked Robots / Swarm Robotics Chair Richard Vaughan, Simon Fraser University Co-Chair
09:53–09:56 WeA3.13 09:56–09:59 WeA3.14 Worst-Case Optimal Average Consensus Robust Sensor Cloud Localization from Estimators for Robot Swarms Range Measurements Matthew Elwin, Randy Freeman, G. Dubbelman1, E. Duisterwinkel2, L. Demi1, E. and Kevin Lynch Talnishnikh2, H.J. Wörtche2, J.W.M. Bergmans1 Northwestern University 1Eindhoven University of Technology 2INCAS3 • Decentralized Averaging • Feasibility study on 3-D localization • Unknown Network of massive sensor clouds • Consistent Performance • Using range-only measurements • Robotic Applications and no beacons • SLAM, Formation Control • Simulations with inlier-outlier • Environmental Modeling models to determine robustness
09:59–10:02 WeA3.15 10:02–10:05 WeA3.16 Application of Grazing Guidance Laws to Human-Swarm Interaction Autonomous Information Gathering Using Spatial Gestures Thomas Apker1, Shih-Yuan Liu2, Jawad Nagi, Alessandro Giusti, Luca M. Donald Sofge3 and J. Karl Hedrick2 Gambardella, and Gianni A. Di Caro 1Exelis, Inc. 2UC Berkeley 3 Naval Research Lab Dalle Molle Institute for AI (IDSIA)
• Grazing animals do area coverage • Basic vocabulary of two-handed autonomously spatial gestures to select robots • They use a 1st order, greedy food- • Use of face engagement for seeker in a Voronoi cell selection and positioning of robots • A velocity controller allows 2nd • SVM classifier for spatial gesture order systems to use grazing laws recognition • Linear estimator covariance models • Distributed cooperative classification “food”, i.e. it is “eaten” by sensors` using distributed consensus
10:05–10:08 WeA3.17 10:08–10:11 WeA3.18 Mapping of Unknown Environments using Probabilistic Guidance of Distributed Minimal Sensing from a Stochastic Swarm Systems using Sequential Convex 1 1 1 Programming A. Dirafzoon , J. Betthauser , J. Schornick , D. 1 1 1 1 D. Morgan , G. Subramanian , Benavides , and E. Lobaton 1 1 1 S. Bandyopadhyay , S. Chung and North Carolina State University F. Y. Hadaegh2 • Swarm of stochastic 1University of Illinois at Urbana-Champaign 2Jet agents explore an Propulsion Lab, California Institute of Technology unknown environment • Probabilistic guidance of Iteration 1 Iteration 3 Iteration 5 30 distributed systems used to • Only interaction 25 achieve desired shape information is used to 20
learn topological • Model predictive control 15 Iteration 10 Iteration 15 Iteration 20
features of the space with sequential convex 10
programs used to generate 5
collision-free trajectories 0 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
203 Session WeA3 Red Lacquer RoomWednesday, September 17, 2014, 09:00–10:20 Networked Robots / Swarm Robotics Chair Richard Vaughan, Simon Fraser University Co-Chair
10:11–10:14 WeA3.19 10:14–10:17 WeA3.20 Geodesic Topological Voronoi Outdoor flocking and formation flight Tessellations in Triangulated with autonomous aerial robots Environments with Multi-Robot Systems G. Vásárhelyi1, Cs. Virágh1, G. Somorjai1, N. Seoung Kyou Lee1, Sándor P. Fekete2 Tarcai1, T. Szörényi1, T. Nepusz1, T. Vicsek1, and James McLurkin1 1Eötvös University, Budapest, Hungary 1 2 Rice University, U.S.A. TU Braunschweig, Germany We present a swarm of ten autonomous • Present a discrete approximation quadcopters with decentralized control of the geodesic Voronoi cell using and hardware, performing collision-free flocking, multi-robot triangulation formation flights, collective target tracking • Devise a distributed patrolling and object avoidance through true self-organized algorithm and its advanced version behaviour. using physical data structure Count them if you can!
• Compute globally optimal centroid using virtual agents
10:17–10:20 WeA3.21 Sponsor Talk: Autonomous Robot Fleets for Automated Warehouses F. Buzan, T. MacDonald, K. Pankratov, L. Sweet Symbotic LLC
• Fleets of high-speed autonomous mobile robots navigate within dense 3D structures to pick and place cases in exact sequence via coordinated task and planning • Deployed in multiple vertical market segments • Winner of 2013 Edison Award
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
204 Session WeB1 Grand Ballroom Wednesday, September 17, 2014, 10:50–12:10 Mechanisms and Actuators / Force and Tactile Sensing Chair Allison M. Okamura, Stanford University Co-Chair
10:50–11:10 WeB1.1 11:10–11:13 WeB1.2 Keynote: Natural Machine Motion and Dynamic Trajectory Planning of Planar Embodied Intelligence Cable-Suspended Parallel Robots Antonio Bicchi Lewei Tang1, Clément Gosselin2,Xiaoqiang Tang1 Università di Pisa & Istituto Italiano di Tecnologia and Xiaoling Jiang2 1Tsinghua University, Beijing, China, 2Université Laval, Québec, Canada What I think of Robots of the Future, i.e. • Cable-suspended robots with • They will move naturally, trajectories that extend beyond • will be soft, the static workspace • will be quick but also strong; • Redundancy increases the • must be robust, dynamic capabilities Cables • must be safe, • Special frequencies are revealed that simplify trajectory planning • Experimental • must be simple (!), M. Brega validation with 2-dof • Determination of feasible ranges and how I think we can build them, though it’s not easy... robot
11:13–11:16 WeB1.3 11:16–11:19 WeB1.4 Workspace Augmentation of Spatial Tendon Routing Resolving Inverse 3-DOF Cable Parallel Robots Kinematics for Variable Stiffness Joint Using Differential Actuation Shouhei Shirafuji1, Shuhei Ikemoto1, Hamed Khakpour1 and Lionel Birglen1 and Koh Hosoda1 1Ecole Polytechnique de Montreal 1Osaka University • Spatial cable differentials • The mechanism to control the are presented position and joint stiffness of a • Comparison between tendon-driven manipulator differentially and independently is proposed individually driven cable • We call it as “tendon routing parallel robots is shown resolving inverse kinematics” (TRIK) • Improvement of two types • The methodology to design this of workspaces is illustrated mechanism is introduced
11:19–11:22 WeB1.5 11:22–11:25 WeB1.6 Drum Stroke Variation using Compliant Robotic Systems on Graphs Variable Stiffness Actuators Yongtae G. Kim1,2, Manolo Garabini1, Stefan S. Groothuis1, Stefano Stramigioli1, Jaeheung Park2 and Antonio Bicchi1 and Raffaella Carloni1 1UNIPI, Centro E. Piaggio, Italy, 2SNU, Korea 1RaM, University of Twente, The Netherlands • Stroke response can be tuned • Modeling methodology of compliant systems actuated by stiffness variation. by variable stiffness actuators based on graph theory • Drum rolling stiffness was • For a given task, optimal actuator stiffness distribution calculated by modeling the can be found dynamics between drum • Framework can membrane and drum stick. assist in design • Drum rolling was implemented decisions in simulation and validated experimentally.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
205 Session WeB1 Grand Ballroom Wednesday, September 17, 2014, 10:50–12:10 Mechanisms and Actuators / Force and Tactile Sensing Chair Allison M. Okamura, Stanford University Co-Chair
11:25–11:28 WeB1.7 11:28–11:31 WeB1.8 Reaching desired states time-optimally from Force-Guiding Particles Chains for equilibrium and vice versa for visco-elastic Shape-Shifting Display joint robots with limited elastic deflection Matteo Lasagni1, Kay Römer1, Nico Mansfeld and Sami Haddadin 1Graz University of Technology German Aerospace Center (DLR) • Folding chains of robotic particles • Considered Problems: form a programmable 3D display 1. Which states can an elastic • Weak and simple mechanisms joint with limited deflection reach from equilibrium? in particles guide an external force to fold the chain 2. How can an elastic joint robot be stopped as fast • Simple and miniaturizable particles as possible? • Scalability: the smaller the particle, • Solutions for both problems provided for 1-DOF the higher the resolution and the • Braking extended to n-DOF and verified in experiment maximum length of a chain
11:31–11:34 WeB1.9 11:34–11:37 WeB1.10 A class of microstructures for HiGen: A High-Speed Genderless scalable collective actuation of Connection Mechanism with Single- Programmable Matter Sided Disconnect for Modular Robots P. Hołobut1, M. Kursa1, Jakub Lengiewicz1 C. Parrott, T. J. Dodd and R. Groß 1 IPPT PAN, Warsaw, Poland The University of Sheffield • One of key functionalities of real • Connects to another unit in a way Programmable Matter that allows either side to disconnect • Applies to large module ensembles in the event of failure • Strength proportional to volume • Faster than existing mechanical genderless connectors • Two types of connections: strong (fixed) and weak (reconfigurable) • Creates clearance between units, aiding modular self-reconfiguration • Several actuator designs • Passes power and communication • Analytical results & DEM simulations collective actuator
11:37–11:40 WeB1.11 11:40–11:43 WeB1.12 Stretchable Electroadhsion Miniature Capacitive Three-Axis Force for Soft Robots Sensor J. Germann1, B. Schubert1 and D. Floreano1 Rachid Bekhti1, V. Duchaine1, P. Cardou2 1Laboratory of Intelligent Systems, 1École de Technologie Supérieure Ecole Polytechnique Fédérale de Lausanne 2Laval University This project's research goal is to develop systematic, • Completely soft and inexpensive, method to enhance the design of multi- stretchable electrically- axis force sensors. Some advantages of the proposed controllable adhesive. approach are: • Simple fabrication for • Compactness and simple design. easy integration with • A good overall accuracy. soft robots. • Tunable shear and • A large range with acceptable normal adhesion force. cross-axis sensitivity. • A good robustness against noise and hysteresis.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
206 Session WeB1 Grand Ballroom Wednesday, September 17, 2014, 10:50–12:10 Mechanisms and Actuators / Force and Tactile Sensing Chair Allison M. Okamura, Stanford University Co-Chair
11:43–11:46 WeB1.13 11:46–11:49 WeB1.14
A Framework for Dynamic High-throughput analysis of the morphology and mechanics Sensory Substitution of tip growing cells using a microrobotic platform D. Felekis1, H. Vogler2, G. Mecja1, S. Muntwyler1, Artashes Mkhitaryan and Darius Burschka M. S. Sakar1, U. Grossniklaus2 and B. J. Nelson1 Technische Universität München, Germany 1IRIS, ETH Zürich 2University of Zürich • Automatic toolbox for configuration • Automated micromanipulation of new sensing modalities and characterization of single • Dynamic selection of an optimal cells processing chain for a specific • 3D topography and stiffness measurement task. maps • Extension of perceptual capabilities • Real-time probing and of a platform with limited number of Camera-based intracellular sensing physical sensors force sensor
11:49–11:52 WeB1.15 11:52–11:55 WeB1.16 What's in the Container? Classifying 3D Spatial Self-organization of a Modular Object Contents from Vision and Touch Artificial Skin Püren Güler1, Yasemin Bekiroğlu1, Philipp Mittendorfer, Emmanuel Dean, Xavi Gratal1, Karl Pauwels2 and Danica Kragic1 and Gordon Cheng 1KTH 2University of Granada ICS, Technische Universität München, Germany
body reference (r) Our robot identifies the content of v T om the container by grasping prior to v T (v)isual on applying manipulation actions to the origin skin cell container. We investigate the LEDs benefits of using unimodal (visual or r T tactile) or bimodal (visual-tactile) om om T o sensory data. Our results show that n the visual and the tactile data are skin patch origin (n) skin patch origin (m) complementary. www.ics.ei.tum.de www.cellulARSkin.eu
11:55–11:58 WeB1.17 11:58–12:01 WeB1.18 Detection of Membrane Puncture with Haptic Active Gathering of Frictional Feedback using a Tip-Force Sensing Needle Properties from Objects Santhi Elayaperumal1, Jung Hwa Bae1, C. Rosales1, A. Ajoudani2, Bruce L. Daniel2 and Mark R. Cutkosky1 M. Gabiccini1,2 and A. Bicchi1,2 1Stanford University 2Stanford Hospital 1Centro di Ric. “E. Piaggio” 2Ins. Italiano di Tecn. Tip-force sensing resulted in higher membrane detection • Gaussian Process to model rate (p<0.05) than feedback based on other sensors. shape and friction from Reconfigurable PVC Block sensory data. Membrane Phantom (Mass/Stiffening/Damping) • Exploration strategy exploits the model to find FBG 6-Axis Haptic Display geodesics on the surface.e. Embedded or F/T • Impedance controller to Needle Sensor perform a successful Slave side Master side contour following.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
207 Session WeB1 Grand Ballroom Wednesday, September 17, 2014, 10:50–12:10 Mechanisms and Actuators / Force and Tactile Sensing Chair Allison M. Okamura, Stanford University Co-Chair
12:01–12:04 WeB1.19 12:04–12:07 WeB1.20 Localization and Manipulation of Small Parts Using GelSight Tactile Sensing R. Li1, R. Platt Jr.2, W. Yuan1, A. ten Pas2, N. Roscup2, M. A. Srinivasan1 and E. H. Adelson1 C. Ciliberto1, L. Fiorio1, M. Maggiali1, L. Natale1, L. 1MIT 2Northeastern University Rosasco1, G. Metta1, G. Sandini1 and F. Nori 1 1 • GelSight fingertips provide Istituto Italiano di Tecnologia high-resolution 3D geometry • We equipped iCub feet with 250-pressure-sensors skin. of grasped parts • We present a method to estimate local skin compliance exploiting a • In-hand localization greatly transformation matrix to define a improves performance on a Baxter holds a USB cable with linear regression. GelSight sensor (left) and obtains cable insertion task the height map for localization (right) • Validation experiments performed directly on the iCub feet.
12:07–12:10 WeB1.21
Toward a Modular Soft Sensor-Embedded Glove for Human Hand Motion and Tactile Pressure Measurement Frank L. Hammond III, Yiğit Mengüç, and Robert J. Wood Harvard School of Engineering and Applied Sciences • Soft modular pressure and extension sensors were used to create a soft data glove • Enabled by novel wire routing Pressure Sensor soft sensor assembly methods • Glove provides static and dynamic motion and pressure data during human grasping Extension Finger Glove Sensor
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
208 Session WeB2 State Ballroom Wednesday, September 17, 2014, 10:50–12:10 Humanoids and Bipeds III / Human Detection and Tracking Chair Sylvain Bertrand, Institute for Human and Machine Cognition Co-Chair
10:50–11:10 WeB2.1 11:10–11:13 WeB2.2 3D-SLIP Steering for Keynote on Humanoids and Bipeds High-Speed Humanoid Turns Patrick M. Wensing, David E. Orin Electrical and Computer Engineering, Dennis Hong The Ohio State University, USA • Extends 3D-SLIP running control to high-speed turns. • Captures unique roles of the inside and outside legs. • Shows single-step changes in turn rate and direction while robust to push disturbances. • Demonstrates a high-speed
turn with a radius that is ¼ 3D-SLIP Steering with Whole-Body that of a 400m track. Control Enables High-Speed Turns
11:13–11:16 WeB2.3 11:16–11:19 WeB2.4
Emergence of humanoid walking behaviors Trajectory generation for continuous leg forces from Mixed-Integer Model Predictive Control during double support and heel-to-toe shift based on divergent component of motion 1 1,2 Aurélien Ibanez , Philippe Bidaud Johannes Englsberger1, T. Koolen2,3, S. Bertrand2, and Vincent Padois1 J. Pratt2, Ch. Ott1 and A. Albu-Schäffer1 1 Univ. Pierre et Marie Curie Paris 06, France 1DLR 2IHMC 3MIT 2 DSB-TIS, ONERA, France • 3D DCM-based trajectory generators • Novel predictive, ZMP-based for continuous double support and approach to walking and balancing heel-to-toe trajectories
• Use of a linear, mixed-integer model continuous adj. • Produce continuous leg forces and to coordinate discrete shifts and facilitate toe-off motion
continuous adjustments • Allow for walking over uneven terrain • Optimal control of walking motor discrete shifts • Tested in simulations and experiments activity without prior definition of gait patterns
11:19–11:22 WeB2.5 11:22–11:25 WeB2.6 MPC in Multi-Contact Motion Predictive Control for Dynamic Application to a Humanoid Robot Locomotion of Real Humanoid Robots H. Audren2,1, J. Vaillant2, A. Kheddar1,2, Stylianos Piperakis, Emmanouil Orfanoudakis, A. Escande1, K. Kaneko1 and E. Yoshida1 and Michail G. Lagoudakis 1CNRS-AIST JRL 2CNRS-UM2 LIRMM Technical University of Crete, Chania, Greece • Quick generation of CoM • Cart and Table model with ZMP control trajectories through MPC on a • Preview control with inverse system reduced model • Constrained linear model predictive control • Task-based whole-body • Rigid body interpolation for feet trajectories controller to track CoM • Sensor fusion for state estimation • Application to object • Handling of sensor noise, delay, and bias manipulation and multi-contact motion • Real-time omnidirectional walk on NAO •10ms control cycle, 21cm/s on rough terrain
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
209 Session WeB2 State Ballroom Wednesday, September 17, 2014, 10:50–12:10 Humanoids and Bipeds III / Human Detection and Tracking Chair Sylvain Bertrand, Institute for Human and Machine Cognition Co-Chair
11:25–11:28 WeB2.7 11:28–11:31 WeB2.8 A Robot-Machine Interface for Full- Planar Sliding Analysis of a Biped Robot functionality Automation using a Humanoid in Centroid Acceleration Space 1 1 1 Heejin Jeong , Sungwook Cho and D.H Shim Taku Senoo and Masatoshi Ishikawa 1 Korea Advanced Institute of Science and University of Tokyo, Japan Technology • State transition between sliding and takeoff is • RMI for a humanoid to pilot an formulated in centroid acceleration space airplane consists of Recognition, • Characteristics of the Decision, and Action. formulated diagram are • To validate, PIBOT (pilot robot) derived by comparison system is developed using a small with a cone of friction humanoid robot and flight simulation • Concrete behavior of a 2- equipment designed for humans. DOF model is analyzed • Simulation results: It can fly the with numerical simulation airplane from cold start to landing. 11:31–11:34 WeB2.9 11:34–11:37 WeB2.10 Energy Based Control of Compass Gait Analytical Control Parameters of the Soft Limbed Bipeds Swing Leg Retraction Method using an Isuru S. Godage, Yue Wang, and Ian D. Walker Instantaneous SLIP Model Clemson University, SC, USA. Natan Shemer, Amir Degani, • Investigate energy based control of Technion-Israel Institute of Technology compass gait soft bipeds. • The Swing Leg Retraction method is • Consider CL and IDA-PBC controllers known to increase the robustness of to evaluate performance, stability, legged running against ground height control effort, and speed variation. variations. • IDA-PBC controller showed better • Using an instantaneous SLIP model results over CL methods. we find optimal parameters analytically • Findings help in extending and developing novel and adapt them to the SLIP. controllers to soft limb robots for practical applications • We finally show simulations and experiments on the ParkourBot robot.
11:37–11:40 WeB2.11 11:40–11:43 WeB2.12
Task-Oriented Whole-Body Planning for Real-Time People Detection and Tracking Humanoids based on Hybrid Motion Generation for Indoor Surveillance Using Multiple Top-View Depth Cameras
M. Cognetti, P. Mohammadi, G. Oriolo, M. Vendittelli T.-E. Tseng1, A.-S. Liu1, P.-H. Hsiao1, C.-M. Sapienza University of Rome, Italy Huang2, L.-C. Fu1,IEEE Fellower • A humanoid is assigned a task (e.g., 1National Taiwan University, Taiwan manipulation) that requires stepping 2National Taipei University of Technology, Taiwan • The C-space submanifold compatible • Real-time indoor surveillance system with task is explored by concatenating – With multiple depth cameras feasible elementary motions – From zenithal (top-view) position • A hybrid scheme generates stepping • Detect human based on and whole-body motions concurrently – the hemiellipsoid head model • Sample plans generated for NAO are • Have 96% of F-score and outperforms validated by dynamic playback in V-REP than other algorithms
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
210 Session WeB2 State Ballroom Wednesday, September 17, 2014, 10:50–12:10 Humanoids and Bipeds III / Human Detection and Tracking Chair Sylvain Bertrand, Institute for Human and Machine Cognition Co-Chair
11:43–11:46 WeB2.13 11:46–11:49 WeB2.14 Robot-Assisted Human Indoor Localization Gesture-Based Attention Direction for a Using the Kinect Sensor and Smartphones Telepresence Robot C. Jiang1, M. Fahad1,Y. Guo1, J. Yang2, Y. Chen1 K. P. Tee, R. Yan,Y. Chua, 1Stevens Inst. of Tech. 2Florida State University Z. Huang and S. Liemhetcharat Institute for Infocomm Research, A*STAR • A robot-assisted localization system that uses the Kinect sensor and • Gesture-based attention direction smartphone-based acoustic rangingg using Localist Attractor Network to localize indoor moving persons and Short-Term Memory • An extended Kalman filter based • Fusion of gesture, speech and head localization algorithm is proposed cues to determine attention target for real-time dynamic position • Experiment results: estimation • 90% accuracy • Real robot-smartphone experiments • Robot as good as human in directing attention
11:49–11:52 WeB2.15 11:52–11:55 WeB2.16 Kinect-based People Detection and Track- Robust articulated upper body pose ing from Small-Footprint Ground Robot tracking under severe occlusions A. Pesenti Gritti1, O. Tarabini1, J. Guzzi2, G. A. Di M. Sigalas1,2, M. Pateraki1 and P. Trahanias1,2 Caro2, V. Caglioti1, L. M. Gambardella2, A. Giusti2 1Institute of Computer Science - FORTH 1Politecnico di Milano 2IDSIA, USI/SUPSI 2University of Crete, Computer Science Dept. • Depth image processing and • Articulated upper body pose candidate legs 3D point clusters tracking extraction • Employment of the User Top • Human legs classification based View facilitates: on supervised machine learning • Exemption of the • Combined usage of Kalman and initialization requirement PDAF filters to track legs and • coping with severe intra- and people barycenters over time inter-personal occlusions
11:55–11:58 WeB2.17 11:58–12:01 WeB2.18
Pedestrian Detection Combining RGB Confidence-Based Pedestrian Tracking in Unstructured And Dense LIDAR Data Environments Using 3D Laser Distance Measurements Cristiano Premebida1, João Carreira1,2, Marcel Häselich, Benedikt Jöbgen, Jorge Batista1 and Urbano Nunes1 Nicolai Wojke, Jens Hedrich, Dietrich Paulus 1ISR, DEEC, Univ. of Coimbra. 2UC Berkeley. Active Vision Group, University of Koblenz-Landau, Germany • New dense depth-map upsampling • Ground removal & 3D LRF features method using LIDAR only Depth RGB • Clustering with dp-means Map • 3D Velodyne and mono-camera Upsampling Image • Classification with a SVM Def.Part fusion (experiments: KITTI dataset) Model (HOG) • Confidence-based particle filter • Def. Part-Models + SVM-based • Trails store the information where rescoring strategy pedestrians moved SVM-rescoring • High performance on KITTI + NMS • Especially designed for unstructured benchmarking Final detection environments
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
211 Session WeB2 State Ballroom Wednesday, September 17, 2014, 10:50–12:10 Humanoids and Bipeds III / Human Detection and Tracking Chair Sylvain Bertrand, Institute for Human and Machine Cognition Co-Chair
12:01–12:04 WeB2.19 12:04–12:07 WeB2.20 Pedalvatar: An IMU-Based Real-Time Body Motion Capture System ! " #$ % ! % Yang Zheng, Ka-Chun Chan, Charlie C.L. Wang &' ( ) !* ( ( $& + ( ) The Chinese University of Hong Kong • 1 • A foot rooted kinematic model to image capture motions with a static foot • A state machine to control the any text in the • switch of roots to reconstruct full- image should body motions be the same • • An IMU-based system can be used size as main outdoor to capture body motions in text real-time
12:07–12:10 WeB2.21 Sponsor Talk: TOYOTA – Partner Robot Joseph Djugash Toyota Motor Eng. & Manuf. North America
• Enriching Quality of Life through Robotic Innovations • Build robots that embody "kindness" & "intelligence" and assist with human activities in: • Elder care • Manufacturing • Mobility
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
212 Session WeB3 Red Lacquer RoomWednesday, September 17, 2014, 10:50–12:10 Collision Detection and Avoidance / Sensing II Chair Bruce MacDonald, University of Auckland Co-Chair
10:50–11:10 WeB3.1 11:10–11:13 WeB3.2
Keynote: Real-Time Collision Avoidance in Human-Robot Bayesian Perception & Decision Interaction Based on Kinetostatic Safety Field From Theory to Real World Applications Christian Laugier M. Parigi Polverini, A.M. Zanchettin, P. Rocco Inria France Politecnico di Milano, Italy Navigable space • Multi-Sensors Bayesian Fusion for & Collision risk • Safety assessment for human- Open & Dynamic Environments robot interaction • Situation Awareness using Sensing • Complete geometry of robot data & Semantic knowledge and obstacles • Future Scene changes Prediction • Real-time control law & Collision Risk Assessment capturing relative position and • Decision making under uncertainty velocity & Application to Automatic Driving
11:13–11:16 WeB3.3 11:16–11:19 WeB3.4 Determining States of Inevitable Collision Prediction Among Polygons Collision using Reachability Analysis with Arbitrary Shape & Unknown Motion Andreas Lawitzky, Anselm Nicklas, Yanyan Lu, Zhonghua Xi and Jyh-Ming Lien Dirk Wollherr and Martin Buss Department of Computer Science, LSR, Technische Universität München, Germany George Mason University, USA • Advance collision prediction beyond • Motion safety has to be guaranteed disc robots beyond limited time horizons • Provide a complimentary approach • The set of states leading inevitably to those that consider behavior and to a collision is equal to the dynamics with simple shapes backwards minimal reachable set • Significantly reduce the number of • This set is determined using theory replans while maintain higher from reachability analysis success rate
11:19–11:22 WeB3.5 11:22–11:25 WeB3.6 Unified GPU Voxel Collision Detection A Practical Reachability-Based Collision for Mobile Manipulation Planning Avoidance Algorithm A. Hermann1, F. Drews1, J. Bauer1, Charles Dabadie1, Shahab Kaynama2 and Claire S. Klemm1, A. Rönnau1, R. Dillmann1 J. Tomlin2 1 FZI Karlsruhe, Germany 1ISAE Supaero 2UC Berkeley • Efficient collision detection for • Pursuer-evader framework robotic planning and monitoring • Pursuer considered as • Highly parallelized algorithms unpredictable executed on GPU • Dynamical capacities considered • Use-case optimized structures: • Safe piecewise constant control Octree, Voxel map, Voxel list using reachability analysis • Live point cloud and • Very light online computation Swept Volume handling • Application to Pioneer ground robots
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
213 Session WeB3 Red Lacquer RoomWednesday, September 17, 2014, 10:50–12:10 Collision Detection and Avoidance / Sensing II Chair Bruce MacDonald, University of Auckland Co-Chair
11:25–11:28 WeB3.7 11:28–11:31 WeB3.8 Time Scaled Collision Cone Based A Representation Method Based on the Planning in Dynamic Environments Probability of Collision S.A.M. Coenen1, J.J.M. Lunenburg1, B.Gopalakrishnan, A.K Singh,K.M Krishna M.J.G. van de Molengraft2 and M. Steinbuch3 RRC, IIIT Hyderabad, India 1Eindhoven University of Technology • Two primary Contributions: • Probabilistic integration of sensor measurements 1) Computationally efficient method, for • Time dependent occupancy probability model computing the intersecting space of non-linear and non-convex collision • Robot uncertainty: bivariate normal distribution cone constraints of large number of • Combine occupancy probability with position predicted obstacle trajectories. uncertainty 2) Optimization framework to connect • Select safe velocity based on probability of collision the current state to the solution space in time optimal fashion.
11:31–11:34 WeB3.9 11:34–11:37 WeB3.10 Real-Time 3D Collision Avoidance for Biped Robots 1 1 Arne-Christoph Hildebrandt , Robert Wittmann , # $ %& ' $ () 1 Daniel Wahrmann, Alexander Ewald and * % 1 Thomas Buschmann %+# ,& )-# + 1Technische Universität München
• Allows to overcome arbitrarily shaped obstacles • Locally optimized trajectories exploiting all swing-foot DoFs • Real-time application and experimental validation !"
11:37–11:40 WeB3.11 11:40–11:43 WeB3.12 A Unified Framework for External Deterioration of Depth Measurements Wrench Estimation, Interaction Control Due to Interference of Multiple RGB-D Sensors and Collision Reflexes for Flying Robots Roberto Martín Martín, Malte Lorbach and Oliver Brock 1 2 Teodor Tomić , Sami Haddadin , Robotics and Biology Lab, Technische Universität Berlin 1German Aerospace Center (DLR) 2Leibniz University Hanover • Are you using Kinect sensors? Then you should know that they can • An external wrench estimator for greatly interfere with each other! flying robots enables: • Exhaustive analysis of interference • Interaction: impedance and between two RGB-D active sensors admittance control; inertia shaping • Propose simple guidelines to • Collision reflexes: detection, Black = failure due minimize the interference reaction and contact location to interference on a sphere
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
214 Session WeB3 Red Lacquer RoomWednesday, September 17, 2014, 10:50–12:10 Collision Detection and Avoidance / Sensing II Chair Bruce MacDonald, University of Auckland Co-Chair
11:43–11:46 WeB3.13 11:46–11:49 WeB3.14 IMU/LIDAR based positioning of a A Quantitative Evaluation of Surface gangway for maintenance operations on Normal Estimation in Point Clouds wind farms Krzysztof Jordan1 and Philippos Mordohai1 1 1 Pierre Merriaux , Rémi Boutteau , 1Stevens Institute of Technology Pascal Vasseur2 and Xavier Savatier1 1IRSEEM 2LITIS • Surface normal estimation from • Exteroceptive system for the unorganized point clouds is well- contactless control of a motion- studied and has many applications compensated gangway • We evaluate the effects of • Algorithm evaluated in real-time 3D implementation choices on normal simulation chain fed with data from estimation in small neighborhoods • Results on data with ground truth actual measurements Color-coded error corrupted by additive noise maps
11:49–11:52 WeB3.15 11:52–11:55 WeB3.16 View Planning for 3D Object Planar Pose Estimation for General Reconstruction with a Mobile Cameras using Known 3D Lines Manipulator Robot Pedro Miraldo and Helder Araujo, J. I. Vasquez1, L.E. Sucar1, Institute for Systems and Robotics Dep. Electrical and Computer Engineering 2 1 2 R. Murrieta-Cid INAOE, Mexico CIMAT Mexico University of Coimbra, Portugal • The proposed method plans views • First planar solution for the pose directly in the configuration space. using known 3D straight lines, • It is based on a fast evaluation and under the framework of rejection of candidate configurations. generalized camera models; • The utility function is implemented as • Simple, fast and robust a series of filters. formulation that can be easily • We present experiments with a real implemented; mobile manipulator robot.
11:55–11:58 WeB3.17 11:58–12:01 WeB3.18 GPS-based Preliminary Map Estimation Dynamic Objects Tracking with a Mobile for Auto. Vehicle Mission Preparation Robot using Passive UHF RFID Tags Yohan Dupuis1, P. Merriaux2, P. Subirats1, R. Ran Liu, Goran Huskic, and Andreas Zell Boutteau2, X. Savatier2, P. Vasseur3 University of Tuebingen 1Cerema 2IRSEEM 3LITIS • Map estimation from a small set of • Dynamic objects tracking using the of vehicular GPS traces collected signal strengths from RFID tags. from low cost devices. • The VFH+ (Vector Field Histogram) • Map estimation compared to digital serves as a local path planner for maps and RTK INS/GPS solution. obstacle avoidance and navigation. • Median error of 2.96m compared to • Our solution provides an alternative RTK INS/GPS solution of the-state-of-the-art object tracking approaches.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
215 Session WeB3 Red Lacquer RoomWednesday, September 17, 2014, 10:50–12:10 Collision Detection and Avoidance / Sensing II Chair Bruce MacDonald, University of Auckland Co-Chair
12:01–12:04 WeB3.19 12:04–12:07 WeB3.20
Spatio-Temporal Motion Features for Laser-based The Role of Target Modeling in Moving Objects Detection and Tracking Designing Search Strategies X. Shen1, S. Kim2 and M. H. Ang Jr.1 Alessandro Renzaglia, Narges Noori 1National University of Singapore and Volkan Isler 2Singapore-MIT Alliance for Research and Technology University of Minnesota, USA • Motion features, similar to optical flow, • Problem: Searching for an unknown were extended for LIDAR sensors to mobile target in a bounded 2D area detect moving objects while sensors • We investigate what impact the target are moving. motion model has on designing
• Sensing uncertainties were search strategies
incorporated to improve the accuracy. • We consider three target models: Motivating fish Stationary, Adversarial, Stochastic • Support Vector Machine classification tracking • For each model, strategies are was performed to find moving objects. application presented and compared in simulation
12:07–12:10 WeB3.21 Advances in Fibrillar On-Off Polymer Adhesive: Sensing and Engagement Speed
Nicholas Wettels1, Aaron Parness1 1NASA Jet Propulsion Laboratory
• Gecko inspired fibrillar adhesive • Fast actuation (<16 msec) • Senses • Pad engagement • Range (up to 60 cm) • Normal Loading (up to 175N)
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
216 Session WeC1 Grand Ballroom Wednesday, September 17, 2014, 14:00–15:20 Surgical Robotics II / Teleoperation and Telerobotics Chair William R. Hamel, University of Tennessee Co-Chair
14:00–14:20 WeC1.1 14:20–14:23 WeC1.2
Keynote: Surgical Robotics: Transition Bimanual Telerobotic Surgery With Asymmetric Force Feedback: A to Automation daVinci surgical system implementation Blake Hannaford Omid Mohareri1, Caitlin Schneider1, and Septimiu Salcudean1 University of Washington 1Robotics and Control Lab, University of British Columbia • Surgery is a very challenging application • A novel control framework to for autonomy enable haptic feedback for two- handed tasks in teleoperated • Very unstructured robot-assisted surgery environment • The technique is implemented on • High cost of error the da Vinci surgical system using • Need for automation the da Vinci Research Kit (dVRK) with human controllers and user studies have accountability been conducted.
14:23–14:26 WeC1.3 14:26–14:29 WeC1.4 First 3D Printed Medical Robot Mass and Inertia Optimization for Natural for ENT Surgery Motion in Hands-On Robotic Surgery Konrad Entsfellner, Ismail Kuru, Joshua G. Petersen1, Thomas Maier , Jan D.J. Gumprecht, Ferdinando Rodriguez y Baena1, and Tim C. Lueth - Technical University Munich 1Imperial College London • Challenging interventions in ENT surgery due to • In hands-on robotic surgery, the surgeon small anatomic structures controls a tool attached to the robot’s end effector by applying forces directly. • Demand for cheap, simple and customizable single-use robots • End effector mass and inertia contribute to the user’s ability to move the tool and • Development and evaluation of therefore, the performance of the surgery. 3D printed robot using selective laser sintering of PA2200 • Optimization of the mass/inertia in the redundancy allows for easier, more • Monolithic structure, compliant linear mechanisms uniform, and more natural tool motion.
14:29–14:32 WeC1.5 14:32–14:35 WeC1.6 Interleaved Continuum-Rigid Using Monocular Images to Estimate Interaction Manipulation Approach Forces During Minimally Invasive Surgery Development and Functional Evaluation of a Clinical Scale Manipulator Benjamin ConradConrad, Michael Zinn Ehsan Noohi, Sina Parastegari, Miloš Žefran University of Illinois at Chicago
• Lack of haptic feedback in MIS can lead to tissue damage • Augmented Reality can enhance the MIS image with force information • Force is estimated from the organ deformation & tool penetration depth • Proposed algorithm introduces virtual template concept • In-vitro experiments with lamb liver are presented
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
217 Session WeC1 Grand Ballroom Wednesday, September 17, 2014, 14:00–15:20 Surgical Robotics II / Teleoperation and Telerobotics Chair William R. Hamel, University of Tennessee Co-Chair
14:35–14:38 WeC1.7 14:38–14:41 WeC1.8 Recursive Estimation of Needle Pose Development of Multi-Axial Force for Control of 3D-Ultrasound-Guided Sensing System for Haptic Feedback Robotic Needle Steering Enabled Minimally Invasive Troy Adebar and Allison Okamura Robotic Surgery Stanford University Dong-Hyuk Lee1, UiKyum Kim1, and Hyouk Ryeol Choi1 • Unscented Kalman filter 1Sungkyunkwan Univ., Korea allows accurate needle tip measurements from • 3-Axial Cartesian force and noisy 3D ultrasound. grasping force sensing capability • This significantly • High-resolution based on improves image-guided capacitive sensing robotic steering accuracy • Considerations for low-cost in ex vivo liver tissue. fabrication and disposability
14:41–14:44 WeC1.9 14:44–14:47 WeC1.10 Estimation of Needle-Tissue Interaction based on Design and Realization of Grasper- Non-linear Elastic Modulus and Friction Patterns Integrated Force Sensor for Minimally Inko Elgezua, Yo Kobayashi, and Masakatsu G. Invasive Robotic Surgery Fujie, Fellow IEEE. Uikyum Kim1, Dong-Hyuk Lee1, Hyungpil Moon1, Fujie Laboratory, Waseda University Ja Choon Koo1 and Hyouk Ryeol Choi1 1 • Needle Tissue interaction is analyzed based on: Sungkyunkwan University, Korea – Non-Linear elastic modulus Repeated Punctures fitted locally • Grasper-integrated force sensor – Friction patterns • Capacitive-type sensor
• Four different interaction states 2 F(x)= KLx - KNLx • Triangular prism structure were found. • Measuring sensing elements
• A novel algorithm for puncture General Friction • Normal and shear forces Trend detection was also proposed. • Pulling and grasping forces Sensorized forceps
14:47–14:50 WeC1.11 14:50–14:53 WeC1.12 A biomechanical model describing tangential tissue deformations during Industrial Robotic Assembly Process Modeling contact micro-probe scanning Using Support Vector Regression B. Rosa1,2, J.Szewczyk2 and G.Morel2 Binbin Li, Heping Chen, Tongdan Jin Texas State University San Marcos 1KU Leuven, Belgium 2ISIR, UPMC-CNRS- INSERM, France • Propose an assembly process modeling method based on support vector regression • Tangential deformations occur when that constructs a model by observing the sweeping a probe over the surface relationship between the assembly parameters of soft tissues. and assembly output. • A simple 2D model with local elastic • Demonstrate the effectiveness of proposed deformations and Coulomb friction is method by experiments using a robotic valve proposed. body assembly process in automotive manufacturing. • Experiments involving robotically • Prove the accuracy of the method and the controlled movements of an proposed algorithm is capable of modeling endomicroscopic probe prove the complex assembly processes. validity of the model.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
218 Session WeC1 Grand Ballroom Wednesday, September 17, 2014, 14:00–15:20 Surgical Robotics II / Teleoperation and Telerobotics Chair William R. Hamel, University of Tennessee Co-Chair
14:53–14:56 WeC1.13 14:56–14:59 WeC1.14 Teleoperation System using Past Image Records Virtual Fixtures for Object for Mobile Manipulator Telemanipulation Ryosuke Murata1, Sira Songtong2, Hisashi Mizumoto3, H. Hawkeye King1,2, Blake Hannaford1, Kazuyuki Kon1 and Fumitoshi Matsuno1 1University of Washington 1Kyoto University 2Komatsu Ltd. 3NEC Corporation, Japan 2Imperial College London
• A new user interface for • Evaluation of virtual fixtures a mobile manipulator focusing oonn compares manual and assisted the manipulation task telemanipulation. • A user can operate the end- • Experiments use the Raven II effector from the virtual third-person viewpoint surgical system, with Mantis Duo Master. • The experiment shows that the proposed system reduces • Advantages and disadvantages of operators’ workloads and improvesoves state-of-the-art VF design are situation awareness The concept of the proposed system illustrated.
14:59–15:02 WeC1.15 15:02–15:05 WeC1.16 Investigating Human Perceptions of Robot Designing Human-Robot Interaction Capabilities in Remote Human-Robot Team Paradigms for Multi-robot Manipulation Tasks based on First-Person Robot Video Feeds Bennie Lewis1 and Gita Sukthankar1 Cody Canning, Thomas Donahue and Department of EECS (CS) Matthias Scheutz, HRI Lab, Tufts University, USA University of Central Florida1 • We investigate possible effects of • Examination of expert-novice image simulated versus real first-person differences in user
robot video feeds in HRI team tasks performance with different any text in the types of intelligent interfaces. • We found a complex interplay image should between task investment, robot be the same • Source code and robot appearance, and realism of 1st- size as main design available at: person video feed as they affect text ial.eecs.ucf.edu/code.php human perceptions of robot teammates
15:05–15:08 WeC1.17 15:08–15:11 WeC1.18 Modeling Visuo-Motor Control and Guidance Transparency Compensation for Bilateral Functions in Remote-Control Operation Teleoperators with Time-Varying Delays Jonathan Andersh1, Bin Li1, Erick J. Rodríguez-Seda and Bérénice Mettler1 United States Naval Academy 1University of Minnesota • Characterize coupling • Closed-loop stability guaranteed Master between gaze and human regardless of time-varying delays control input during remote • Transparency compensated when control flight the slave robot transitions between Slave Wall • Model the visuo-motor free motion and hard contact mechanisms from • Perceived impedance adapted online experimental data • Position drifts reduced while in contact • Estimate vehicle state and • Stable interaction with non-passive human operators task elements from gaze data
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
219 Session WeC1 Grand Ballroom Wednesday, September 17, 2014, 14:00–15:20 Surgical Robotics II / Teleoperation and Telerobotics Chair William R. Hamel, University of Tennessee Co-Chair
15:11–15:14 WeC1.19 15:14–15:17 WeC1.20
Model-free Path Planning for Redundant Robots Learning Task Outcome Prediction for using Sparse Data from Kinesthetic Teaching Robot Control from Interactive Env. Andrei Haidu1, Daniel Kohlsdorf2 D. Seidel1, C. Emmerich1 and J. J. Steil1 and Michael Beetz1 1Bielefeld University 1Universität Bremen 2GATECH • purely data-driven approach for • Extraction and learning of autonomous path planning for action and common sense redundant robot arm (LWR IV) knowledge from a cooking • data gathered by structured user based game running on a interaction: kinesthetic teaching in confined spaces robot-simulator with realistic rigid body physics. • Instantaneous Topological Map + bootstrapping heuristics learns a • Task outcome prediction navigation graph of the algorithm for the given system obstacle-free workspace
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
220 Session WeC2 State Ballroom Wednesday, September 17, 2014, 14:00–15:20 Learning by Demonstration / Industrial and Manufacturing Robotics Chair Lynne Parker, University of Tennessee Co-Chair
14:00–14:20 WeC2.1 14:20–14:23 WeC2.2
Keynote: Machine Learning of Motor A Robust Autoregressive Gaussian Process Skills for Robotics Motion Model Using l1-Norm Based Low-Rank Jan Peters Kernel Matrix Approximation IAS, TU Darmstadt & MPI for Intelligent Systems Eunwoo Kim, Sungjoon Choi, and Songhwai Oh Seoul National University, Korea • Machine learning (ML) is crucial to • Address the measurement noise or outlier endow robots both with more issues by proposing a robust AR-GP model abilities and more autonomy. • However, off-the-shelf ML rarely • Show the relationship between GP and low- rank kernel approximation scales to robotics.
• We present recent successes at • For robustness, l1-norm based low-rank domain-appropriate approaches to kernel approximation is proposed robot learning for anthropomorphic • Successfully avoided moving pedestrians robots. without any collisions and arrived at the goal
14:23–14:26 WeC2.3 14:26–14:29 WeC2.4 Learning from Demonstrations for Robot Learns Chinese Calligraphy Manipulation of Deformable Objects from Demonstrations Alex Lee, Sandy Huang, Dylan Hadfield-Menell, Yuandong Sun1 Huihuan Qian1,3 Yangsheng Xu2,3 Eric Tzeng and Pieter Abbeel 1The Chinese University of Hong Kong University of California, Berkeley 2The Chinese University of Hong (Shenzhen) 3Shenzhen Institutes of Advanced Technology • Schulman et al. [ISRR 2013] predict gripper motions for a new scene by first finding • Proposed a new approach to stroke a registration between training scene parameterization and new scene, and then extrapolating • Applied Locally Weighted Linear this registration to transfer training Regression to map from stroke scene gripper motion to new scene parameters to brush trajectory • Challenge addressed: optimizing the • The robot can learn to write new scene's gripper motion when calligraphy from demonstrations predicted motion is not executable by robot
14:29–14:32 WeC2.5 14:32–14:35 WeC2.6 Learning to Sequence Movement Kinematically Optimised Predictions Primitives from Demonstrations of Object Motion Simon Manschitz1,2, Jens Kober2,3, Dominik Belter1,2, Marek Kopicki1, Michael Gienger2 and Jan Peters1 Sebastian Zurek1 and Jeremy Wyatt1 1TU Darmstadt 2Honda RI-EU 3Univ. Bielefeld 1Univ. of Birmingham 2Poznan Univ. of Technol. • Sequence demonstrated • This paper shows how to obtain Kin. Demonstrations Reproduction • Robot learns when to learned simulator of specific objects perform which action • The learner predicts trajectories for • Graph structure generalizes the object. These are optimised post from demonstrations prediction to minimise • Switching behavior learned interpenetrations according to the with multiple classifiers collision checker • The method is experimentally verified 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
221 Session WeC2 State Ballroom Wednesday, September 17, 2014, 14:00–15:20 Learning by Demonstration / Industrial and Manufacturing Robotics Chair Lynne Parker, University of Tennessee Co-Chair
14:35–14:38 WeC2.7 14:38–14:41 WeC2.8 Program Synthesis by Examples for LAT: A Simple Learning from Object Repositioning Tasks Demonstration Method Benjamin Reiner, Wolfgang Ertel, Ashley Feniello, Hao Dang, and Stan Birchfield Heiko Posenauer and Markus Schneider Microsoft Research Univ. of Appl. Sci. Ravensburg-Weingarten • A learning-by-demonstration framework is presented. • Learning by Averaging Trajectories • Tablet-based interface enables rapid robot teaching. • Very easy and efficient • Generic stack-based concatenative domain-specific mathematics language models object repositioning tasks. • Approximate a normal distribution • Human readable programs over trajectories are learned through a novel • Join trajectories by multiplying learning algorithm based on normal distributions human demonstrations. • Linear time complexity
14:41–14:44 WeC2.9 14:44–14:47 WeC2.10 Discovering Task Constraints Through Unsupervised object individuation Observation and Active Learning from RGB-D image sequences S. Koo1, D. Lee1, and D.-S. Kwon2 Bradley Hayes, Brian Scassellati 1Dep. EE and IT, TUM, Germany Yale University 2Dep. ME, KAIST, Korea • We use Active Learning to expedite • Integration of location-based and robot task comprehension from feature-based object segmentation human demonstrations methods based on the infant’s • We present a query generation object indexing theory. RGB-D data strategy that encourages instructor
demonstration diversity • Computational efficiency and
• Small groups of instructors perform robustness in stacking, unstacking,
better than an individual given the and occluding tasks. Result data same number of total demonstrations 14:47–14:50 WeC2.11 14:50–14:53 WeC2.12 Grasp Planning Based on Grasp Stiffness Modeling of Industrial Robots for Strategy Extraction from Demonstration Deformation Compensation in Machining Ulrich Schneider1, Mahdi Momeni-K1, Yun Lin, Yu Sun, Matteo Ansaloni2 and Alexander Verl1 1University of South Florida 1Fraunhofer IPA 2University of Modena • We extracted the thumb placement A new stiffness modeling and identification method for and grasp type from human industrial robots is presented and validated on a demonstration KR125. 36 nonlinear functions are used to describe the stiffness of robot joints. Validation in machining process • Both human strategies Mapped to • are independent of robotic shows the improvement kinematics achieved through compliance compensation • represent human intentions based on wrench • highly constrain the hand measurement on the TCP. configuration space 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
222 Session WeC2 State Ballroom Wednesday, September 17, 2014, 14:00–15:20 Learning by Demonstration / Industrial and Manufacturing Robotics Chair Lynne Parker, University of Tennessee Co-Chair
14:53–14:56 WeC2.13 14:56–14:59 WeC2.14
A Study on Data-Driven In-Hand Twisting Process Using a Velocity Coordination and Corner Novel Dexterous Robotic Gripper for Assembly Automation Matching in a Multi-Robot Sewing Cell 1 2 2 Fei Chen, Ferdinando Cannella, Carlo Canali, Mariapaola J. Schrimpf , M. Bjerkeng and G. Mathisen D'Imperio, Traveler Hauptman, Giuseppe Sofia, Darwin Caldwell 1Norwegian University of Science and Technology Department of Advanced Robotics, Istituto Italiano di Tecnologia, Italy 2SINTEF ICT • Design a novel reconfigurable • A sewing demonstrator is industrial gripper for precise twisting presented and the control • Analyze the kinematic and dynamic algorithms are described. • Study the twisting course • A leader/follower coordination • Study the success condition for strategy is proposed to achieve twisting based on theoretical and corner matching. experimental study • Experiments are included, demonstrating corner matching.
14:59–15:02 WeC2.15 15:02–15:05 WeC2.16 On the Location of the Center of Mass Design and motion planning of for Parts with Shape Variation body-in-white assembly cells 1,2,3 1 Fatemeh Panahi A. Frank van der Stappen S. Pellegrinelli , N. Pedrocchi , 1 2 1,3 Utrecht University L. Molinari Tosatti , A. Fischer and T. Tolio 1ITIA-CNR 2Technion 3Politecnico di Milano
• General model for shape variation • Multi-robot cell for body-in-white assembly • Characterize worst-case displacement • Automatic and simultaneous of center of mass (COM) identification of cell design and multi- • k-facet outer approximation of COM robot motion plan locus in O(kn log n) time, where n is • 4-step iterative algorithm for global object complexity optimum identification addressing • Bounds on diameter of COM locus for collision detection fat objects • Decrease of the engineer-to-order time
15:05–15:08 WeC2.17 15:08–15:11 WeC2.18 Cartesian Sensor-less Force Control Improving the Sequence of Robotic for Industrial Robots Tasks with Freedom of Execution Hyunchul Cho, Minjeong Kim, Sergey Alatartsev and Frank Ortmeier Hyunkyu Lim and Donghyeok Kim Otto-von-Guericke University of Magdeburg Hyundai Heavy Industries Co. Ltd.
• Contact forces were estimated using a DOB. • Robot tasks often allow a certain • Frictions at each joint were suppressed by the dither. freedom of execution • The desired impedance characteristicharacteristic • This freedom is used to optimize: was realized with position and orientation of the end- the position servo of effector and robot configuration HHI’s robot controller. • Proposed approach is evaluated on scenarios from cutting/deburring domain Details and Demo
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
223 Session WeC2 State Ballroom Wednesday, September 17, 2014, 14:00–15:20 Learning by Demonstration / Industrial and Manufacturing Robotics Chair Lynne Parker, University of Tennessee Co-Chair
15:11–15:14 WeC2.19 15:14–15:17 WeC2.20 Parallel Active/Passive Force Control of Automated guidance of peg-in-hole Industrial Robots with Joint Compliance assembly tasks for complex-shaped parts 1 1 Arun Dayal Udai1, Abdullah Aamir Hayat1, Hee-Chan Song , Young-Loul Kim , 1 Subir Kumar Saha2 and Jae-Bok Song 1 Indian Institute of Technology Delhi Korea university, Seoul, Korea • We propose an assembly strategy • Active force control is attained for complex-shaped parts which using external force control. performs force control based on • In parallel a passive joint visually-obtained geometric compliant-like behavior is information and CAD models. proposed which is based on • A proposed guidance algorithm is actuator current limiting. based on selecting an optimal • The proposed controller makes the system safe against assembly direction. any hazards due to pinching, trapping and impact. • An impedance control scheme is • A precise force/position control was also be obtained. used to control the contact force. 15:17–15:20 WeC2.21 Intuitive skill-level programming of handling tasks on a mobile manipulator Mikkel Rath Pedersen1, Dennis Levin Herzog1 and Volker Krüger1 1Aalborg University Copenhagen, Denmark • Novel skill-level programming imageimmagage approach for industrial robots,
combining a GUI and gesture anyanany texttetexxtt inin theththe recognition for task programming imageiimmaagge sshshouldhououldld • Thorough evaluation of the bbee thethhee samesaamme approach, verifying that the use sizesisizzee asas mainmmaainin case task can be programmed in texttteexxtt as little as two minutes
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
224 Session WeC3 Red Lacquer RoomWednesday, September 17, 2014, 14:00–15:20 Localization and Mapping IV / Locomotion, Navigation, and Mobility Chair Gianluca Antonelli, Univ. of Cassino and Southern Lazio Co-Chair
14:00–14:20 WeC3.1 14:20–14:23 WeC3.2 Keynote: Toward Persistent SLAM in Challenging Environments Ryan Eustice Timothy Morris, Feras Dayoub, University of Michigan Peter Corke and Ben Upcroft QUT, CyPhy Lab • SLAM has come a long way in the last couple of decades • Online ranking of maps to determinee the most useful at any particular • This talk will describe some of moment. our current work toward fielding operational vehicles • Map u that use SLAM as their main navigation scheme in long- term deployments Autonomous Ship Hull Inspection • Factor graph used for robust exclusion of aliased localization. 14:23–14:26 WeC3.3 14:26–14:29 WeC3.4 Long-Term Top. Localization in Changing SAIL-MAP : Loop-Closure Detection Environments using Spectral Maps Using Saliency-Based Features T. Krajník 1, J. P. Fentanes1,O.M.Mozos1, Merwan BIREM1, Jean-Charles QUINTON1, Tom Duckett1, Johan Ekekrantz2, Marc Hanheide1 François Berry1 and Youcef MEZOUAR1 1University of Lincoln, UK 2KTH, Sweden 1Blaise Pascal University - Institut Pascal • learns long-term environment dynamics • The problem : Given two images what is the probability that these two • predicts environment appearance at a given time images shows the same scene. • significantly improves robustness or localization • Solution : Use the salient region as feature to match between the different images. Salient regions are known to be quite discriminative, robust to viewpoint change and image perturbations, as well as having a high repeatability rate
14:29–14:32 WeC3.5 14:32–14:35 WeC3.6 Visual Place Recognition using Linear-Time Estimation with Tree ADF HMM Sequence Matching and Low-Rank Approximation Peter Hansen1 and Brett Browning2 Duy-Nguyen Ta1, Frank Dellaert1, 1Carnegie Mellon University in Qatar 1Georgia Institute of Technology 2Carnegie Mellon University/NREC • Visual place recognition using • Two filtering-based SLAM methods query/database sequence maintaining tree structures to matching in HMM framework. achieve linear-time complexity • Local and flexible velocity/state • Tree Assumed Density Filtering transition constraints. optimally projects densities to trees • Similarity matrix rank reduction • ITF reduces information loss using ? for robust scoring. low-rank approximation with new • Evaluated on multiple datasets. latent variables
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
225 Session WeC3 Red Lacquer RoomWednesday, September 17, 2014, 14:00–15:20 Localization and Mapping IV / Locomotion, Navigation, and Mobility Chair Gianluca Antonelli, Univ. of Cassino and Southern Lazio Co-Chair
14:35–14:38 WeC3.7 14:38–14:41 WeC3.8 Large-Scale Image Mosaicking using Multimodal Hyperedge Localization Algorithm Based on Zigbee Constraints from Multiple Registration Methods within the Generalized Graph SLAM Framework Wireless Sensor Network with Application to an Active Shopping Cart M. Pfingsthorn, A. Birk, F. Ferreira, Shengnan Gai, Eui-Jung Jung, G. Veruggio, M. Caccia and G. Bruzzone Byung-Ju Yi炻Hanyang University
• Large scale marine image mosaic • This paper proposed a probability X G Y localization algorithm based on G • Uncertain loop hypotheses (~20% 3
A A A A 4 2 3 4 5 L hybrid sensor system with O R outliers) used as hyperedges G L 5 G R A L A
application to an active shopping cart Y (m) 6 • Two separate registration methods A 7 Measured data 8
Estimated data RO (ASC)in a given experimental Given path 8 Odometry A fused in multimodal constraints ASC localization E E 9 o A 9 S
environment. 8 10 12 14 16 18 • Prefilter (bottom) outperforms X (m ) • The hybrid sensor system helps to Fig. 1 Comparison of the proposed state-of-the-art (top) by orders of ASC localization method and odometry method magnitude improve the localization performance of the ASC
14:41–14:44 WeC3.9 14:44–14:47 WeC3.10 RF Odometry for Localization in Pipes Multi-Vehicle Localisation with Additive Based on Periodic Signal Fadings Compressed Factor Graphs Carlos Rizzo1, Vijay Kumar2, Lachlan Toohey, Oscar Pizarro, Francisco Lera1 and José Luis Villarroel1 and Stefan B. Williams 1Univ. of Zaragoza 2Univ. of Pennsylvania ACFR, University of Sydney • Accurate localization is a problem • Minimises bandwidth to solve full history inside pipes due to the nature of the for each vehicle using all information environment and the lack of • Permits relinearisation of local states exploitable features. • Size of data transmitted dependent only • We present a RF odometry-like on intervehicle observation rate not method for in-pipe longitudinal local sensor measurement rate localization based on periodic • Single iteration equivalent to single received signal fadings. iteration of centralised solution.
14:47–14:50 WeC3.11 14:50–14:53 WeC3.12 Building Local Terrain Maps HexaMorph: A Reconfigurable and Using Spatio-Temporal Classification Foldable Hexapod Robot Inspired by for Semantic Robot Localization Origami Stefan Laible and Andreas Zell Wei Gao, Ke Huo, Jasjeet S. Seehra, Cognitive Systems, Univ. of Tuebingen, Germany Karthik Ramani and Raymond J. Cipra • Terrain classification on fused 3D Purdue University LIDAR and camera data • A starfish-like hexapod robot • Considering spatial dependencies designed for modularity, foldability using Conditional random and reconfigurability fields • Capable of performing the self- • Building terrain and elevation maps deploying and locomotive squirming for semantic localization
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
226 Session WeC3 Red Lacquer RoomWednesday, September 17, 2014, 14:00–15:20 Localization and Mapping IV / Locomotion, Navigation, and Mobility Chair Gianluca Antonelli, Univ. of Cassino and Southern Lazio Co-Chair
14:53–14:56 WeC3.13 14:56–14:59 WeC3.14 On the Optimal Selection of Motors and Active Behavior of Musculoskeletal Robot Arms Transmissions for Driven by Pneumatic Artificial Muscles for Receiving Human’s Direct Teaching Effectively Electromechanical and Robotic Systems 1 1 1 Siavash Rezazadeh, Jonathan Hurst Shuhei Ikemoto , Yuji Kayano and Koh Hosoda 1 Oregon State University Osaka University, Japan • A general approach for • So far, we have proposed a direct electromechanical systems, with teaching method for musculoskeletal particular application to legged robots robots actuated by PAMs. • Selection based on the trade-off • In this research, we propose a method between agility and efficiency to generate active behavior of the • Considering the option of customized robot during the teaching phase. motor windings using multi-objective • The validity has been successfully optimization methods confirmed by an experiment
14:59–15:02 WeC3.15 15:02–15:05 WeC3.16 Received Signal Strength based Bearing-only GeckoGripper: A Soft Robotic Gripper Robot Navigation in a sensor network field using Gecko-Inspired Fiber Adhesives Nikhil Deshpande1, Edward Grant2, Sukho Song1, Carmel Majidi1, and Metin Sitti1,2 Mark Draelos3 and Thomas C. Henderson4 1Carnegie Mellon University 2Max-Planck 1IIT, Italy, 2NCSU, 3Duke University, 4University of Utah Institute for Intelligent Systems • Bearing estimation using RSS and • A soft, inflatable gripper based on particle filtering (PF) for map-less, controllable adhesion mechanisms ranging-less navigation in WSN of gecko-inspired fiber adhesives • Basic node-to-node navigation – with stretch of a membrane upto 15% better than without PF • Pick-and-place manipulations of • Advanced scheme uses surface fit various non-planar 3D parts using to generate intermediate way-points the adhesion control mechanisms in WSN – upto 23% better than and superior adaptability of the Outdoor Trajectory basic scheme Comparison membrane
15:05–15:08 WeC3.17 15:08–15:11 WeC3.18 Design and Architecture of a Hybrid Unmanned Aerial Underwater Series Elastic Snake Robot Vehicle: Modeling and Simulation David Rollinson, Yigit Bilgen, Ben Brown, Florian Enner, Paulo Drews-Jr1,3, Armando Neto2 and Mario Campos3 Steven Ford, Curtis Layton, Justine Rembisz, Mike Schwerin, 1Fundação Universitaria Rio Grande - Brazil Andrew Willig, Pras Velagapudi and Howie Choset 2Universidade Federal de São João Del-rei – Brazil Carnegie Mellon University 3Universidade Federal de Minas Gerais – Brazil • A novel quadrotor-like aerial-underwater platform design capable of transitioning from air to water (or vice-versa) in a simple and rapid way; • We provide a closed-loop model of the system and discuss some simulated experiments
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
227 Session WeC3 Red Lacquer RoomWednesday, September 17, 2014, 14:00–15:20 Localization and Mapping IV / Locomotion, Navigation, and Mobility Chair Gianluca Antonelli, Univ. of Cassino and Southern Lazio Co-Chair
15:11–15:14 WeC3.19 Circumnavigation by a Mobile Robot Using Bearing Measurements Ronghao Zheng and Dong Sun Department of Mechanical and Biomedical Engineering City University of Hong Kong • The problem of steering a mobile robot to achieve a circular motion around a target is considered. • The control schemes require only bearing measurements and deal with point target and disk target. • The proposed control schemes is verified by experiments on an e- puck robot.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
228 Session WeD1 Grand Ballroom Wednesday, September 17, 2014, 15:50–17:10 Micro/Nano Robotics II / Impedance, Compliance, and Force Control Chair Dong Sun, City University of Hong Kong Co-Chair
15:50–16:10 WeD1.1 16:10–16:13 WeD1.2
Keynote: Soft, printable, and small: an overview of Modeling and experiments of high speed magnetic manufacturing methods for novel robots at Harvard micromanipulation at the air/liquid interface
Robert Wood Mohamed Dkhil, Aude Bolopion, Harvard University Stéphane Régnier, Michaël Gauthier Femto-st Institute, University Pierre and Marie Curie Traditional manufacturing methods tend to be ineffective for robots with sub-millimeter scale features, robots • magnetic object air/liquid interface made entirely from soft materials, or robots requiring extremely low cost • and lead times. This talk will highlight workspace alternative manufacturing methods • electromagnet employed at Harvard for robots such as the RoboBee (right), squishy robots, and printable robots.
16:13–16:16 WeD1.3 16:16–16:19 WeD1.4 Assembly and Mechanical Characterizations Controllable Roll-to-Swim Motion of Polymer Microhelical Devices Transition of Helical Nanoswimmers
S. Alvo, D. Decanini, L. Couraud, Antoine Barbot, Dominique Decanini and A.-M. Haghiri-Gosnet and G. Hwang Gilgueng Hwang Laboratory for Photonics and Nanostructures, CNRS, France Laboratory for Photonics and Nanostructures, CNRS, France
• Polymer MicroHelical Devices • Roll-to-Swim (RTS) for improving (PMHD) for large range force sensor the propulsion robustness of • In-situ SEM nanorobotic microrobot in fluid manipulation to reveal the • RTS is a multimodal robot able to
mechanical properties of PMHD roll on the surface under flow and swim over obstacles by corkscrew • PMHD enlarges the force range up ) to 12 μN from 91 higher stiffness motion • RTS can be controlled either than conventional microhelix manually or by visual servoing
16:19–16:22 WeD1.5 16:22–16:25 WeD1.6 Three-Dimensional Rotation of Bovine Robust Nanomanipulation Control Oocyte by Using Magnetically Driven On- Based on Laser Beam Feedback chip Robot Nabil Amari1, David Folio1,Antoine Ferreira1 Lin Feng, Bilal Turan, U Ningga, and F. Arai 1Laboratoire PRISME; INSA-CVL, France Nagoya University, Japan • Nanomanipulation under the Laser Beam We present an approach for • Control strategy of two-fingered three-dimensional rotation of nanomanipulation system a single oocyte. By using a tracking a Laser Spot customer-designed micro- • Measuring and estimating robot, oocyte orientation the position of the laser beam control was achieved with using Particle Filter maximum speeds of 3 rad/s and accuracy of 7 degrees. • Experimental validation of the concept
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
229 Session WeD1 Grand Ballroom Wednesday, September 17, 2014, 15:50–17:10 Micro/Nano Robotics II / Impedance, Compliance, and Force Control Chair Dong Sun, City University of Hong Kong Co-Chair
16:25–16:28 WeD1.7 16:28–16:31 WeD1.8 Microrobotic Platform for Mechanical Stimulation Magnetic-Based Motion Control of Sperm- of Swimming Microorganism on a Chip Shaped Microrobots using Weak Oscillating Belal Ahmad1, Tomohiro Kawahara1, Magnetic Fields Takashi Yasuda1 and Fumihito Arai2 Islam S. M. Khalil*, Kareem Youakim*, 1Kyushu Institute of Technology 2Nagoya University Alonso Sánchez† and Sarthak Misra† * † • The developed platform realizes German University in Cairo University of Twente mechanical stimulation of • A sperm-shaped microrobot is swimming microorganisms in a fabricated and controlled using microfluidic chip by microrobot. oscillating fields (~5 mT) • Paramecium with 1 mm/s • Flagellated swim (at 45 Hz) in swimming speed is tracked, water and on the bottom of a magnified, stimulated, and petri-dish are achieved at observed by the platform. average speeds of 158 μm/s and 6 μm/s, respectively.
16:31–16:34 WeD1.9 16:34–16:37 WeD1.10 On-chip Flexible Scaffold for Cell Isolation System for Construction of Multishaped Tissues Rare Circulating Tumor Cell P. Chumtong1, M. Kojima1, M. Horade1, T Masuda1, S Yilling1, S W Eui1, M Niimi1 K. Ohara2, K. Kamiyama1, Y. Mae1, A Yusa2, H Nakanishi3 and F Arai1 Y. Akiyama3, M. Yamato3, and T. Arai1 1Nagoya Univ 2ASTF 3Aichi Cancer Center 1Osaka University 2Meijo University 3 • We have successfully designed Tokyo Women’s Medical University and demonstrated the size- • Flexible microscaffold made of based isolation of cells using a PDMS facilitates the fabrication microfluidic device employing of many different tissue shapes. the convective self-assembly, • Round and lattice shaped thereby achieved the separation tissues are fabricated by and collection of purified single seeding NIH3T3 on the chip tumor or rare cells. with prepared scaffolds.
16:37–16:40 WeD1.11 16:40–16:43 WeD1.12 Incorporating In-situ Force Sensing Joint Space Torque Controller Based on Capabilities in a Magnetic Microrobot Time-Delay Control with Collision Detection Wuming Jing1, David J. Cappelleri1, Sung-moon Hur1, Sang-Rok Oh & Yonghwan Oh1 1School of Mechanical Engineering, Purdue University 1Interaction and Robotics Research Center, KIST, Seoul, Korea • Micro Force Sensing Magnetic Microrobot (μFSMM) • This research addresses a control • 2D vision-based micro-force sensor method for friction-existing robot manipulators and safe motion with • Magnetic microrobot body its environment • In-situ force sensing capability with mobility • Time-Delay Control(TDC) with • Stiffness calibrated with micro force stiction feed-forward friction sensing probe compensator is implemented to • Characterized relationship between overcome friction force and magnetic field/input current • Collision detection method using dynamic model and the residual generator
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
230 Session WeD1 Grand Ballroom Wednesday, September 17, 2014, 15:50–17:10 Micro/Nano Robotics II / Impedance, Compliance, and Force Control Chair Dong Sun, City University of Hong Kong Co-Chair
16:43–16:46 WeD1.13 16:46–16:49 WeD1.14 Force/vision control for robotic cutting Hierarchical Inequality Task of soft materials Specification for Indirect Force Philip Long, Wisama Khalil and Philippe Martinet Controlled Robots using Quadratic École Centrale de Nantes, IRCCyN UMR CNRS Programming 6597, France Ewald Lutscher and Gordon Cheng, • Cooperative robot control to cut Technische Universität München deformable object • Force control ensures cut without • Virtual set point selection according damage to surrounding area to force/positioning equality and • Vision update ensures robot can inequality tasks on Cartesian and react to object deformations joint level • Second robot applies a pulling • Inherent compliance of the force to facilitate separation underlying indirect force controller is preserved
16:49–16:52 WeD1.15 16:52–16:55 WeD1.16 Fast Dual-Arm Manipulation Using External Torque Sensing Algorithm for Variable Admittance Control Flexible-Joint Robot based on Magnus Bjerkeng1, Johannes Schrimpf2, Disturbance Observer Structure Torstein Myhre3 and Kristin Y. Pettersen2 Young Jin Park1 and Wan Kyun Chung1 1SINTEF ICT 2NTNU ITK 3NTNU IPK 1POSTECH • Human interaction • Torque sensing algorithm of FJR is and dual-arm proposed cooperative handling. • based on the DOB structure • Force control and • to estimate both actuating motor trajectory tracking. torque and external link torque • 14 DOF experiments simultaneously using two redundant • Actuating motor toque is then utilized robots. to motor disturbance compensation
16:55–16:58 WeD1.17 16:58–17:01 WeD1.18 Implicit Force Control for an Industrial Robot Cartesian Space Synchronous with Flexible Joints and Flexible Links Impedance Control of Two 7-DOF Robot Roberto Rossi, Luca Bascetta, Arm Manipulators Paolo Rocco Minghe Jin, Zijian Zhang, Fenglei Ni, Hong Liu Politecnico di Milano, Italy Harbin Institute of Technology(HIT) • Compliance model • Synchronous Errors Of The Cartesian
Space including joints, links and GX11 GX cj j cj i ci contact elasticity GX111 X GX 1 cjj j cj i ci • Force Control algorithm GXG 111 XGXX GX1 based on compliance model cjj j cj i ci • Cartesian Space Synchronous • Limit cycles due to friction Impedance Controller suppressed by variable JtMXutCXXutGXFXFKrtKrtT ( ) () ˆˆ ut()tC Cˆˆˆ , ut()tGX GGXˆ X Fˆˆ())() ˆ ()( ()( control gain i XiiiiXi Xiiiii iX XiiXiiXiiiX i i extpi di
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
231 Session WeD1 Grand Ballroom Wednesday, September 17, 2014, 15:50–17:10 Micro/Nano Robotics II / Impedance, Compliance, and Force Control Chair Dong Sun, City University of Hong Kong Co-Chair
17:01–17:04 WeD1.19 17:04–17:07 WeD1.20 Fully Omnidirectional Compliance in Mobile Augmenting impedance control with Robots Via Drive-Torque Sensor Feedback structural compliance for improved Kwan Suk Kim1, Alan S. Kwok1, contact transition performance Gray C. Thomas1 and Luis Sentis1 Dongwon Kim, R. Brent Gillespie, 1The University of Texas at Austin Brandon J. Johnson, and Xingjian Lai University of Michigan • Holonomic mobile base • A spring-damper coupler reduces the • External force sensed by torque sensor on drivetrain impedance to the environment while → Omnidirectional Compliance improving performance in contact transition tasks. • We present a simple method for estimating interaction forces and regulating the contact force with only one position sensor and without a priori knowledge of the environment. 17:07–17:10 WeD1.21 Fuzzy Learning Variable Admittance Control for Human-Robot Cooperation Fotios Dimeas, Nikos Aspragathos University of Patras, Greece • A fuzzy model reference learning system modifies online the gains of the admittance controller • Adaptation to the minimum jerk trajectory model Combination of expert know- ledge and adaptation facilitates human-robot cooperation Less human effort, less time required and more accurate positioning on p2p movements
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
232 Session WeD2 State Ballroom Wednesday, September 17, 2014, 15:50–17:10 Unmanned Aerial Systems II / Legged Robots II Chair Raffaella Carloni, University of Twente Co-Chair
15:50–16:10 WeD2.1 16:10–16:13 WeD2.2 Keynote: Material-Handling – Paradigms Robust Attitude Controller for Uncertain for Humanoids and UAVs Hexarotor Micro Aerial Vehicles (MAVs) Dafizal Derawi1, Nurul Dayana Salim1,
Paul Oh Hairi Zamzuri1, Hao Liu 2, Mohd Azizi Abdul University of Nevada, Las Vegas (UNLV) Rahman 1, and Saiful Amri Mazlan1 Perhaps subtle is the observation that robotics is in a 1Universiti Teknologi Malaysia 2Beihang Uni. “step change”; the recent DARPA Robotics Challenge • Robust, decoupled, linear time-invariant control (DRC) and various large-scale projects (e.g. FP7 • Nominal controller: PI+PID & Robust compensator European Commission) reveal that today’s robots can compound the IT revolution with mobile material- • Uncertainties (equivalent disturbances): parametric handling capabilities. The supply-chain bottleneck uncertainties, coupling, nonlinear dynamics, and ext. occurs at the “tails” where support infrastructures differ disturbances from location-to-location. This talk posits how today’s humanoids and UAVs have the potential to overcome bottlenecks by accelerating material-handling
16:13–16:16 WeD2.3 16:16–16:19 WeD2.4 Emergency Landing for a Quadrotor in Case of Guaranteed Road Network Search a Propeller Failure: A Backstepping Approach with Small Unmanned Aircraft Vincenzo Lippiello, Fabio Ruggiero, Diana Serra, Michael Dille1,2, Ben Grocholsky2, Department of Electrical Engineering and Information and Sanjiv Singh2 Technology, Università di Napoli Federico II, Italy 1SGT / NASA Ames 2Carnegie Mellon University • A backstepping approach is proposed to • Guaranteed capture of road- Primitive motions: cope with the failure of a quadrotor bound evaders • Guard intersection propeller. • Mapping abstract pursuit- • A birotor configuration with fixed evasion to UAV motions
propellers is considered. • Unbounded-speed evaders • Theory shows that the birotor can reach • Larger, slower UAV teams • Sweep road segment any point in the Cartesian space. • Bounded-speed evaders • Simulation tests are presented. • Smaller, faster UAV teams
16:19–16:22 WeD2.5 16:22–16:25 WeD2.6 A Ground-Based Optical System for On Crop Height Estimation with UAVs Autonomous Landing of a Fixed Wing UAV 1 1 Weiwei Kong1, Dianle Zhou1,Yu Zhang1, Daibing Zhang1, Xun Wang1, David Anthony , Sebastian Elbuam , Boxin Zhao1, Chengping Yan1, Lincheng Shen1, Jianwei Zhang2 Aaron Lorenz,1 and Carrick Detweiler1 1 2 National University of Defense Technology University of Hamburg 1University of Nebraska-Lincoln • A novel ground-based platform with • Develops a low flying UAV system to a large field of view (FOV), estimate crop heights with a 2D eliminating the dependency of laser scanner GNSS. • Algorithm computes crop height to • AdaBoost algorithm has been within 5cm of ground truth applied to track the target. • Cluttered laser scans are filtered to • Several real flights in outdoor control vehicle altitude environments support the accuracy of the system.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
233 Session WeD2 State Ballroom Wednesday, September 17, 2014, 15:50–17:10 Unmanned Aerial Systems II / Legged Robots II Chair Raffaella Carloni, University of Twente Co-Chair
16:25–16:28 WeD2.7 16:28–16:31 WeD2.8 Model-aided State Estimation for Inspection of Pole-Like Structure using Vision Quadrotor MAVs with Wind Disturbances controlled VTOL UAV and Shared Autonomy Inkyu Sa1, Stefan Hrabar2 and Peter Corke1 D. Abeywardena1, Z. Wang2, G. Dissanayake1 1QUT, CSIRO Brisbane, Australia S. Waslander3 and S. Kodagoda1 • Image based visual servoing 1U. Of Tech. Sydney 2KTH 3U. Of Waterloo using line features (Camera+IMU for de-rotation) • Effect of wind on Quadrotor dynamic is modeled and employed for state • The use of shared autonomy estimation for easy&safe inspection of pole-like structures • Sensing package - monocular camera and IMU • Indoor and outdoor • Observability analysis proves that both quadrotor pose (day&night) experiments with and wind can be estimated simultaneously reliable ground truth (VICON and Leica) for validation. • Experiments in Vicon room with industrial grade FAN using an ARDrone quadrotor • No GPS is used. 16:31–16:34 WeD2.9 16:34–16:37 WeD2.10 Image-based control for dynamically The Quadroller: Modeling of cross-coupled aerial manipulation a UAV/UGV Hybrid Quadrotor R. Mebarki, V. Lippiello, and B. Siciliano Jared R. Page and Paul E. I. Pounds PRISMA Lab University of Queensland University of Napoli Federico II • Quadrotor endowed with a robotic arm and a fixed camera. • Driving mode uses passive • Visual servoing controller for the wheels to double range positioning of assembling parts. • Skateboard steering uses • Integral Backstepping low-level existing flight control mixing controller for velocity regulation. • Aircraft tilts sideways to turn • Simulation results. Sketch of the robotic system
16:37–16:40 WeD2.11 16:40–16:43 WeD2.12 Persistent monitoring with a team of Compliant Terrain Legged Locomotion autonomous gliders using static soaring Using a Viscoplastic Approach J.J. Acevedo1, N.R.J. Lawrance2, Vasileios Vasilopoulos, Iosif S. Paraskevas and B.C. Arrue1, S. Sukkarieh2 and A. Ollero1 Evangelos G. Papadopoulos 1University of Sevilla 2University of Sydney National Technical University of Athens
• Cooperative patrolling missions to • Legged robot compliant foot-terrain (, )
minimize the refresh time. interaction
• Distributed algorithm based on • Proposed new viscoplastic impact coordination variables. model for interaction ( , ) • Exploiting thermal sources to gain • Results show that compliance affects energy and keep the mission. Forces and gait response ! • One-to-one coordination for euler angles • Developed a novel controller to
dynamic thermal allocation. for the model compensate for terrain compliance
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
234 Session WeD2 State Ballroom Wednesday, September 17, 2014, 15:50–17:10 Unmanned Aerial Systems II / Legged Robots II Chair Raffaella Carloni, University of Twente Co-Chair
16:43–16:46 WeD2.13 16:46–16:49 WeD2.14 Passive Dynamic Walking of More Solutions Means More Problems: Compass-like Biped Robot with Resolving Kinematic Redundancy in Dynamic Absorbers Robot Locomotion on Complex Terrain Yukihiro Akutsu1, Fumihiko Asano1, Isao Tokuda2 Brian Satzinger1, Jason I. Reid2, Max 1JAIST 2Ritsumeikan Univ. Bajracharya2, Paul Hebert2 and Katie Byl1 1UCSB 2JPL • Passive compass gait with dynamic absorbers (DAs) is investigated • RoboSimian has 7-DOF limbs. • Speeding-up is achieved by the effect • For quadruped walking, 3 DOFs are of DAs with suitable parameters often sufficient (to pick footholds). • Numerical simulations show some • To resolve redundancy efficiently interesting nonlinear phenomena and tractably, we combine an RRT search (for dominant and swing • Dominant dynamics of DAs is legs) with well-designed IK tables modeled and its effect is analyzed (for dependent limbs).
16:49–16:52 WeD2.15 16:52–16:55 WeD2.16 Hopping control for the musculoskeletal A Passive Dynamic Quadruped that bipedal robot: BioBiped Moves in a Large Variety of Gaits Maziar A. Sharbafi1, Katayon Radkhah2, Zhenyu Gan, C. David Remy, Oskar von Stryk2 and Andre Seyfarth1 University of Michigan, Robotics and Motion 1Lauflabor, 2Sim Group, TU Darmstadt Laboratory • Method: two-layer controller • A rigid main body and four • Virtual model control for bouncing massless springs, passive • Velocity based leg adjustment (VBLA) model, no energy losses, for swinging the leg energetically conservative • Achievements: • With a single passive dynamic quadrupedal • Hopping patterns similar to humans model, we can produce 6 • From in-place to forward hopping by kinds of different gaits. tuning few control parameters BioBiped Robot
16:55–16:58 WeD2.17 16:58–17:01 WeD2.18 Reactive Posture Behaviors for Stable Velocity Disturbance Rejection for Planar Bipeds Walking with HZD-Based Control Legged Locomotion over Steep Inclines David Post & James Schmiedeler A. Roennau1, G. Heppner1,
Aerospace & Mechanical Engineering, University of Notre Dame, USA M. Nowicki2, J. M. Zoellner1 and R. Dillmann1 1 2 Approach FZI, Karlsruhe, Germany PUT, Poznan, Poland • Modify desired joint trajectories within a step in response to velocity disturbances. • Behavior-based control system for a • Make modifications via heuristics extracted from hexapod robot with 4 joints per leg simulations of disturbed walking under orbital stabilization control. • Hybrid system architecture with deliberate and reactive components Experimental Results • Real-time implementation on 5-link biped ERNIE. • Three independent posture • Reduced step-to-step velocity variations in behaviors react on disturbances and undisturbed walking. keep the robot stable in all terrains • More rapid return to desired velocity post-disturbance. • Ability to reject larger disturbances without gait failure. • Autonomous adaptation to inclines
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
235 Session WeD2 State Ballroom Wednesday, September 17, 2014, 15:50–17:10 Unmanned Aerial Systems II / Legged Robots II Chair Raffaella Carloni, University of Twente Co-Chair
17:01–17:04 WeD2.19 17:04–17:07 WeD2.20 The Effect of Leg Impedance on Stability On the Energetics of Quadrupedal Bounding and Efficiency in Quadrupedal Trotting With and Without Torso Compliance Will Bosworth1, Sangbae Kim1, Neville Hogan1,2 Qu Cao and Ioannis Poulakakis 1Dept of Mechanical Engineering, MIT, USA University of Delaware, USA 2Dept of Brain & Cog Sci, MIT, USA • A simulation of the MIT Cheetah • Two reduced-order models are robot performing a trot gait with proposed to study the energetics tuned leg impedance control. of quadrupedal bounding
• Shows how stability is more • Cyclic motions with minimum Flexible-torso sensitive to knee impedance cost of transport are generated than hip; that efficiency is not sensitive to impedance. • Torso compliance enhances gait efficiency at high speeds • Simulation data compares favorably with experimental Rigid-torso data of the MIT Cheetah trotting.
17:07–17:10 WeD2.21 Self-stabilizing quadruped trot-running and period-doubling bifurcations Jongwoo Lee1, Dong Jin Hyun1, Jooeun Ahn1, Sangbae Kim1, and Neville Hogan1 1Mechanical Engineering, MIT, USA • The dynamics of a quadruped robot model with impedance control is analyzed using simulation. • The simulation study shows self-stabilizing trot-running at various speeds. • At high speeds, period- doubling bifurcation is observed , which might limit the performance.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
236 Session WeD3 Red Lacquer RoomWednesday, September 17, 2014, 15:50–17:10 Computer Vision II / Recognition Chair Philippe Martinet, Ecole Centrale de Nantes Co-Chair
15:50–16:10 WeD3.1 16:10–16:13 WeD3.2 Keynote: Semantic Parsing in Indoors A Model-free Approach for the and Outdoors Environments Segmentation of Unknown Objects Jana Kosecka U. Asif, M. Bennamoun,and F. Sohel George Mason University The University of Western Australia • Initial segmentation: • Simultaneous segmentation and • Gradient-based seeding. categorization of open scenes • Regions grow based on sensory data into background structural variations (i.e., and object categories 3D proximity, planarity, • Efficient processing of video and and surface normal orientation). multiple sensor modalities • Perceptual grouping: • Semantic refinement for finer • Shape between regions. object discrimination • Homogeneity of inter- region connectivity.
16:13–16:16 WeD3.3 16:16–16:19 WeD3.4 Automatic detection of pole-like Real-time and Low Latency Embedded structures in 3D urban environments Computer Vision Hardware Based on a Federico Tombari1, Nicola Fioraio1,Tommaso Cavallari1 Combination of FPGA and Mobile CPU Samuele Salti1, Alioscia Petrelli1,Luigi Di Stefano1 Dominik Honegger1, Helen Oleynikova1, 1University of Bologna and Marc Pollefeys1 1ETH Zürich • Detection of pole-like • Stereo camera setup with an FPGA structures (lamp posts, as an additional layer between traffic signs, light poles,..) camera and CPU in 3D urban data acquired with a LiDAR • System calculates dense disparity images with 752*480 resolution at •Local-global description and classification approach to 60 fps reject false positives: first point-wise, then cluster-wise • 5 Watt power consumption, 50 •Use of context to discriminate wrt. tree trunks grams total weight
16:19–16:22 WeD3.5 16:22–16:25 WeD3.6 Multi-View Terrain Classification using Efficient Real-Time Loop Closure Panoramic Imagery and LIDAR Detection Using GMM and Tree Structure Sarah Taghavi Namin1,2, Mohammad Najafi1,2 Mohammed Boulekchour and Nabil Aouf and Lars Petersson1 Cranfield University, Shrivenham, UK 1NICTA 2The Australian National University • Several views along the road • Two new methods for visual loop-p image closure detection are proposed. Several 2D feature vectors for each 3D point any text in the • The first technique uses Bayes • Choosing the best 2D view with image should Decision Theory for loop closure Consensus 2D View Selection be the same detection based on Gaussian • 3D Enhanced CRF: size as main Mixture Model (GMM). -Robust against over-smoothing text • A new technique based on a combination of GMM with the KD-- -Learning from previous mistakes Tree data structure. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
237 Session WeD3 Red Lacquer RoomWednesday, September 17, 2014, 15:50–17:10 Computer Vision II / Recognition Chair Philippe Martinet, Ecole Centrale de Nantes Co-Chair
16:25–16:28 WeD3.7 16:28–16:31 WeD3.8 Place Categorization using Sparse and Real-Time Global Localization of Intelligent Road Vehicles in Lane-Level via Lane Marking Detection Redundant Representations and Shape Registration H. Carrillo, Y. Latif, J. Neira and J. A. Castellanos Dixiao Cui, Jianru Xue, University of Zaragoza Shaoyi Du and Nanning Zheng IAIR, Xi’an Jiaotong University • Novel formulation of the place categorization • Real-time centimeter-level global problem by posing it as an L1-minimization localization of intelligent vehicles in problem. urban environments
• Innovative Shape Registration • Faster training phase and performance based Cross Validation scheme comparable to state-of-the-art methods. • Cross-validating detected lane • Online robot operation with on-the-fly and markings and a GPS based road active learning phase. shape prior
16:31–16:34 WeD3.9 16:34–16:37 WeD3.10 On-road Vehicle Detection through Part Model Real-time Depth Enhanced Monocular Learning and Probabilistic Inference Odometry (Open Source) C. Wang1, H. Zhao1, C. Guo2, S. Mita2, H. Zha3 Ji Zhang, Michael Kaess and Sanjiv Singh 1 Key Lab of Machine Perception, Peking Univ., Robotices Institute at Carnegie Mellon University 2Toyota Central R&D Labs, 3Toyota Technological Institute • RGB-D visual odometry that is able to • On-road vehicle detection, focus on utilize sparsely provided depth vehicle pose inference on part instan- • Register a depthmap using depth from RGB-D cameras or lidars, and involve ces by addressing the issues of partial three types of features in solving for observation and varying viewpoints. motion: depth from depthmap, depth by • Vehicle appearance and geometric SFM, and depth unavailable models are learnt from image samples. • Tested with 3 sensor setups, rated #2 • Road-structure based viewpoint maps on KITTI benchmark using depth from are generated by statistic of vehicles. Velodyne (compared to stereo VO)
16:37–16:40 WeD3.11 16:40–16:43 WeD3.12 MEVO: Multi-Environment Place Recognition and Self-Localization in Interior Stereo Visual Odometry Hallways by Indoor Mobile Robots: A Signature- Based Cascaded Filtering Framework Thomas Koletschka, Luis Puig, Khalil Ahmad Yousef , Johnny Park and Avinash Kak and Kostas Daniilidis Electrical and Computer Engineering, Purdue University, USA University of Pennsylvaniania • We propose a cascaded filter approach to 3D-JUDOCA • Robust stereo visual odometry for robot self-localization. The filter cascade Features consists of a prefilter followed by an arbitrary H H both indoor and outdoor environments number of filters. 2 3 • Increased accuracy over using just • All filters are based on signatures learned using a model of the environment based on H H one feature type 3D junction features (3D-JUDOCA). 4 Where am I? 5 H • Efficient line stereo and frame-to- • We describe a novel method for designing, H: Histogram 1 Radial Signature RS: H selecting, and matching the signatures for 1 Vertical Signature VS: |H –H | frame matching with sub-pixel 2 3 both the prefiltering stage and subsequent Horizontal Signature HS: |H4 –H5| accuracy and occlusion handling filtering stages. Self Localization by a • Our experimental validation is based on a Mobile Robot large network of hallways.
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
238 Session WeD3 Red Lacquer RoomWednesday, September 17, 2014, 15:50–17:10 Computer Vision II / Recognition Chair Philippe Martinet, Ecole Centrale de Nantes Co-Chair
16:43–16:46 WeD3.13 16:46–16:49 WeD3.14 Automated Perception of Safe Docking Terrain Classification Using Locations with Alignment Information Laser Range Finder Siddarth Jain1 and Brenna Argall12 Krzysztof Walas1, Michal Nowicki1, 1Northwestern University, USA 1Poznan University of Technology, 2Rehabilitation Institute of Chicago, USA 60-965 Poznan, Poland • Intensity and depth values • Feature vector – statistical values and 2D Fast Fourier Transform • Novel method: Perception of safe and oriented docking locations from depth data • 98% correctly recognized terrain samples for 12 terrain types • Formulation: Geometric features, no fiducial/landmark requirements, for rectangular & circular structures • Low computational cost – classification of 4 m2 in 88 ms • Evaluation: A variety of docking structures and configurations from varied viewpoints
16:49–16:52 WeD3.15 16:52–16:55 WeD3.16
A Novel Feature for Polyp Detection in Automation of "Ground Truth" Annotation for Multi- Wireless Capsule Endoscopy images View RGB-D Object Instance Recognition Datasets Aitor Aldoma1, Thomas Fäulhammer1, Yixuan Yuan and Max Q.-H. Meng Markus Vincze1, Department of Electronic Engineering, 1Vienna University of Technology The Chinese University of Hong Kong, China
• Propose a new feature integrating • Automatic annotation without the Gabor filter and Monogenic- constraints on scene layouts through Local Binary Pattern (M-LBP) exploitation of multiple viewpoints: methods in color components. •Single-view recognition in all frames. • Achieve average polyp detection •Scene reconstruction through visual Fig. (a) Illustration of polyps (b) features and common objects. accuracy, sensitivity and Components diagram of a WCE. specificity at 91.43%, 88.09%, •3D Hypothesis Verification. and 94.78%. •“Ground-truth” projection.
16:55–16:58 WeD3.17 16:58–17:01 WeD3.18 Recognition of Inside Pipeline Geometry by Large Scale Place Recognition using Using PSD Sensors for Autonomous Navigation Geometrical Landmark Relations Y. S. Choi1, H. M. Kim1, J. S. Suh1, H. M. Mun1, Marian Himstedt1, Jan Frost1, Sven Hellbach2, S. U. Yang1, C. M. Park1 and H. R. Choi1 Hans-Joachim Böhme2 and Erik Maehle1 1Sungkyunkwan University, Korea 1University of Lübeck 2HTW Dresden • Recognition method by • Detect landmarks in 2D range scans using PSD sensors • Estimate relative orientations and • Recognition of pipeline distances of landmarks geometry • Generate scan signatures (GLARE) • Distinction of T-branch with landmark relations and miter • GLAREs are viewpoint invariant and • Detection of pipeline highly discriminative element type
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
239 Session WeD3 Red Lacquer RoomWednesday, September 17, 2014, 15:50–17:10 Computer Vision II / Recognition Chair Philippe Martinet, Ecole Centrale de Nantes Co-Chair
17:01–17:04 WeD3.19 17:04–17:07 WeD3.20 Evaluation of Feature Selection and Automatic Segmentation and Recognition of Model Training Strategies for Object Human Activities from Observation based on Category Recognition Semantic Reasoning Haider Ali and Zoltan-Csaba Marton K. Ramirez-Amaro1, M. Beetz2 and G. Cheng1 German Aerospace Center (DLR) 1Institute for Cognitive Systems, Technical University of Munich, Germany. 2Institute for Artificial Intelligence, University of Bremen, Germany. • Quantifying the generalizing power of object category recognition between In this paper, we propose a datasets. framework that combines different signals via semantic • Evaluating the VFH, ESF and PFH features reasoning to enable robots for and their (full and partial) combinations. on-line segmentation and • Analyzing the results given by features recognition of human activities selection methods (mRMR and MaxRel). by understanding what it sees • Improving the categorization accuracy from videos with 85% accuracy. obtained through adapting the training set. 17:07–17:10 WeD3.21 Detection of Liquids in Cups Based on the Refraction of Light with a Depth Camera Using Triangulation Yoshitaka Hara*1, Fuhito Honda*1, Takashi Tsubouchi*1, and Akihisa Ohya*1
*1 University of Tsukuba, Japan • For opaque liquids, the liquid Opaque Liquid surface is measured • In the case of transparent liquids, the raised bottom is measured
• We formulated it theoretically Transparent Liquid based on the refraction of light • Our method can detect liquids of various transparency in cups
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
240
Author Index
241
242 IROS 2014 Author Index ...... TuA2.20 Amemiya, Motoyuki ...... TuB1.13 A Amirat, Yacine ...... SuFD10. Abayazid, Momen ...... MoD1.2 1 Abbeel, Pieter ...... WeC2.3 Amirpour Amraii, Saman ...... MoC3.8 Abdi, Hamid ...... TuA1.15 Andersh, Jonathan ...... WeC1.17 Abdul Rahman, Mohd Azizi ...... WeD2.2 Anderson, Will ...... TuB3.2 Abdur-Rahim, Jamilah ...... TuE2.4 Ando, Masatoshi ...... MoA2.2 Abe, Kasumi ...... TuB2.14 Ando, Takeshi ...... TuB1.13 ...... TuE2.5 Andreff, Nicolas ...... MoB3.13 Abeywardena, Dinuka ...... WeD2.7 Ang Jr, Marcelo H ...... WeB3.19 Accoto, Dino ...... TuD1.7 Anne Dual, Seraina ...... TuB1.21 Acevedo, José Joaquín ...... WeD2.11 Anooshahpour, Farshad ...... MoD1.18 Achtelik, Markus W...... SuPM2.1 Ansaloni, Matteo ...... WeC2.12 Acosta, Jose Angel ...... TuE3.8 Anthony, David ...... WeD2.6 Adebar, Troy K...... WeC1.7 Antonelli, Gianluca ...... WeC3 C Adelson, Edward ...... WeB1.19 Aono, Hiroyuki ...... TuD1.11 Adorno, Bruno Vilhena ...... TuA1.17 Aouf, Nabil ...... WeD3.6 Aertbelien, Erwin ...... MoD3.12 Aoyama, Tadayoshi ...... MoC1.6 Agapito, Lourdes ...... MoC2.16 Apker, Thomas ...... WeA3.15 Agha-mohammadi, Ali-akbar ...... TuE3.4 Arai, Fumihito ...... MoC1.1 Agmon, Noa ...... TuD2.20 ...... MoC1.5 Agogino, Adrian ...... TuB2.20 ...... WeD1.5 Agrawal, Sunil ...... WeA1.18 ...... WeD1.7 Aguilera, Sergio ...... TuA1.9 ...... WeD1.10 Ahmad, Belal ...... WeD1.7 ...... ThFD3.1 Ahmad Sharbafi, Maziar ...... TuC2.7 Arai, Tatsuo ...... MoC1.9 ...... WeD2.15 ...... WeD1.9 Ahmad Yousef, Khalil ...... WeD3.12 Aranda, Miguel ...... MoA3.15 Ahn, Jooeun ...... WeD2.21 Araujo, Helder ...... WeB3.16 Ahn, Sang Chul ...... TuC3.17 Ardiyanto, Igi ...... TuD3.12 Ajoudani, Arash ...... WeB1.18 Arevalo, Vicente ...... MoB1.6 Akbari Hamed, Kaveh ...... TuC2.5 Argall, Brenna ...... WeD3.13 Akiyama, Ken ...... TuA3.13 ...... ThFD2.1 Akiyama, Yoshikatsu ...... WeD1.9 Ariizumi, Ryo ...... TuB2.19 Akst, Lee ...... MoD1.13 Arisumi, Hitoshi ...... TuB3.18 Akutsu, Yukihiro ...... WeD2.13 Arkin, Ronald ...... MoD3.6 Al Mehairi, Hind ...... TuE3.2 Armand, Mehran ...... WeA1.8 Al-Hosani, Hanan ...... TuE3.2 Arras, Kai Oliver ...... MoA2.12 Alamdari, Aliakbar ...... TuD1.14 ...... MoD2.3 Alami, Rachid ...... SuFD10. Arrichiello, Filippo ...... WeA2.21 1 Arroyo, Roberto ...... MoC2.16 ...... MoA2.14 ...... TuD3.9 Alatartsev, Sergey ...... WeC2.18 Arrue, Begoña C...... WeD2.11 Alberti, Marina ...... TuD2.3 Artemiadis, Panagiotis ...... TuB1.17 Albu-Schäffer, Alin ...... TuD1.1 Artigas, Jordi ...... ThFD8.1 ...... WeB2.4 Asada, Harry ...... TuB3.4 Aldea, Emanuel ...... MoC2.13 Asano, Fumihiko ...... WeD2.13 Aldoma, Aitor ...... WeD3.16 Asfour, Tamim ...... TuC1.15 Aleotti, Jacopo ...... WeA2.12 Asif, Umar ...... WeD3.2 Alexenko, Tatiana ...... MoD2.6 Asmar, Daniel ...... MoB3.20 Ali, Haider ...... WeD3.19 Aspragathos, Nikos A...... WeD1.21 Aliprantis, Ioannis ...... MoC3.11 Assa, Akbar ...... MoB3.14 Allan, Jean-Francois ...... MoB1.12 ...... TuC3.12 Allen, Peter ...... MoC2.19 Atashzar, Seyed Farokh ...... WeA1.15 ...... MoD1.14 ...... WeA1.16 ...... TuB2.11 Atkeson, Christopher ...... MoC2.11 Allen, Ross ...... TuB2.15 Atsuta, Hiroshi ...... MoC2.7 Alsayed, Zayed ...... TuC3.10 Attamimi, Muhammad ...... TuB2.14 Alterovitz, Ron ...... TuA2.6 ...... TuE2.5 ...... TuA2.9 Auat Cheein, Fernando ...... TuA1.9 Althoefer, Kaspar ...... TuC1.16 Audren, Hervé ...... WeB2.5 ...... TuE1.2 Avci, Ebubekir ...... TuA1.18 Althoff, Matthias ...... MoD3.3 Ayanian, Nora ...... ThFD11. Alunni, Nicholas ...... WeA3.6 1 Alves Neto, Armando ...... WeC3.18 Azad, Morteza ...... TuE1.11 Alvo, Sébastien ...... WeD1.3 Azimian, Hamidreza ...... MoB1.16 Alwala, Kalyan Vasudev ...... MoC3.6 ...... TuB1.9 Amari, Nabil ...... WeD1.6 Azuma, Takashi ...... TuB1.6 Amato, Nancy ...... TuA2.1 B ...... TuD2.19 Bab-hadiashar, Alireza ...... TuC3.4 ...... WeA2.17 Babin, Vincent ...... MoB1.12 Ambrus, Rares ...... TuA2.17 Babu, Ajish ...... MoA2.7
243 Backus, Spencer ...... MoA1.7 Bharatheesha, Mukunda ...... MoA2.19 Badino, Hernan ...... TuE3.13 Bhattacharya, Sourabh ...... MoA1.12 Bae, Jung Hwa ...... WeB1.17 Bhattacharya, Subhrajit ...... MoA1.14 Baek, Young Min ...... WeA1.10 Bhattacharyya, Sampriti ...... TuB3.4 Baglini, Emanuele ...... TuA1.11 Bhurchandi, Kishor ...... MoA3.8 Bajones, Markus ...... TuC2.13 Bicchi, Antonio ...... MoD1.10 Bajracharya, Max ...... TuB3.15 ...... MoD1.11 ...... WeD2.14 ...... WeB1.1 Balakrishnan, Subramaniam ...... MoD1.5 ...... WeB1.5 Balasubramanian, Ravi ...... TuE2.14 ...... WeB1.18 Bandyopadhyay, Saptarshi ...... WeA3.18 Bidaud, Philippe ...... WeB2.3 Banthia, Vikram ...... MoD1.5 Bilgen, Yigit ...... WeC3.17 Baradat, Cédric ...... MoB1.15 Billard, Aude ...... TuE2.12 ...... TuA1.19 ...... ThFD9.1 Barattini, Paolo ...... SuFD3.1 Bingham, Jeffrey ...... WeA2.3 Barbot, Antoine ...... WeD1.4 Birbach, Oliver ...... MoB1.5 Barfoot, Timothy ...... TuD2.16 Birchfield, Stan ...... WeC2.7 Barkan, Andrew ...... TuB1.17 Birem, Merwan ...... WeC3.4 Barrett, Samuel ...... MoA3.19 Birglen, Lionel ...... WeB1.3 Barry, Jennifer ...... MoA2.21 Birk, Andreas ...... TuD3.4 Barszap, Alexander ...... TuB2.11 ...... WeC3.7 Bartlett, Nicholas ...... MoB2.7 Bjerkeng, Magnus ...... WeC2.14 Bartneck, Christoph ...... MoD2.2 ...... WeD1.15 Basar, Tamer ...... MoA1.12 Bloesch, Michael ...... MoC2.6 Bascetta, Luca ...... WeD1.17 ...... TuD3.11 Basso, Brandon ...... SuPM2.1 Boehme, Hans-Joachim ...... WeD3.18 Batista, Jorge ...... WeB2.17 Boeuf, Alexandre ...... MoA2.14 Bauer, Jörg ...... WeB3.5 Bohg, Jeannette ...... MoA1.9 Baumgartner, Matthias ...... TuB2.18 Bohren, Jonathan ...... MoD2.11 Bäuml, Berthold ...... MoB1.5 Böhringer, Karl F...... TuD1.11 ...... TuC3.9 Bok, Yunsu ...... MoB1.7 Bazaz Behbahani, Sanaz ...... TuD1.10 Bolopion, Aude ...... WeD1.2 Beardsley, Paul ...... MoB1.10 Bonfe, Marcello ...... TuD2.11 Bechlioulis, Charalampos ...... MoA1.8 Bonsignorio, Fabio Paolo ...... SuFD3.1 ...... MoC1.12 Boone, Amanda ...... MoC1.20 ...... TuA3.20 Bore, Nils ...... TuA2.20 ...... TuC3.13 Borgerink, Dian J...... TuE3.15 Becker, Aaron ...... MoC1.20 Borges, Geovany Araujo ...... TuA1.17 ...... TuB1.7 Borghesan, Gianni ...... TuD2.11 Beckner, Clayton ...... MoD2.2 ...... ThFD4.1 Beetz, Michael ...... WeC1.20 Bornschlegl, Eric ...... TuB3.13 ...... WeD3.20 Borum, Andy ...... MoA1.10 Begum, Momotaz ...... SuFD9.1 Bostelman, Roger ...... SuFD3.1 Bekhti, Rachid ...... WeB1.12 Bosworth, William ...... WeD2.19 Bekiroglu, Yasemin ...... TuE2.12 Boulekchour, Mohammed ...... WeD3.6 ...... WeB1.15 Boutselis, George ...... MoC1.12 Beksi, William ...... WeA3.3 Boutteau, Rémi ...... WeB3.13 Belharet, Karim ...... MoC1.8 ...... WeB3.17 Bellocchio, Enrico ...... TuE2.9 Bowen, Chris ...... TuA2.6 Belter, Dominik ...... WeC2.6 Boyer, Frédéric ...... TuE3.6 Belter, Joseph ...... TuD1.18 Brackx, Branko ...... TuD1.6 Ben Amor, Heni ...... MoD2.17 Bradai, Benazouz ...... TuC3.10 Benavides, Daniel ...... WeA3.17 Braga, Juan ...... TuE3.8 Bennamoun, Mohammed ...... WeD3.2 Brand, Christoph ...... TuA2.19 Bennehar, Moussab ...... TuA1.12 Brandao, Martim ...... TuA2.15 ...... TuC1.3 Brandstetter, Jürgen ...... MoD2.2 Bennewitz, Maren ...... ThFD5.1 Brendel, Thomas ...... TuB1.18 Berenson, Dmitry ...... WeA3.6 Brennan, Sean ...... TuE1.6 Bergasa, Luis Miguel ...... MoC2.16 Bretl, Timothy ...... MoA1.10 ...... TuD3.9 Briggs, Gordon ...... TuD2.10 Bergbreiter, Sarah ...... MoC1.4 Brock, Oliver ...... MoB2.15 Berger, Erik ...... MoD2.17 ...... MoC1 C Bergmans, Jan W. M...... WeA3.14 ...... TuA1.1 Berkvens, Rafael ...... TuA2.13 ...... TuC1.19 Berman, Spring ...... SuFD7.1 ...... TuD2.2 Berry, Francois ...... WeC3.4 ...... WeB3.12 Bertaska, Ivan R...... TuB3.11 Brockmeyer, Eric ...... TuD1.5 Berthoz, Alain ...... MoD2.8 Broekens, Joost ...... TuC2.17 Bertram, John ...... TuC2.3 Bronte, Sebastian ...... MoC2.16 Bertrand, Sylvain ...... WeB2 C ...... TuD3.9 ...... WeB2.4 Brossette, Stanislas ...... MoC2.3 Betthauser, Joseph ...... WeA3.17 Brouwer, Dannis M...... TuE3.15 Bezzo, Nicola ...... WeA2.15 Brown, Christopher ...... TuA3.4 Bharambe, Sachin ...... MoA3.8 Brown, H. Ben ...... WeC3.17
244 Browning, Brett ...... WeC3.5 Caselli, Stefano ...... WeA2.12 Bruyninckx, Herman ...... TuD2.11 Castellanos, Jose A...... WeD3.7 Bruzzone, Gabriele ...... WeC3.7 Cavallari, Tommaso ...... WeD3.3 Buchli, Jonas ...... MoD2.18 Cavusoglu, M. Cenk ...... WeA1.1 ...... TuC1 C ...... WeA1.2 ...... ThFD9.1 Cazy, Nicolas ...... MoB3.21 Buehler, Martin ...... TuE1 C Censi, Andrea ...... TuC3.6 Bullard, Kalesha ...... TuE2.10 Chakraborti, Tathagata ...... TuD2.10 Bullock, Ian ...... TuA1.5 Chakraborty, Nilanjan ...... MoA3.20 Burbridge, Christopher ...... TuD2.3 ...... MoC3.8 Burdet, Etienne ...... MoD2.1 Chalasani, Preetham ...... MoD1.13 ...... TuB1.21 Chan, Ka Chun ...... WeB2.20 ...... ThFD9.1 Chan, Wesley Patrick ...... MoD2.5 Burdick, Joel ...... MoA2.15 Chang, Shih-Fu ...... MoC2.19 Burgard, Wolfram ...... MoB1.11 Chao, Haiyang ...... MoB3.3 ...... MoD2.20 Charrow, Benjamin ...... WeA3.4 Burgner-Kahrs, Jessica ...... MoD1.12 Chatzidaki, Avgousta ...... MoA3.7 Burlion, Laurent ...... TuB3.13 Chauhan, Aneesh ...... TuB2.17 Burschka, Darius ...... WeB1.13 Chaumette, Francois ...... MoB3.21 Buschmann, Thomas ...... TuC2.11 Chaves, Stephen ...... TuD3.7 ...... WeB3.9 Che, Fengyu ...... MoA2.3 Buss, Brian G...... TuC2.5 Chebotar, Yevgen ...... TuE2.16 Buss, Martin ...... MoB3.2 Chemori, Ahmed ...... TuA1.12 ...... MoB3.7 ...... TuC1.3 ...... MoC1.16 Chen, Fei ...... WeC2.13 ...... WeA2.9 Chen, Heping ...... WeC1.12 ...... WeB3.3 Chen, Kuo ...... TuE2.11 Bustamante, Gabriel ...... TuD3.21 Chen, Nelson ...... MoC1.20 Butzke, Jonathan ...... MoA2.20 Chen, Sung-Hua ...... WeA1.14 Byl, Katie ...... TuC2.8 Chen, Weihai ...... WeA1.18 ...... WeD2.14 Chen, Wenjie ...... MoB1.13 C Chen, Xiaoping ...... MoB3.10 Caarls, Wouter ...... MoA2.19 Chen, Yingying ...... WeB2.13 Cabras, Paolo ...... WeA1.9 Chen, YuFeng ...... TuD1.17 Cabrera-Mora, Flavio ...... MoA3.17 ...... TuE3.5 Cacace, Jonathan ...... MoD1.6 Chenal, Thomas ...... TuD1.9 Caccia, Massimo ...... WeC3.7 Cheng, Bo ...... TuE1.5 Cadena Lerma, Cesar Dario ...... TuC3.8 Cheng, Gordon ...... WeB1.16 Caetano, Joao ...... TuA3.18 ...... WeD1.14 Caglioti, Vincenzo ...... MoC3.21 ...... WeD3.20 ...... WeB2.15 Cheng, Yu ...... TuA1.7 Cai, Caixia ...... MoB3.12 Cherian, Arun ...... MoB2.10 Caimmi, Marco ...... WeA1.21 Chernova, Sonia ...... TuE2.13 Cakmak, Maya ...... TuC2.14 ...... WeA3.6 Caldwell, Darwin G...... MoC2.5 Chevallereau, Christine ...... TuE3.6 ...... MoD1.10 Chiddarwar, Shital ...... MoA3.8 ...... TuC1.6 Chiu, Han-Pang ...... MoB3.5 ...... WeC2.13 Cho, Changhyun ...... TuB2.10 Caldwell, Timothy ...... MoC1.18 Cho, Hyunchul ...... WeC2.17 Campos, Mario Montenegro ...... WeC3.18 Cho, Kyu-Jin ...... MoA3.9 Canali, Carlo ...... WeC2.13 ...... MoB2.4 Candelas Herías, Francisco Andrés ...... MoA1.15 Cho, Sungwook ...... WeB2.7 Canete, Luis ...... TuC1.7 Choi, Dong - Geol ...... MoB1.7 Cannata, Giorgio ...... TuA1.11 Choi, Hyouk Ryeol ...... TuA3.15 Cannella, Ferdinando ...... WeC2.13 ...... WeC1.8 Canning, Cody ...... WeC1.15 ...... WeC1.10 Cao, Qu ...... WeD2.20 ...... WeD3.17 Cappelleri, David ...... WeD1.11 Choi, Ji-wung ...... MoA2.18 Cardou, Philippe ...... WeB1.12 Choi, Jung-Yun ...... WeA1.4 Carfang, Anthony ...... MoC3.19 Choi, Junho ...... TuB1.19 Carlevaris-Bianco, Nicholas ...... TuC3.20 Choi, Seungmoon ...... MoD1.8 Carlone, Luca ...... TuC3.6 Choi, Sungjoon ...... WeC2.2 Carloni, Raffaella ...... TuE3.11 Choi, Youngjin ...... WeA1.13 ...... WeB1.6 Choi, Yun Seok ...... TuA3.15 ...... WeD2 C ...... WeD3.17 Carpenter, Ryan ...... TuE2.14 Chokushi, Yuuto ...... MoA2.2 Carpin, Stefano ...... MoC3.14 Chong, Nak Young ...... MoD2.19 Carreira, Joao Luis da Silva ...... WeB2.17 Choo, Junghoon ...... TuB2.9 Carrera, Arnau ...... TuA3.20 Choset, Howie ...... MoC3.1 Carreras, Marc ...... TuA3.20 ...... MoC3.6 Carrillo, Henry ...... WeD3.7 ...... MoC3.9 Case, Jennifer ...... MoB2.10 ...... TuB2.19 ...... TuD1.9 ...... TuC1.11 Case, Michael ...... MoC2.19 ...... TuC1.17
245 ...... WeA1.3 Danès, Patrick ...... TuD3.21 ...... WeA2.2 Daney, David ...... SuFD10...... WeA2.10 1 ...... WeC3.17 Dang, Hao ...... WeC2.7 Chou, Alvin ...... MoC1.20 Daniel, Bruce ...... WeB1.17 Choudhary, Siddharth ...... MoC2.15 Daniel, Kohlsdorf ...... WeC1.20 Christensen, Henrik Iskov ...... MoA3.16 Daniilidis, Kostas ...... WeD3.11 ...... MoC2.15 Dankowicz, Harry ...... MoA1.19 Chu, Gilwhoan ...... TuB2.9 Dantam, Neil ...... WeA2.5 Chu, Henry ...... TuB1.5 Dartois, Jean-Emile ...... TuE3.10 Chu, Vivian ...... TuE2.10 Darzi, Ara ...... MoD1.19 Chua, Yuanwei ...... WeB2.14 Das, Aveek ...... MoB3.5 Chuah, Meng Yee (Michael) ...... TuE1.13 Das, Jnaneshwar ...... TuB3.2 Chumtong, Puwanan ...... WeD1.9 Davis, Brian ...... TuD2.14 Chun, Changmook ...... TuB1.14 Davis, Lauren ...... TuA3.3 Chung, Soon-Jo ...... WeA3.18 Davison, Andrew J ...... WeP1L.1 Chung, Wan Kyun ...... MoD1.8 Dayal, Udai, Arun ...... WeC2.19 ...... MoD2.16 Dayoub, Feras ...... WeC3.2 ...... TuC1.2 de Almeida, Anibal ...... MoA3.3 ...... WeD1.16 ...... TuA1.6 Ciliberto, Carlo ...... WeB1.20 de Croon, Guido ...... MoD3.20 Cipra, Raymond ...... WeC3.12 de la Puente, Paloma ...... TuC2.13 Cirillo, Marcello ...... MoA2.16 De Luca, Alessandro ...... MoD2 C Clapham, Richard James ...... MoA3.5 ...... TuB2.4 ...... MoC3.4 ...... TuC1.8 Clark, Ashley ...... TuB2.15 De Nardi, Renzo ...... TuE3.3 Clark, Christopher M...... MoC3.17 De Raedt, Luc ...... TuD2.4 ...... TuE3 C De Schutter, Joris ...... MoD3.12 ...... TuE3.16 Dean Leon, Emmanuel ...... MoB3.12 Clemens, Frank ...... MoB2.8 Dean-Leon, Emmanuel ...... WeB1.16 Coenen, Sebastiaan Antonius Maria ...... WeB3.8 Dear, Tony ...... WeA2.2 Cognetti, Marco ...... MoA3.14 Decanini, Dominique ...... WeD1.3 ...... WeB2.11 ...... WeD1.4 Coleman, David ...... MoC1.18 Degani, Amir ...... WeB2.10 Colgate, Edward ...... TuP1L C Del Bue, Alessio ...... MoC2.18 Colledanchise, Michele ...... MoD3.4 Del Prete, Andrea ...... TuE1.10 Collidge, Bill ...... TuA3.2 Delabarre, Bertrand ...... TuE3.10 Collins, Jason ...... WeA2.16 Dellaert, Frank ...... MoC2.15 Colomé, Adrià ...... MoD2.14 ...... MoC2.17 Coltin, Brian ...... TuE2.3 ...... TuC3.3 Combes, Stacey ...... TuE3.5 ...... TuC3.6 Company, Olivier ...... MoB1.15 ...... WeC3.6 ...... TuA1.19 DelPreto, Joseph ...... TuD1.19 Condal Margarit, Jordi ...... TuD1.2 Demi, Libertario ...... WeA3.14 Conrad, Benjamin ...... WeC1.5 Demonceaux, Cédric ...... MoA2.5 Conte, Christian ...... MoC3.13 Deng, Xinyan ...... TuE1.5 Corke, Peter ...... SuAM1.1 Derawi, Dafizal ...... WeD2.2 ...... MoP1L.1 Deshpande, Ashish ...... MoB2.20 ...... WeC3.2 Deshpande, Nikhil ...... WeC3.15 ...... WeD2.8 Destephe, Matthieu ...... TuC2.16 Correll, Nikolaus ...... MoC1.10 Detry, Renaud ...... SuAM1.1 ...... MoC1.18 Detweiler, Carrick ...... WeD2.6 Cortes, Juan ...... MoA2.14 Devaurs, Didier ...... TuD2.15 ...... TuD2.15 Deyle, Travis ...... TuC2.12 Cortés Poza, David ...... TuB3.3 Dhanak, Manhar ...... TuB3.11 Cortesao, Rui ...... TuB1.3 Di, Wang ...... MoA1.17 Cosentino, Sarah ...... TuC2.16 Di Caro, Gianni A...... MoA3.21 Costante, Gabriele ...... TuE2.9 ...... MoC3.21 Couraud, Laurent ...... WeD1.3 ...... WeA3.16 Cruz, Patricio ...... MoA3.18 ...... WeB2.15 Cui, Dixiao ...... WeD3.8 Di Stefano, Luigi ...... WeD3.3 Cui, Xiang ...... WeA1.18 Dias, Jorge ...... MoD1.3 Cui, Yanzhe ...... MoD3.17 ...... TuE3.2 Culha, Utku ...... MoB2.8 Dietrich, André ...... MoC3.12 Cutkosky, Mark ...... WeB1.17 Digani, Valerio ...... TuA2.3 Cuvillon, Loic ...... TuA1.20 Dille, Michael ...... WeD2.4 D Dillmann, Rüdiger ...... MoC2 C d'Andréa-Novel, Brigitte ...... TuE1.9 ...... WeB3.5 Dabadie, Charles ...... WeB3.6 ...... WeD2.18 Dadashzadeh, Behnam ...... TuC2.10 DiMaio, Simon P...... MoB1.21 Dai, Jian ...... MoC2.5 ...... ThFD6.1 ...... TuE1.2 Dimarogonas, Dimos V...... MoD3.7 Daley, Monica ...... TuC2.6 Dimeas, Fotios ...... WeD1.21 Dame, Amaury ...... TuE3.10 Dinh, Paul ...... MoD3.13
246 Dirafzoon, Alireza ...... WeA3.17 Erdogan, Can ...... TuD2.6 Dissanayake, Gamini ...... MoC3.18 Erez, Tom ...... TuA1.10 ...... TuA2.5 Ertel, Wolfgang ...... WeC2.8 ...... TuC3.1 Escaida Navarro, Stefan ...... MoA1.3 ...... TuC3.11 Escande, Adrien ...... MoC2.3 ...... WeD2.7 ...... WeB2.5 Dixit, Rahul ...... MoC1.14 Escobedo-Cabello, Jesus-Arturo ...... TuE2.6 Djugash, Joseph ...... WeB2.21 Eudes, Alexandre ...... TuD3.10 Dkhil, Mohamed ...... WeD1.2 Eustice, Ryan ...... MoA2.8 Dockter, Rodney ...... TuB1.2 ...... MoB1.8 Dodd, T J ...... WeB1.10 ...... TuC3.20 Doignon, Christophe ...... WeA1.9 ...... TuD3.7 Dollar, Aaron ...... MoA1.7 ...... WeC3.1 ...... TuA1.2 Evdaimon, Theodoros ...... MoA3.7 ...... TuA1.5 Even, Jani ...... TuA3.11 ...... TuD1.18 ...... TuE2.4 Domahidi, Alexander ...... MoC3.13 Ewald, Alexander ...... TuC2.11 Donahue, Thomas ...... WeC1.15 ...... WeB3.9 Dong, Haiwei ...... TuA2.12 F Donner, Philine ...... MoC1.16 Fadlil, Muhammad ...... TuB2.14 Douillard, Bertrand ...... TuB3.15 Fahad, Muhammad ...... WeB2.13 Draelos, Mark ...... WeC3.15 Faigl, Jan ...... TuD2.7 Drake, James ...... MoB1.16 Falcone, Maurizio ...... MoA1.12 ...... TuB1.9 Falkenhahn, Valentin ...... TuC1.9 Drews, Florian ...... WeB3.5 Fang, Zheng ...... MoB3.4 Drews Jr, Paulo ...... WeC3.18 Fankhauser, Péter ...... TuD3.11 Drouilly, Romain ...... TuA2.18 Fantuzzi, Cesare ...... TuA2.3 Drumwright, Evan ...... TuE1.16 ...... WeA3.8 Du, Shaoyi ...... WeD3.8 Farinelli, Alessandro ...... MoC2.18 Dubbelman, Gijs ...... WeA3.14 Farrow, Nicholas ...... MoC1.10 Duceux, Guillaume ...... MoB2.12 Farshidian, Farbod ...... SuFD5.1 Duchaine, Vincent ...... WeB1.12 ...... MoD2.18 Duckett, Tom ...... WeC3.3 Fassbender, Dennis ...... WeA2.6 Dudek, Gregory ...... TuB3.1 Fatikow, Sergej ...... MoC1.17 ...... TuB3.3 Fäulhammer, Thomas ...... WeD3.16 Duisterwinkel, Erik ...... WeA3.14 Faust, Aleksandra ...... SuFD5.1 Dune, Claire ...... MoB3.21 Fearing, Ronald ...... TuD2.21 Dupont, Pierre ...... MoC1.13 Featherstone, Roy ...... TuE1.11 ...... TuB1.1 Feix, Thomas ...... TuA1.5 ...... TuB1.7 Fekete, Sándor ...... WeA3.19 ...... WeA1.11 Felekis, Dimitrios ...... WeB1.14 Dupuis, Yohan ...... WeB3.17 Felfoul, Ouajdi ...... TuB1.7 Durst, Phillip J ...... TuA3.18 ...... WeA1.11 Dutta, Rajdeep ...... MoC3.20 Felt, Wyatt ...... TuD1.8 Dymond, Patrick ...... TuD2.17 Feng, Lin ...... WeD1.5 E Feng, Siyuan ...... MoC2.11 Eckenstein, Nick ...... TuD1.12 Feniello, Ashley ...... WeC2.7 Eder, Kerstin ...... MoD3.5 Feo, Eduardo ...... MoA3.21 Eguchi, Kiyoshi ...... TuB2.6 Fernández, José Javier ...... TuB3.6 Eilering, Anna ...... MoD1.9 Fernández Alcantarilla, Pablo ...... TuD3.9 Einramhof, Peter ...... TuC2.13 Fernández-Moral, Eduardo ...... MoB1.6 Ekekrantz, Johan ...... WeC3.3 Ferrari, Silvia ...... MoA1.13 El Saddik, Abdulmotaleb ...... TuA2.12 ...... MoA1.16 Elayaperumal, Santhi ...... WeB1.17 Ferreira, Antoine ...... MoC1.8 Elbaum, Sebastian ...... WeD2.6 ...... WeD1.6 Elgezua Fernandez, Inko ...... WeC1.9 Ferreira, Fausto ...... WeC3.7 Ellenrieder, Karl von ...... TuB3.11 Ferreira, João Filipe ...... MoD1.3 Elsayed, Yahya ...... MoB2.2 Ferreira, Ricardo ...... TuA2.15 Elwin, Matthew ...... WeA3.13 Ferrer, Gonzalo ...... TuA2.2 Emami, Patrick ...... TuB2.2 Ferri, Federico ...... MoB3.6 Emmerich, Christian ...... WeC1.19 Ficuciello, Fanny ...... TuB2.3 Endo, Mai ...... TuA3.17 Fierro, Rafael ...... MoA3.18 Endo, Mitsuru ...... TuA3.17 Figueredo, Luis Felipe da Cruz ...... TuA1.17 Endo, Nobutsuna ...... TuC2.16 Figueroa, Nadia ...... TuA2.12 Endo, Satoshi ...... TuB2.7 Figueroa, Rafael ...... MoA3.18 Endres, Felix ...... MoB1.11 Filliat, David ...... MoB2.12 Enes, Baptiste ...... MoA3.3 Fink, Jonathan ...... TuA3.19 Englert, Peter ...... MoA1.9 ...... WeA3.4 ...... MoA1.18 Finzi, Alberto ...... MoD1.6 Englsberger, Johannes ...... WeB2.4 Fioraio, Nicola ...... WeD3.3 Enner, Florian ...... WeC3.17 Fiorio, Luca ...... WeB1.20 Entsfellner, Konrad ...... WeC1.3 Fischer, Anath ...... WeC2.16 Eqtami, Alina ...... WeA1.11 Fischinger, David ...... TuC2.13 Erdem, Esra ...... TuD2.5 Flacco, Fabrizio ...... TuB2.4
247 ...... TuC1.8 Geyer, Hartmut ...... TuB1.15 Floreano, Dario ...... MoA3.1 ...... TuC2.9 ...... WeB1.11 Ghiringhelli, Fabrizio ...... MoC3.21 Florek - Jasinska, Monika ...... TuA1.4 Ghrist, Robert ...... MoA1.14 Florentz, Gaspard ...... MoC2.13 Giannarou, Stamatia ...... TuB1.8 Folio, David ...... MoC1.8 Gianni, Mario ...... MoB3.6 ...... WeD1.6 Gienger, Michael ...... MoA1.21 Folkesson, John ...... TuA2.17 ...... WeC2.5 ...... TuA2.20 ...... ThFD12...... TuD2.3 1 Ford, Steven ...... WeC3.17 Giguere, Philippe ...... TuB3.3 Forgoston, Eric ...... TuB3.10 Gilbert, Hunter B...... MoD1.12 Fowler, Dennis ...... MoD1.14 Gillespie, Brent ...... WeD1.20 Fox, Maria ...... ThFD5.1 Gini, Maria ...... SuFD5.1 Franchi, Antonio ...... TuD3.6 ...... MoA3 C ...... ThFD11...... MoB3.11 1 Giusti, Alessandro ...... MoC3.21 Franchi, Giulia ...... MoD1.9 ...... WeA3.16 Francis, Peter ...... TuB1.9 ...... WeB2.15 Frank, Barbara ...... MoD2.20 Glisson, Matthew ...... MoD2.4 Freeman, Randy ...... WeA3.13 ...... TuD1.5 Freese, Marc Andreas ...... SuAM1.1 Godage, Isuru S...... TuD1.13 Frese, Udo ...... TuC3.9 ...... WeB2.9 Frew, Eric W...... MoC3.19 Godoy, Julio ...... MoB3.11 Fries, Carsten ...... TuC3.14 Goerner, Jared ...... WeA3.12 Fry, Katelyn ...... MoA3.11 Gogu, Grigore ...... TuA1.13 Fu, Chenglong ...... TuC2.2 Goins, Alex ...... TuE2.14 Fu, Li-Chen ...... WeA1.14 Gomez, Randy ...... MoD2.7 ...... WeB2.12 Gonçalves, Paulo ...... ThPM1.1 Fuchiwaki, Ohmi ...... TuD1.11 Gong, Chaohui ...... MoC3.9 Fujie, Masakatsu G...... TuB1.13 ...... WeA2.10 ...... WeC1.9 González-Jiménez, Javier ...... MoB1.6 Fukuda, Toshio ...... MoC1.2 Gopalakrishnan, Bharath ...... WeB3.7 ...... MoC1.3 Gosselin, Clement ...... MoB1.1 Fukumori, Kazuhiro ...... MoC1.7 ...... MoB1.12 Funakoshi, Kotaro ...... MoB2.13 ...... WeB1.2 ...... TuB2.14 Gouttefarde, Marc ...... TuA1.14 Furgale, Paul Timothy ...... MoB1.10 Gouveia, Bruno ...... MoD3.18 Furnémont, Raphaël ...... TuD1.6 Gouyon, Fabien ...... TuA3.7 Futaki, Hajime ...... TuC2.16 Goyard, David ...... WeA1.9 G Graña Sanchez, Adrian ...... MoD1.4 Gabiccini, Marco ...... MoD1.11 Granna, Josephine ...... MoD1.12 ...... WeB1.18 Grant, Edward ...... WeC3.15 Gai, Shengnan ...... WeC3.8 Gräser, Axel ...... TuB1.18 Gallagher, William ...... TuB2.8 Gratal Martínez, Xavi ...... WeB1.15 Galloway, Kevin ...... MoB2.7 Gravdahl, Jan Tommy ...... MoA3.2 Galloway, Kevin ...... TuC2.5 ...... MoA3.6 Gambardella, Luca ...... MoA3.21 ...... MoA3.10 ...... MoC3.21 ...... MoC3.7 ...... WeA3.16 Gravish, Nicholas ...... TuE3.5 ...... WeB2.15 Gray, Kierstin ...... MoC1.19 Gammell, Jonathan David ...... TuD2.16 Gray, Wendell ...... TuA3.18 Gams, Andrej ...... TuA2.11 Green, Adrian ...... MoD3.11 Gan, Zhenyu ...... WeD2.16 Greigarn, Tipakorn ...... WeA1.2 Gangloff, Jacques ...... TuA1.20 Griffin, Brent Austin ...... TuC2.5 Gans, Nicholas (Nick) ...... MoD3.11 Grimminger, Felix ...... MoC2.10 Gao, Ming ...... TuE2.8 Grizzle, J.W ...... TuC2.5 Gao, Wei ...... WeC3.12 Grocholsky, Ben ...... WeD2.4 Gaponov, Igor ...... TuD1.3 Groothuis, Stefan S...... WeB1.6 Garabini, Manolo ...... WeB1.5 Gross, Roderich ...... SuFD6.1 Gasparri, Andrea ...... SuAM2.1 ...... WeB1.10 ...... WeA3.7 Grossniklaus, Ueli ...... WeB1.14 Gauthier, Michael ...... WeD1.2 Grunberg, David ...... TuA3.10 ...... ThFD3.1 Gu, Qingyi ...... MoC1.6 Gautier, Maxime ...... MoB1.4 Gu, Yu ...... MoB3.3 Gehring, Christian ...... TuD3.11 Gucunski, Nenad ...... TuA3.16 Geiger, Andreas ...... MoB3.9 Guerin, Kelleher ...... MoD2.11 Gelin, Rodolphe ...... MoD2.8 Guglielmelli, Eugenio ...... TuA1 C Gemici, Mevlana Celaleddin ...... MoB2.18 ...... TuD1.7 Geng, Tao ...... MoB2.2 Guiffo Kaigom, Eric ...... MoD3.19 Genter, Katie ...... MoA3.19 Güler, Püren ...... WeB1.15 Gentilini, Iacopo ...... TuD2.14 Gumprecht, Jan David Jerome ...... WeC1.3 Gerke, Paul ...... MoD3.20 Guo, Chunzhao ...... WeD3.9 Germann, Juerg Markus ...... WeB1.11 Guo, Yi ...... WeB2.13
248 Guowei, Cai ...... TuE3.2 1 Gupta, Satyandra K...... TuB3.11 He, Junhu ...... TuC1.18 Guy, Stephen J...... MoB3.11 He, Qin ...... MoC2.8 Guzzi, Jerome ...... MoC3.21 Hebert, Paul ...... WeD2.14 ...... WeB2.15 Hechtman, Steven A...... TuA3.4 H Hedrich, Jens ...... WeB2.18 Ha, Inyong ...... MoC2.8 Hedrick, Karl ...... WeA3.15 Ha, Junhyoung ...... MoC1.13 Hein, Björn ...... MoA1.3 Ha, Manh-Tuan ...... TuC1.5 Hellbach, Sven ...... WeD3.18 Habed, Adlane ...... MoA2.5 Helmick, Daniel ...... TuB3.15 Habibi, Golnaz ...... MoC1.20 Henderson, Thomas C...... WeC3.15 Hache, Marc-Antoine ...... MoD2.8 Hennig, Philipp ...... TuB2.21 Hada, Yasushi ...... TuA3.13 Henze, Bernd ...... TuE1.14 Hadaegh, Fred ...... WeA3.18 Heppner, Georg ...... WeD2.18 Haddadin, Sami ...... WeB1.7 Heredia, Guillermo ...... TuE3.8 ...... WeB3.11 Herlant, Laura ...... MoD2.13 Hadfield-Menell, Dylan ...... WeC2.3 Hermann, Andreas ...... WeB3.5 Hager, Gregory ...... MoD2.11 Hershberger, Dave ...... MoB3.8 ...... TuD3.1 Herzog, Alexander ...... MoC2.10 Haghiri-Gosnet, Anne-Marie ...... WeD1.3 Herzog, Dennis Levin ...... WeC2.21 Hagita, Norihiro ...... TuA3.11 Heß, Daniel ...... MoD3.3 ...... TuE2.4 Heshmati-alamdari, Shahab ...... TuA3.20 Haidegger, Tamas ...... SuFD3.1 ...... TuC3.13 ...... MoA1.20 Hidalgo-Carrio, Javier ...... MoA2.7 ...... ThPM1.1 Hieida, Chie ...... TuE2.5 Haidu, Andrei ...... WeC1.20 Hildebrandt, Alexander ...... TuC1.9 Hailes, Stephen ...... TuE3.3 Hildebrandt, Arne-Christoph ...... TuC2.11 Haksar, Ravi ...... WeA2.3 ...... WeB3.9 Hamel, William R...... WeC1 C Hill, Andrew John ...... TuD2.8 Hamlet, Alan ...... TuB2.2 Hilliges, Otmar ...... MoC3.13 Hammond III, Frank L...... WeB1.21 Hilton, William ...... MoD3.16 Han, Jungwook ...... TuB3.5 Himstedt, Marian ...... WeD3.18 Hang, Kaiyu ...... TuA1.8 Hindriks, Koen ...... TuC2.17 Hanheide, Marc ...... WeC3.3 Hirata, Yasuhisa ...... TuE3.14 Haninger, Kevin ...... MoB1.13 Hirche, Sandra ...... MoC1.16 Hannaford, Blake ...... WeC1.1 ...... TuD2.18 ...... WeC1.14 Hirschmüller, Heiko ...... TuA2.19 Hansen, Peter ...... WeC3.5 Hlavac, Vaclav ...... MoA1.11 Hara, Yoshitaka ...... WeD3.21 Hoarau, Antoine ...... MoD2.13 Hara, Yusuke ...... MoB2.3 Hochgeschwender, Nico ...... MoC1.21 Harada, Kanako ...... WeA1.10 Hodgins, Jessica ...... TuD1.5 Harada, Kensuke ...... TuC1.12 Hoepflinger, Mark ...... TuD3.11 Hargrove, Levi ...... TuB1.12 Höfer, Sebastian ...... TuD2.2 Harrington, Dagan ...... MoD3.6 Hogan, Neville ...... WeD2.19 Hart, Stephen ...... MoD3.13 ...... WeD2.21 Hartmann, Jan ...... WeD3.18 Hojaij, Abdullah ...... MoB3.20 Hartmann, Mitra ...... ThFD10. Holden, Christian ...... MoA3.10 1 Hollinger, Geoffrey ...... TuD2.7 Hasaneini, Seyed Javad ...... TuC2.3 Hollis, Ralph ...... WeA2.7 Hasegawa, Takaaki ...... TuB2.6 Holobut, Pawel ...... WeB1.9 Hasegawa, Tsutomu ...... TuC1.12 Homma, Yukio ...... TuB1.6 Hasegawa, Yasuhisa ...... MoC1.2 Honda, Fuhito ...... WeD3.21 ...... TuB2.6 Honegger, Dominik ...... WeD3.4 Häselich, Marcel ...... WeB2.18 Hong, Dennis ...... MoC2.8 Hashimoto, Kenji ...... TuA2.15 ...... WeB2.1 ...... TuC2.16 Hong, Jisoo ...... TuB1.14 Hashimoto, Shuji ...... MoB2.3 Hong, Man Bok ...... MoB1.17 Hata, Nobuhiko ...... TuB1.4 Hong, SeongHun ...... TuB2.10 Hatao, Naotaka ...... TuD3.20 Horade, Mitsuhiro ...... MoC1.9 Hattenberger, Gautier ...... TuD3.2 ...... WeD1.9 Hatton, Ross ...... WeA2.2 Hornung, Rachel Hannah ...... WeA2.13 Hauert, Sabine ...... SuFD7.1 Horowitz, Matanya ...... MoA2.15 Hauptman, Traveler ...... WeC2.13 ...... MoD3.2 Hauser, Kris ...... MoD1.9 Hoseinnezhad, Reza ...... TuC3.4 ...... TuA2.7 Hosoda, Koh ...... WeB1.4 Hawes, Nick ...... SuFD4.1 ...... WeC3.14 ...... MoD3.8 How, Jonathan ...... TuE3.4 ...... TuD2.3 How, Jonathan Patrick ...... MoA1.16 Hay, Jennifer ...... MoD2.2 Howard, Ayanna ...... TuB2.1 Hayao, Nakanishi ...... WeD1.10 Hrabar, Stefan ...... WeD2.8 Hayashi, Akinobu ...... MoA1.21 Hsiao, Po-Hao ...... WeB2.12 Hayat, Abdullah Aamir ...... WeC2.19 Hsieh, M. Ani ...... MoC3 C Hayes, Bradley ...... WeC2.9 ...... TuB3.10 Hayward, Vincent ...... ThFD10. Hu, Huosheng ...... MoA3.5
249 ...... MoC3.4 Jacobson, Adam ...... TuA2.13 Hu, Jwu-Sheng ...... WeB3.10 Jacoff, Adam ...... TuA3.2 Hu, Ying ...... WeA1.6 Jain, Siddarth ...... WeD3.13 Huan, Zhijie ...... TuB1.5 Jamisola, Jr., Rodrigo S...... MoD1.10 Huang, Cheng-Ming ...... WeB2.12 Janabi-Sharifi, Farrokh ...... MoB3.14 Huang, Guoquan ...... MoA1.13 ...... TuC3.12 Huang, Hai ...... MoA1.17 Jang, Giho ...... WeA1.13 Huang, Qiang ...... MoC1.3 Jara, Carlos ...... MoA1.15 Huang, Sandy ...... WeC2.3 Jarc, Tony ...... ThFD7.1 Huang, Shoudong ...... TuC3.11 Jaulin, Luc ...... MoA2.11 Huang, Zhiyong ...... WeB2.14 Jayasekara, Peshala Gehan ...... TuB3.19 Huber, Basil ...... TuC3.19 Jayasuriya, Suhada ...... TuC1.4 Huber, Daniel ...... MoA2.10 Jenkin, Michael ...... TuD2.17 ...... TuE3.13 Jensfelt, Patric ...... TuA2.17 Hubicki, Christian ...... TuC2.6 ...... TuA2.20 Hudson, Jonathan ...... TuB3.9 ...... TuD2.3 Huhtala, Kalevi ...... MoA2.18 Jeong, Dong-Hyun ...... TuB2.9 Hunt, Jeremy ...... MoC1.20 Jeong, Donghwa ...... MoD2.15 Huo, Ke ...... WeC3.12 Jeong, Heejin ...... WeB2.7 Huo, Zhiyu ...... MoD2.6 Jeong, Seungwoo ...... TuB2.9 Hur, Sung-moon ...... WeD1.12 Jeong, Sungmoon ...... MoD2.19 Hurst, Jonathan ...... TuC2.6 Jia, Yunyi ...... TuA1.7 ...... TuC2.10 Jian, Yong-Dian ...... TuC3.3 ...... WeC3.13 Jiang, Chao ...... WeB2.13 Hurtos, Natalia ...... TuA3.20 Jiang, Shu ...... MoD3.6 Huskić, Goran ...... WeB3.18 Jiang, Xiaoling ...... WeB1.2 Hussain, Babar ...... MoA2.3 Jimenez-Cano, Antonio ...... TuE3.8 Hutchinson, Seth ...... MoP1L C Jin, Haiyang ...... WeA1.6 ...... MoB3 C Jin, JingFu ...... MoD3.11 ...... MoC3.15 Jin, Maolin ...... TuC1.6 Hutter, Marco ...... TuD3.11 Jin, Minghe ...... WeD1.18 Hwang, Gilgueng ...... WeD1.3 Jin, Tongdan ...... WeC1.12 ...... WeD1.4 Jing, Wuming ...... WeD1.11 Hwangbo, Jemin ...... TuD3.11 Jo, Joonhee ...... MoC1.15 Hyun, Dong Jin ...... WeD2.21 Jöbgen, Benedikt ...... WeB2.18 Hyung, SeungYong ...... WeA1.4 Johannes, Matthew ...... TuA3.4 I Johansson, Anders ...... MoA2.17 Iba, Soshi ...... MoA1.21 John, Meagan ...... MoC1.20 Ibanez, Aurélien ...... WeB2.3 Johnson, Brandon ...... WeD1.20 Ichien, Kentaro ...... MoB2.14 Jones, Chris ...... TuA3.21 Iida, Fumiya ...... MoB2.8 Jones, Mikhail ...... TuC2.6 Iijima, Hiroshi ...... TuB1.13 Jonniaux, Grégory ...... TuB3.13 Ikeda, Atsutoshi ...... TuE2.2 Jordan, Krzysztof ...... WeB3.14 Ikemoto, Shuhei ...... WeB1.4 Joshi, Sanjay ...... TuB2.11 ...... WeC3.14 Jubien, Anthony ...... MoB1.4 Ikeuchi, Katsushi ...... MoD2.4 Julier, Simon Justin ...... TuE3.3 Illing, Boris ...... TuC1.15 Jun, Bong Huan ...... MoC3.5 Imamura, Ryota ...... TuD1.11 Jun, Chanyoung ...... MoA1.14 Inaba, Masayuki ...... MoD2.5 Jun, Seung-kook ...... TuD1.14 Inoue, Koji ...... MoD2.7 Jung, Chan-Yul ...... TuB1.19 Iordachita, Iulian ...... MoD1.13 Jung, Eui-jung ...... WeC3.8 Isaksson, Mats ...... TuA1.15 Jung, Gwang-Pil ...... MoA3.9 Iscen, Atil ...... TuB2.20 Jung, Sunpill ...... MoA3.9 Ishi, Carlos Toshinori ...... TuA3.11 Junichi, Fukuda ...... TuA3.5 Ishigami, Genya ...... TuB3.19 K Ishiguro, Hiroshi ...... MoB2.21 Kaelbling, Leslie ...... WeA2.14 Ishihara, João Yoshiyuki ...... TuA1.17 Kaess, Michael ...... WeD3.10 Ishii, Idaku ...... MoC1.6 Kagami, Satoshi ...... TuD3.20 Ishii, Shin ...... TuE2.4 Kai, Yoshihiro ...... MoD2.9 Ishikawa, Masatoshi ...... WeB2.8 Kaiser, Jörg ...... MoC3.12 Isler, Volkan ...... TuA2.8 Kak, Avinash ...... WeD3.12 ...... TuD3.6 Kakiuchi, Yohei ...... MoD2.5 ...... WeB3.20 Kakizaki, Takao ...... TuA3.17 Istvan, Ulbert ...... MoD2.20 Kallakuri, Nagasrikanth ...... TuA3.11 Ito, Akira ...... MoA1.5 Kalouche, Simon ...... TuB3.12 Itoyama, Katsutoshi ...... TuA3.9 Kamat, Ajinkya ...... MoA3.8 Ivan, Vladimir ...... TuC3.15 Kambhampati, Subbarao ...... TuD2.10 Iwahashi, Naoto ...... MoB2.13 Kamezaki, Mitsuhiro ...... TuA3.12 Iwata, Hiroyasu ...... TuA3.12 Kaminka, Gal A ...... TuD2.20 Iyama, Takahiro ...... TuA3.9 ...... TuE2.7 Izu, Tomoyuki ...... TuA3.13 Kamiyama, Kazuto ...... MoC1.9 J ...... WeD1.9 Jacobs, Sam Ade ...... TuD2 C Kanakia, Anshul ...... MoC1.10 ...... TuD2.19 Kanda, Takefumi ...... TuD1.4
250 Kaneishi, Daisuke ...... TuB1.13 ...... WeD2.19 Kaneko, Kenji ...... WeB2.5 ...... WeD2.21 Kang, Chul-Goo ...... TuC1.5 Kim, Seong-Woo ...... WeB3.19 Kang, Sungchul ...... TuB2.10 Kim, Seung-Jong ...... TuB1.14 ...... TuD1.16 ...... TuB1.19 Kanno, Shotaro ...... MoD2.9 Kim, Sung-Kyun ...... MoC1.15 Kao, Hsien-Tang ...... WeA2.10 Kim, Sunny ...... MoC1.20 Kapadia, Apoorva ...... MoA3.11 Kim, Uikyum ...... WeC1.8 Kapusta, Ariel ...... MoB2.17 ...... WeC1.10 Karamouzas, Ioannis ...... MoB3.11 Kim, Yong-Jae ...... WeA1.4 Karpelson, Michael ...... MoB2.7 Kim, Yongtae ...... WeB1.5 Karras, George ...... TuA3.20 Kim, You Keun ...... MoB2.17 Karydis, Konstantinos ...... TuD2.21 Kim, Young-Loul ...... WeC2.20 Kaseman, Quillan ...... MoC1.20 Kim, Youngmoo ...... MoD3.16 Kastein, Hannah ...... TuE3.16 ...... TuA3.10 Kato, Takahisa ...... TuB1.4 King, H. Hawkeye ...... WeC1.14 Katsura, Seiichiro ...... ThFD8.1 King, Roger ...... TuA3.18 Katyal, Kapil ...... TuA3.4 Kira, Zsolt ...... TuB2.16 Katzschmann, Robert ...... MoB2.6 Kirchner, Frank ...... MoA2.7 Kavraki, Lydia ...... WeA2.1 Kirsch, Robert ...... WeA1.19 Kawahara, Tomohiro ...... WeD1.7 Kishi, Tatsuhiro ...... TuC2.16 Kawakami, Shinji ...... TuA1.18 Kitaguchi, Satoshi ...... MoD2.9 Kawamura, Akihiro ...... TuA1.3 Kjellstrom, Hedvig ...... TuD3.3 Kawamura, Sadao ...... TuA1.3 Klein, Julius ...... TuB1.21 Kawanishi, Michihiro ...... TuA1.18 Klein, Robert H ...... MoA1.16 Kayano, Yuji ...... WeC3.14 Klemm, Sebastian ...... WeB3.5 Kaynama, Shahab ...... WeB3.6 Klinger, Wilhelm ...... TuB3.11 Kazakidi, Asimina ...... MoA3.7 Klingner, John ...... MoC1.10 Kazanzides, Peter ...... ThFD6.1 Klodmann, Julian ...... WeA2.13 Kee, Seong-Hoon ...... TuA3.16 Knips, Guido ...... MoB2.19 Keith, François ...... MoC2.3 Knoll, Alois ...... MoB3.12 Kelasidi, Eleni ...... MoA3.2 Kobayashi, Yo ...... TuB1.13 Kelly, Alonzo ...... TuE1.8 ...... WeC1.9 Kemp, Charlie ...... MoB2.17 Kober, Jens ...... WeC2.5 ...... TuC2.12 Koch, Kevin Koch ...... MoC1.20 Kenmochi, Masanori ...... TuA1.18 Kodagoda, Sarath ...... MoC3.18 Kennedy, Ryan ...... MoA2.4 ...... WeD2.7 Kent, David ...... TuE2.13 Koene, Ansgar Roald ...... TuB2.7 Kervendal, Erwan ...... TuB3.13 Koenig, Sven ...... MoA2.16 Kessens, Chad C...... WeA2.16 Kofron, Michael ...... TuA3.3 Khakpour, Hamed ...... WeB1.3 Koganezawa, Koichi ...... MoA1.4 Khalil, Islam S.M...... WeD1.8 ...... MoA1.5 Khalil, Wisama ...... WeD1.13 Koh, Je-Sung ...... MoA3.9 Khatib, Oussama ...... MoA1 C Koizumi, Norihiro ...... TuB1.6 Khatib, Oussama ...... ThFD12. Kojima, Masaru ...... MoC1.9 1 ...... WeD1.9 Kheddar, Abderrahmane ...... MoC2.3 Kolberg, Mariana ...... MoA2.11 ...... WeB2.5 Koletschka, Thomas ...... WeD3.11 Khoshnam Tehrani, Mahta ...... WeA1.7 Kolev, Svetoslav ...... TuA1.10 Khosoussi, Kasra ...... TuC3.11 Komsuoglu, Haldun ...... TuA3.2 Kia, Solmaz ...... WeA3.5 Kon, Kazuyuki ...... WeC1.13 Kim, Ayoung ...... TuD3.7 Kondaxakis, Polychronis ...... TuC2.18 Kim, ChangHwan ...... TuB1.14 Kondo, Tadahisa ...... TuE2.4 ...... TuB1.19 Kong, Weiwei ...... WeD2.5 Kim, Charles ...... MoB2.5 Konidaris, George Dimitri ...... SuFD4.1 Kim, Donghyeok ...... WeC2.17 Konigorski, Ulrich ...... MoA2.6 Kim, Dongwon ...... WeD1.20 Konyo, Masashi ...... TuA3.5 Kim, Eunwoo ...... WeC2.2 Koo, Inwook ...... MoB2.4 Kim, Hee Joong ...... MoC3.5 Koo, Ja Choon ...... WeC1.10 Kim, Ho Moon ...... TuA3.15 Koo, Seongyong ...... WeC2.10 ...... WeD3.17 Koolen, Twan ...... WeB2.4 Kim, Hyoung-Gon ...... TuC3.17 Kopicki, Marek ...... WeC2.6 Kim, Hyoungkyun ...... MoD1.8 Kormushev, Petar ...... MoD1.10 Kim, Jayoung ...... TuA3.14 Korpela, Christopher M...... TuE3.7 Kim, Ji-Suk ...... MoA3.9 Kose, Hidekazu ...... TuB1.4 Kim, JinWhan ...... TuB3.5 Kosecka, Jana ...... WeD3.1 Kim, Jiyoung ...... WeA1.4 Kosti, Shahar ...... TuE2.7 Kim, Keehoon ...... TuB1.20 Kosuge, Kazuhiro ...... TuB2.13 Kim, Kwan Suk ...... WeD1.19 ...... TuE3.14 Kim, Min Gu ...... TuD3.18 Kothari, Mangal ...... MoC3.20 Kim, Min Jeong ...... WeC2.17 Koumpogiannis, Thomas ...... MoD2.8 Kim, Min Jun ...... TuC1.2 Kovács, Levente ...... MoA1.20 Kim, MinKyu ...... TuB1.20 Kowalewski, Timothy ...... TuB1.2 Kim, Sangbae ...... TuE1.13 ...... TuB1.10
251 Kraetzschmar, Gerhard ...... MoC1.21 ...... WeD3.7 Kragic, Danica ...... MoD3.7 Latscha, Stella ...... TuA3.3 ...... TuA1.8 Lauf, Adrian P...... WeA3.9 ...... TuE2.12 Laugier, Christian ...... SuFD10...... WeB1.15 1 Krajník, Tomáš ...... WeC3.3 ...... SuFD12. Kramer, Rebecca ...... MoB2.10 1 ...... TuD1.9 ...... TuD3.16 Krishna, Madhava ...... WeB3.7 ...... TuE2.6 Krishnamachari, Bhaskar ...... WeA3.7 ...... WeB3.1 Krishnan, Aravindhan ...... TuA2.14 LaValle, Steven M ...... MoB3.1 Krishnan, Girish ...... MoB2.11 ...... TuA2 C Kroeger, Torsten ...... WeA2 C Lawitzky, Andreas ...... WeB3.3 ...... ThFD4.1 Lawrance, Nicholas Robert Jonathon ...... WeD2.11 Kroemer, Oliver ...... TuE2.15 Layton, Curtis ...... WeC3.17 ...... TuE2.16 Lazarescu, Mihai ...... TuA3.2 Kronander, Klas ...... ThFD9.1 Le, Duong ...... MoA2.13 Krovi, Venkat ...... TuD1 C Lee, Alex Xavier ...... WeC2.3 ...... TuD1.14 Lee, C. S. George ...... TuC2 C Krovi, Venkat ...... ThFD6.1 ...... WeA3.11 Krsek, Pavel ...... MoA1.11 Lee, Daniel D...... MoC2.8 Krueger, Volker ...... WeC2.21 Lee, Dong-Hyuk ...... WeC1.8 Krut, Sebastien ...... MoB1.15 ...... WeC1.10 ...... TuA1.19 Lee, Dongheui ...... WeC2.10 Kubota, Takashi ...... TuB3.19 Lee, Dongjun ...... TuB1.6 Kudoh, Shunsuke ...... MoD2.4 Lee, Dongjun ...... ThFD8.1 Kuemmerle, Rainer ...... MoB1.11 Lee, Hosun ...... MoD2.19 Kuiken, Todd ...... TuP1L.1 Lee, Hyeongcheol ...... TuB2.10 Kuipers, Benjamin ...... TuA2.16 Lee, Insup ...... WeA2.15 Kulick, Johannes ...... MoB2.15 Lee, Jaemin ...... TuB1.20 Kumar, R Prasanth ...... MoC1.14 Lee, Jaeyeon ...... TuD2.13 Kumar, Rakesh ...... MoB3.5 Lee, Jeongseok ...... WeA2.3 Kumar, Vijay ...... MoD3.10 Lee, Jihong ...... MoC3.5 ...... TuE3.1 ...... TuA3.14 ...... WeA3.4 Lee, Jinoh ...... TuC1.6 ...... WeC3.9 Lee, Jong Min ...... TuB1.19 Kunz, Tobias ...... WeA2.18 Lee, Jongwoo ...... WeD2.21 Kunze, Lars ...... TuD2.3 Lee, Joon-Young ...... MoC2.14 Kurazume, Ryo ...... TuC1.12 Lee, Joseph ...... MoC2.21 Kurisu, Masamitsu ...... TuB3.17 Lee, Jusuk ...... WeA1.4 Kurniawati, Hanna ...... TuC2.15 Lee, Kiju ...... MoD2.15 Kursa, Michał ...... WeB1.9 Lee, Kwang-Kyu ...... WeA1.4 Kuru, Ismail ...... WeC1.3 Lee, Sang Hyoung ...... TuD3.18 Kutzer, Michael Dennis Mays ...... TuA3.4 Lee, Seong-Oh ...... TuC3.17 Kweon, In So ...... MoA2.5 Lee, Seoung Kyou ...... MoC3.16 ...... MoB1.7 ...... WeA3.19 ...... MoC2.14 Lee, Su-Lin ...... TuB1.8 Kwok, Alan ...... WeD1.19 ...... WeA1.5 Kwon, Dong-Soo ...... WeC2.10 Lee, Woosub ...... TuB2.10 Kwon, Woo Young ...... TuD3.17 ...... TuD1.16 Kwon, Woong ...... WeA1.4 Lefeber, Dirk ...... TuD1.6 Kyriakopoulos, Kostas ...... MoA1.8 Legnani, Giovanni ...... WeA1.21 ...... MoC1.12 Lei, Qujiang ...... TuC1.13 ...... TuA3.20 Leibrandt, Konrad ...... MoD1.19 ...... TuC3.13 Leininger, Matthias R...... MoD1.20 ...... TuE1.7 Lekakou, Constantina ...... MoB2.2 Kyrki, Ville ...... MoA1.2 Lengiewicz, Jakub ...... WeB1.9 ...... TuC2.18 Lennon, Craig ...... WeA2.16 L Lenzi, Tommaso ...... TuB1.12 La, Hung ...... TuA3.16 Leonard, John ...... MoA1.13 Labbé, Mathieu ...... TuC3.5 ...... MoA2.1 Lacerda, Bruno ...... MoD3.8 ...... MoA2.9 Lacroix, Simon ...... TuD3.2 ...... TuB3 C Lagoudakis, Michail ...... WeB2.6 ...... TuB3.14 Lai, Jin-Shin ...... WeA1.14 Lepora, Nathan ...... ThFD10. Laible, Stefan ...... WeC3.11 1 Lam, Tin Lun ...... MoA1.6 Lera, Francisco ...... WeC3.9 Lane, Joshua ...... MoD3.17 Leu, Adrian ...... TuB1.18 Langford, Lindsay ...... MoC1.20 Leung, Henry ...... TuC2.3 Langlois, Thibault ...... TuA3.7 Levihn, Martin ...... TuC1.20 Laribi, Med Amine ...... TuA1.16 Lewis, Bennie ...... WeC1.16 Lasagni, Matteo ...... WeB1.8 Lewis, Michael ...... MoC3.8 Laschi, Cecilia ...... MoB2.1 Li, Bin ...... WeC1.17 Latif, Yasir ...... TuC3.8 Li, Binbin ...... WeC1.12
252 Li, Gang ...... MoA2.6 Lu, David V...... MoB3.8 Li, Hai peng ...... MoB3.16 Lu, Junkai ...... MoB1.13 Li, Haizhou ...... TuC3.2 Lu, Wenjie ...... MoA1.13 Li, Hao ...... MoC1.20 ...... MoA1.16 Li, Luyang ...... MoB3.17 Lu, Xiang ...... WeB2.19 Li, Miao ...... TuE2.12 Lu, Yan ...... MoC2.21 Li, Rui ...... WeB1.19 Lu, Yanyan ...... WeB3.4 Li, Shaohua ...... MoA2.3 Lu, Ying ...... TuE1.12 Li, Yinxiao ...... MoC2.19 Luck, Kevin Sebastian ...... MoD2.17 Li, Yue-ming ...... MoA1.17 Lueth, Tim C...... MoD1.20 Li, Zhi ...... MoC1.19 ...... WeC1.3 Liang, Siyang ...... TuA1.7 Lumia, Ron ...... MoB3.18 Liao, Hongen ...... TuB1.11 Lunenburg, Janno Johan Maria ...... WeB3.8 Liao, Yu-Wei ...... TuB2.5 Luo, Jingru ...... TuA2.7 ...... WeA1.19 Luo, Lingzhi ...... MoA3.20 Liarokapis, Minas ...... MoA1.8 Luo, Ren ...... SuFD10...... MoC1.12 1 ...... TuC3.13 ...... MoB1.19 ...... TuE1.7 Lussier, Jake ...... MoB1.9 Liemhetcharat, Somchaya ...... WeB2.14 Lussier Desbiens, Alexis ...... TuD1.17 Lien, Jyh-Ming ...... WeB3.4 Lutscher, Ewald ...... WeD1.14 Lien, Wei-Ming ...... WeA1.14 Lybarger, Andrew ...... MoA3.20 Likhachev, Maxim ...... MoA2.20 Lynch, Kevin ...... MoOT15 C ...... MoC1.15 ...... TuB2.5 Liljebäck, Pål ...... MoA3.6 ...... WeA1.19 ...... MoC3.7 ...... WeA2.11 Lim, Angelica ...... TuA3.7 ...... WeA3.13 Lim, Gi Hyun ...... TuB2.17 Lyons, Damian ...... MoD3.6 Lim, Hwasup ...... TuC3.17 M Lim, Hyunkyu ...... WeC2.17 Ma, Yingchong ...... WeA2.4 Lin, Chia-Hsun ...... WeA1.14 MacAllister, Brian ...... MoA2.20 Lin, Chung-Yen ...... MoD2.21 MacAlpine, Patrick ...... MoA3.19 Lin, Sheng-Yen ...... WeA1.14 MacDonald, Bruce ...... WeB3 C Lin, Tsung-Wei ...... MoB1.19 Macias, Nate ...... MoB3.19 Lin, Yukun ...... TuE3.16 Maciejewski, Anthony A...... MoB1 C Lin, Yun ...... WeC2.11 MacIver, Malcolm A...... TuE3.12 Lindeman, Robert ...... WeA3.6 MacLachlan, Robert A...... MoD1.17 Lingnau, Daniel C...... TuD3.13 Macnab, Chris ...... TuC2.3 Lippiello, Vincenzo ...... MoD1.6 Maddahi, Yaser ...... MoD1.5 ...... WeD2.3 Mae, Yasushi ...... MoC1.9 ...... WeD2.9 ...... WeD1.9 Liu, An-Sheng ...... WeB2.12 Maeda, Shingo ...... MoB2.3 Liu, Changliu ...... MoD2.10 Maehle, Erik ...... WeD3.18 Liu, Hao ...... WeD2.2 Maffei, Renan ...... MoA2.11 Liu, Hong ...... WeD1.18 Maggiali, Marco ...... WeB1.20 Liu, Hongbin ...... TuE1.2 Magrini, Emanuele ...... TuB2.4 Liu, Jingtai ...... WeB2.19 Mahl, Tobias ...... TuC1.9 Liu, Karen ...... WeA2.3 Mahoor, Mohammad ...... MoD3.17 Liu, Liu ...... TuE2.11 Maier, Thomas ...... WeC1.3 Liu, Ming ...... MoA2.3 Mainprice, Jim ...... WeA3.6 Liu, Ran ...... WeB3.18 Maisonnier, Bruno ...... MoD2.8 Liu, Shih-Yuan ...... WeA3.15 Majidi, Carmel ...... WeC3.16 Liu, Tsung-Ming ...... MoD3.6 Makrodimitris, Michail ...... MoC3.11 Liu, Xiaolong ...... MoD1.16 Malka, Ronit ...... TuD1.17 Liu, Yunhui ...... MoB3.15 Malosio, Matteo ...... WeA1.21 ...... MoB3.17 Mancini, Gregory ...... MoD1.16 Llorente, Domingo ...... TuE3.8 Mansard, Nicolas ...... TuE1.10 Lo, Chan-Hsiang ...... WeA1.14 Manschitz, Simon ...... WeC2.5 Lobaton, Edgar ...... WeA3.17 Mansfeld, Nico ...... WeB1.7 Lodi Rizzini, Dario ...... WeA2.12 Marchand, Eric ...... TuE3.10 Lofaro, Daniel ...... MoD3.16 Marchese, Andrew ...... MoB2.6 ...... WeA3.6 Marino, Alessandro ...... WeA2.21 Long, Philip ...... WeD1.13 Marlow, Kristan ...... TuA1.15 Looi, Thomas ...... MoB1.16 Maroney, Kyle ...... TuC2.21 ...... TuB1.9 Marques, Lino ...... MoA3.3 Lopez-Nicolas, Gonzalo ...... MoA3.15 ...... MoD3.18 ...... ThAM1.1 Marschall, Albert ...... MoA2.6 Lorbach, Malte ...... TuD2.2 Martell, Michael ...... MoC3.3 ...... WeB3.12 Martin, Fernando ...... TuD3.13 Lorenz, Aaron ...... WeD2.6 Martín Martín, Roberto ...... TuC1.19 Lowe, Christopher G...... TuE3.16 ...... WeB3.12 Lowrance, Christopher John ...... WeA3.9 Martinet, Philippe ...... SuFD12. Lowrey, Kendall ...... TuA1.10 1 Lozano-Perez, Tomas ...... WeA2.14 ...... WeD1.13
253 ...... WeD3 C ...... WeD1.8 Martinez, Sonia ...... WeA3.5 Misumi, Jumpei ...... TuD1.4 Martinez Mozos, Oscar ...... WeC3.3 Mita, Seiichi ...... WeD3.9 Martins, Ricardo ...... MoD1.3 Mitchell, Ian ...... WeA1.20 Martinson, Eric ...... TuD3.19 Mitsuishi, Mamoru ...... MoD1.21 Marton, Zoltan-Csaba ...... WeD3.19 ...... TuB1.6 Maruyama, Hisataka ...... MoC1.5 ...... WeA1.10 Marzinotto, Alejandro ...... MoD3.7 Mittendorfer, Philipp ...... WeB1.16 Mason, Matthew T...... MoA1.1 Miura, Jun ...... TuD3.12 Massot-Campos, Miquel ...... TuB3.6 Miyake, Jun ...... MoC1.7 Mastrogiovanni, Fulvio ...... TuA1.11 Mizumoto, Hisashi ...... WeC1.13 Masuda, Taisuke ...... MoC1.5 Mizumoto, Takeshi ...... MoD2.7 ...... WeD1.10 ...... TuA3.8 Mathijssen, Glenn ...... TuD1.6 Mkhitaryan, Artashes ...... WeB1.13 Mathisen, Geir ...... WeC2.14 Möckel, Rico ...... SuFD6.1 Matsubara, Takamitsu ...... MoB2.14 Mohades Kasaei, Seyed Hamidreza ...... TuB2.17 Matsumoto, Yoshio ...... TuD3.15 Mohammad, Siba ...... MoC3.12 Matsumoto, Yuya ...... TuB1.13 Mohammadi, Pouya ...... WeB2.11 Matsuno, Fumitoshi ...... TuB2.19 Mohammadi Nejad Rashty, Aida ...... TuC2.7 ...... WeC1.13 Mohammed, Samer ...... SuFD10. Mavrogiannis, Christoforos ...... TuE1.7 1 Mazel, Alexandre ...... MoD2.8 Mohareri, Omid ...... WeC1.2 Mazlan, Saiful Amri ...... WeD2.2 Mohseni, Kamran ...... TuB3.8 McColl, Derek ...... TuC2.20 ...... TuE1.3 McGee, Timothy G...... TuA3.4 Moldovan, Bogdan ...... TuD2.4 McGill, Stephen ...... MoC2.8 Molinari, Lorenzo ...... WeA1.21 Mcloughlin, Michael ...... TuA3.4 Molinari Tosatti, Lorenzo ...... WeC2.16 McLurkin, James ...... MoC1.20 Momeni, Mahdi ...... WeC2.12 ...... MoC3.16 Momiki, Chinami ...... WeA1.12 ...... WeA3.19 Monica, Riccardo ...... WeA2.12 McMahon, James ...... WeA2.20 Monsuez, Bruno ...... MoD3.9 McMahon, Troy ...... WeA2.17 Montella, Corey ...... TuE3.9 McMullen, Adam ...... MoC1.20 Moon, Hyungpil ...... TuA3.15 Mebarki, Rafik ...... WeD2.9 ...... WeC1.10 Mecja, Geraldo ...... WeB1.14 Moon, Seungbin B...... SuFD3.1 Meger, David Paul ...... TuB3.3 Morales, Marco ...... SuFD5.1 Mehta, Ankur ...... TuD1.19 Morales Saiki, Luis Yoichi ...... TuA3.11 Meier, Franziska ...... TuB2.21 ...... TuE2.4 Meier, Lorenz ...... SuPM2.1 Morari, Manfred ...... MoC3.13 Memberg, William ...... WeA1.19 Mordohai, Philippos ...... WeB3.14 Meng, Max Q.-H...... MoB1.3 Morel, Guillaume ...... WeC1.11 ...... WeD3.15 Morgan, Daniel ...... WeA3.18 Menguc, Yigit ...... WeB1.21 Morikawa, Shigehiro ...... TuE1.4 Menna, Matteo ...... MoB3.6 Morimoto, Jun ...... WeA1.17 Merriaux, Pierre ...... WeB3.13 Morin, Pascal ...... TuD3.10 ...... WeB3.17 Morisset, Benoit ...... TuA2.18 Merritt, Gabrielle ...... TuA3.3 Morita, Akio ...... WeA1.10 Mersha, Abeje Y...... TuE3.11 Moro, Federico Lorenzo ...... ThFD12. Messenger, Sean ...... MoC3.17 1 Metta, Giorgio ...... MoB1.14 Morooka, Ken'ichi ...... TuC1.12 ...... MoD3.14 Morris, Timothy ...... WeC3.2 ...... TuE1.10 Motooka, Kouma ...... TuC3.16 ...... WeB1.20 Motoyoshi, Takahiro ...... MoC1.9 Mettler, Berenice ...... WeC1.17 Moualeu, Antonio ...... TuB2.8 Meyer, Bertrand ...... MoD3.15 Moulard, Thomas ...... MoC2.2 Mezouar, Youcef ...... TuA1.13 ...... MoC2.3 ...... WeC3.4 Mueggler, Elias ...... TuC3.19 ...... ThAM1.1 Mueller, Andre ...... WeA2.6 Michaud, Francois ...... TuC3.5 Mueller, Christian Atanas ...... TuD3.4 Michini, Matthew ...... TuB3.10 Mueller, Joerg ...... WeA2.8 Mifsud, Alexis ...... TuD3.21 Mühlig, Manuel ...... MoA1.21 Mikami, Yuya ...... MoC2.2 Mukadam, Mustafa ...... MoA1.10 Milford, Michael J ...... TuA2.13 Mun, Hyeong Min ...... TuA3.15 Millard, Alan Gregory ...... WeA2.19 ...... WeD3.17 Miller, David W...... TuB3.14 Muntwyler, Simon ...... WeB1.14 Miller, Lauren ...... TuE3.12 Murata, Ryosuke ...... WeC1.13 Miller, Philip ...... MoB3.5 Murino, Vittorio ...... MoC2.18 Mills, James K...... TuB1.5 Murphey, Todd ...... TuE3.12 Milutinovic, Dejan ...... MoC1.19 Murphy, Robin ...... TuA3.1 Minamoto, Gaku ...... TuA3.6 Murphy, Ryan Joseph ...... TuA3.4 Minor, Mark ...... MoD1.7 ...... WeA1.8 Miraldo, Pedro ...... WeB3.16 Murray, Richard ...... MoD3.2 Mishima, Yuuki ...... TuD1.20 Murrieta-Cid, Rafael ...... WeB3.15 Misra, Sarthak ...... MoD1.2 Myhre, Torstein ...... WeD1.15
254 Mylonas, George ...... WeA1.5 ...... WeB1.20 N Norouzi, Mohammad ...... TuA2.5 Naegeli, Tobias ...... MoC3.13 Nowicki, Michał ...... WeD2.18 Nagai, Takayuki ...... MoB2.13 ...... WeD3.14 ...... TuB2.14 Nunes, Rui ...... MoB2.7 ...... TuE2.5 Nunes, Urbano ...... SuFD12. Nagaoka, Masanori ...... TuB1.13 1 Nagasaka, Shogo ...... MoB2.13 ...... WeB2.17 Nagatani, Keiji ...... TuA3.13 Nurzaman, Surya G...... MoB2.8 Nagavalli, Sasanka ...... MoA3.20 O Nageotte, Florent ...... WeA1.9 O'Kane, Jason ...... TuA2.10 Nagi, Jawad ...... WeA3.16 Oberländer, Jan ...... TuE2.8 Nahavandi, Saeid ...... TuA1.15 Ochiai, Yuya ...... TuE2.2 Najafi, Mohammad ...... WeD3.5 Odhner, Lael ...... MoA1.7 Naka, Shigeyuki ...... TuE1.4 Ogasawara, Tsukasa ...... TuE2.2 Nakadai, Kazuhiro ...... MoD2.7 Ogawa, Takeshi ...... TuE2.4 ...... TuA3.7 Ogle, Jonathan ...... TuB3.2 ...... TuA3.8 Ogren, Petter ...... MoD3.4 Nakajima, Masahiro ...... MoC1.2 Oh, Paul Y...... MoC2.9 ...... MoC1.3 ...... TuE3.7 Nakamura, Keisuke ...... MoD2.7 ...... WeA3.6 ...... TuA3.7 ...... WeD2.1 ...... TuA3.8 Oh, Sang-Rok ...... MoC1.15 Nakamura, Tomoaki ...... MoB2.13 ...... TuB1.20 ...... TuB2.14 ...... WeD1.12 Nakamura, Yoshihiko ...... TuD2.18 Oh, Songhwai ...... WeC2.2 Nakamura, Yutaka ...... MoB2.21 Oh, Yonghwan ...... MoC1.15 Nakashima, Yasutaka ...... TuB1.13 ...... WeD1.12 Nakata, Yoshihiro ...... MoB2.21 Ohara, Kenichi ...... MoC1.9 Nakatomi, Hirofumi ...... WeA1.10 ...... WeD1.9 Narikiyo, Tatsuo ...... TuA1.18 Ohata, Takuma ...... TuA3.8 Nashashibi, Fawzi ...... TuC3.10 Ohya, Akihisa ...... WeD3.21 Natale, Lorenzo ...... MoB1.14 Okada, Kei ...... MoD2.5 ...... MoD3.14 Okada, Masafumi ...... WeA2.9 ...... TuE1.10 Okadome, Yuya ...... MoB2.21 ...... WeB1.20 Okal, Billy ...... MoD2.3 Navarro-Alarcon, David ...... MoB3.15 Okamoto, Takahiro ...... MoD2.4 Neerincx, Mark ...... TuC2.17 Okamura, Allison M...... MoD1.1 Negre Carrasco, Pep Lluis ...... TuB3.6 ...... WeB1 C Neira, José ...... TuC3 C ...... WeC1.7 ...... TuC3.8 Okano, Teruo ...... MoC1.7 ...... WeP1L C Okeke, Nnena ...... MoC1.20 ...... WeD3.7 Okumura, Ichiro ...... TuB1.4 Nejat, Goldie ...... TuC2.20 Okuno, Hiroshi G...... TuA3.7 Nelson, Bradley J...... WeB1.14 ...... TuA3.9 ...... ThFD3.1 Okutomi, Masatoshi ...... TuC3.16 Nenci, Fabrizio ...... WeA3.10 Olds, Kevin ...... MoD1.13 Nepusz, Tamás ...... WeA3.20 Oleynikova, Helen ...... WeD3.4 Neuland, Renata ...... MoA2.11 Oliveira, João Lobato ...... TuA3.7 Neumann, Gerhard ...... MoD2.17 Oliveira, Miguel ...... TuB2.17 Neumann, Klaus ...... MoB2.9 Oliver, Gabriel A...... TuB3.6 Neumann, Ruediger ...... TuC1.9 Ollero, Anibal ...... TuE3.8 Neunert, Michael ...... MoD2.18 ...... WeD2.11 Nevarez, Victor ...... MoB3.18 Olson, Edwin ...... MoB1.2 Neveln, Izaak ...... TuE3.12 ...... MoC2.20 Ngo, Phillip ...... TuB3.2 Olszowy, Wiktor ...... MoB3.7 Nguyen, Dinh Quan ...... TuA1.14 Omari, Sammy ...... TuD3.11 Nguyen, Kim Doang ...... MoA1.19 Omidshafiei, Shayegan ...... MoA1.16 Nguyen, Linh Van ...... MoC3.18 Omori, Takashi ...... TuE2.5 Nguyen, Luan ...... TuA3.16 Orfanoudakis, Emmanouil ...... WeB2.6 Ni, Fenglei ...... WeD1.18 Orin, David ...... WeB2.2 Nicklas, Anselm ...... WeB3.3 Oriolo, Giuseppe ...... MoA2 C Nicola, Jeremy ...... MoA2.11 ...... MoA3.14 Nierhoff, Thomas ...... TuD2.18 ...... WeB2.11 Niimi, Miyako ...... WeD1.10 Orsag, Matko ...... TuE3.7 Nikitenko, Agris ...... TuA3.18 Ortmeier, Frank ...... WeC2.18 Nishida, Shin-Ichiro ...... TuB3.18 Osa, Takayuki ...... MoD1.21 Nisky, Ilana ...... ThFD7.1 Osaki, Naoto ...... TuD1.4 Noda, Tomoyuki ...... WeA1.17 Osendorfer, Christian ...... WeA2.13 Nomiya, Akira ...... TuB1.6 Ota, Hiroki ...... MoC1.7 Noohi, Ehsan ...... WeC1.6 Otake, Yoshito ...... WeA1.8 Noori, Narges ...... TuA2.8 Otsuka, Takuma ...... TuA3.9 ...... WeB3.20 Otsuki, Masatsugu ...... TuB3.18 Nori, Francesco ...... TuE1.10 Ott, Christian ...... TuA1.4
255 ...... TuE1.14 ...... WeA1.15 ...... WeB2.4 ...... WeA1.16 Otte, Stefan ...... MoB2.15 Pateraki, Maria ...... WeB2.16 Ozawa, Ryuta ...... TuD1.20 Pateromichelakis, Nikolaos ...... MoD2.8 Ozgur, Erol ...... TuA1.13 Pathak, Kaustubh ...... TuD3.4 P Patoglu, Volkan ...... TuD2.5 Pacchierotti, Claudio ...... MoD1.2 Paudel, Danda Pani ...... MoA2.5 Pacheco-Lopez, Paulette ...... MoD1.13 Paul, Oliver ...... MoD2.20 Pack, Daniel ...... MoC3.20 Paull, Liam ...... MoA2.9 Padois, Vincent ...... WeB2.3 Paulus, Dietrich ...... WeB2.18 Page, Jared ...... WeD2.10 Pauwels, Karl ...... TuC3.15 Paik, Jamie ...... MoB2 C ...... TuD3.3 ...... TuD1.2 ...... WeB1.15 ...... TuD1.9 Pavone, Marco ...... MoC3.14 Paikan, Ali ...... MoD3.14 ...... TuB2.15 Pajarinen, Joni ...... MoA1.2 Pedersen, Mikkel Rath ...... WeC2.21 ...... TuC2.18 Pedrocchi, Nicola ...... WeC2.16 Pajic, Miroslav ...... WeA2.15 Pekarovskiy, Alexander ...... WeA2.9 Paladini, Marco ...... MoC2.16 Peliti, Pietro ...... MoA3.14 Palmer, Andrew William ...... TuD2.8 Pellegrinelli, Stefania ...... WeC2.16 Palmieri, Luigi ...... MoA2.12 Peñalver, Antonio ...... TuB3.6 Palomer, Albert ...... TuB3.6 Pentzer, Jesse ...... TuE1.6 ...... TuB3.7 Peremans, Herbert ...... TuA2.13 Palomeras, Narcis ...... TuA3.20 Perreault, Eric ...... TuB2.5 ...... TuB3.6 ...... WeA1.19 Palunko, Ivana ...... MoC1.16 Perrin, Nicolas Yves ...... MoC2.5 Panahi, Fatemeh ...... WeC2.15 Perruquetti, Wilfrid ...... WeA2.4 Pang, Yongjie ...... MoA1.17 Pesenti Gritti, Armando ...... WeB2.15 Pangercic, Dejan ...... ThFD5.1 Peters, Jan ...... MoD2.17 Papadakis, Panagiotis ...... TuC2.19 ...... TuE2.15 Papadopoulos, Evangelos ...... MoC3.11 ...... TuE2.16 ...... TuB3.16 ...... WeC2.1 ...... WeD2.12 ...... WeC2.5 Papanikolopoulos, Nikos ...... TuB1 C Petersen, Joshua ...... WeC1.4 ...... WeA3.3 Peterson, Taylor ...... TuE3.16 Pappas, George J...... MoD3.1 Petersson, Lars ...... WeD3.5 ...... MoD3.10 Petrelli, Alioscia ...... WeD3.3 ...... WeA2.15 Petric, Tadej ...... TuA2.11 Para, Matthew ...... TuA3.4 Petrík, Vladimír ...... MoA1.11 Paraskevas, Iosif S...... WeD2.12 Pettersen, Kristin Y...... MoA3.2 Parastegari, Sina ...... WeC1.6 ...... MoA3.6 Parent, Gershon ...... TuA2.21 ...... MoC3.7 Parigi Polverini, Matteo ...... WeB3.2 ...... WeD1.15 Park, Chan Min ...... TuA3.15 Pfeifer, Rolf ...... TuB2.18 ...... WeD3.17 Pfingsthorn, Max ...... WeC3.7 Park, Chung Hyuk ...... SuFD9.1 Phillips-Grafflin, Calder ...... WeA3.6 Park, Daegeun ...... MoB2.4 Piater, Justus ...... MoB2.16 Park, Daehyung ...... MoB2.17 ...... ThFD5.1 Park, Frank ...... MoC1.13 Piccoli, Matthew ...... TuA3.3 ...... TuE1.1 Pieropan, Alessandro ...... TuD3.3 Park, Hae Won ...... SuFD9.1 Pierri, Francesco ...... WeA2.21 Park, Hae-Won ...... TuE1.13 Pierrot, François ...... MoB1.15 Park, Hyongju ...... MoC3.15 ...... TuA1.12 Park, Jaeheung ...... WeB1.5 ...... TuA1.19 Park, Jeonghong ...... TuB3.5 ...... TuC1.3 Park, Johnny ...... WeD3.12 Piperakis, Stylianos ...... WeB2.6 Park, Jong Hyeon ...... TuB2.9 Pippin, Charles ...... MoA3.16 Park, Myoung Soo ...... TuD3.5 Pires, Bernardo ...... MoA2.10 Park, Seongsik ...... MoD2.16 Pirri, Fiora ...... MoB3.6 Park, Shinsuk ...... TuB1.19 Pizarro, Oscar ...... WeC3.10 Park, Wooram ...... TuD2.13 Plaku, Erion ...... MoA2.13 Park, Young Jin ...... WeD1.16 ...... WeA2.20 Parker, David ...... MoD3.8 Platt, Robert ...... WeB1.19 Parker, Lynne ...... WeC2 C Poignet, Philippe ...... MoD1.4 Parlitz, Christopher ...... TuC1.21 Pollard, Evangeline ...... TuC3.10 Parmiggiani, Alberto ...... MoB1.14 Pollard, Nancy S ...... TuC1.15 Parness, Aaron ...... TuB3.12 Pollefeys, Marc ...... WeD3.4 ...... WeB3.21 Polushin, Ilia G...... MoD1.15 Parrott, Christopher ...... WeB1.10 ...... MoD1.18 Pastor, Peter ...... MoC2.10 Pomares, Jorge ...... MoA1.15 Patel, Nisha ...... MoD1.19 Ponte, Hugo ...... TuC1.17 Patel, Rajnikant V...... MoD1.15 Popov, Dmitry ...... TuD1.3 ...... MoD1.18 Popova, Irina ...... MoB2.19 ...... WeA1.7 Porez, Mathieu ...... TuE3.6
256 Portello, Alban ...... TuD3.21 Reynaerts, Dominiek ...... MoC3.2 Portugal, David ...... MoA3.16 Reynolds, Matthew ...... TuC2.12 ...... MoD3.18 Rezazadeh, Siavash ...... WeC3.13 Posenauer, Heiko ...... WeC2.8 Rhudy, Matthew ...... MoB3.3 Post, David ...... WeD2.17 Riano, Lorenzo ...... SuFD4.1 Poulakakis, Ioannis ...... TuD2.21 Ribas, David ...... TuB3.7 ...... WeD2.20 Ribeiro, Alejandro ...... WeA3.4 Pounds, Paul ...... WeD2.10 Ricci, Elisa ...... TuE2.9 Prada, Miguel ...... TuB2.7 Riccomini, Emanuele ...... MoD1.11 Prasad, Kush ...... MoA2.20 Richards, Arthur ...... MoA2.17 Pratt, Jerry ...... WeB2.4 Richardson, Andrew ...... MoC2.20 Prattichizzo, Domenico ...... MoD1.2 Ridao, Pere ...... TuB3.6 Premebida, Cristiano ...... WeB2.17 Ridao, Pere ...... TuB3.7 Prestes, Edson ...... MoA2.11 Riedel, Sebastian Danilo ...... MoD2.11 ...... ThPM1.1 Righetti, Ludovic ...... MoA1.9 Primerano, Richard ...... MoA3.4 ...... MoC2.6 Prusa, Daniel ...... MoA1.11 ...... MoC2.10 Puig, Luis ...... WeD3.11 Ristic-Durrant, Danijela ...... TuB1.18 Pulido Fentanes, Jaime ...... WeC3.3 Ritter, Helge Joachim ...... TuB2.12 Q Rivera, Jordan ...... MoB2.5 Qi, Peng ...... TuE1.2 Rives, Patrick ...... MoB1.6 Qi, Ronghuai ...... MoA1.6 ...... TuA2.18 Qian, Huihuan ...... WeC2.4 ...... TuC2.19 Qin, Yi ...... TuE1.5 Riviere, Cameron N...... MoD1.17 Qiu, Chen ...... TuE1.2 Rizzo, Carlos ...... WeC3.9 Qiu, Kejie ...... MoA2.3 Roa, Maximo A...... TuE1.14 Qiu, Zhaopeng ...... WeA2.4 Robbins, Nicholas ...... MoC1.20 Quan, Qiquan ...... TuB3.20 Roberts, Richard ...... MoC2.17 Queisser, Jeffrey ...... MoB2.9 Robuffo Giordano, Paolo ...... MoB3.21 Quinton, Jean-Charles ...... WeC3.4 Rocco, Paolo ...... WeB3.2 R ...... WeD1.17 Racz, Peter ...... MoD2.2 Rocha, Rui P...... MoA3.16 Radford, Nicolaus ...... MoD3.13 Rodriguez y Baena, Ferdinando ...... WeC1.4 Radkhah, Katayon ...... WeD2.15 Rodriguez-Seda, Erick J...... WeC1.18 Raharijaona, Thibaut ...... TuB3.13 Roemer, Kay ...... WeB1.8 Raiola, Gennaro ...... MoD2.13 Roennau, Arne ...... WeB3.5 Ramaithitima, Rattanachai ...... MoD3.10 ...... WeD2.18 Raman, Vasumathi ...... MoA3.12 Roh, Kyungshik ...... WeA1.4 Ramani, Karthik ...... WeC3.12 Rojas, Nicolas ...... TuA1.2 Ramaswamy, Arunkumar ...... MoD3.9 Roldan, Jay Ryan ...... MoC1.19 Ramezani, Alireza ...... TuC2.5 Rolf, Matthias ...... MoB2.9 Ramirez-Amaro, Karinne ...... WeD3.20 Rollinson, David ...... MoC3.6 Ranasinghe, Ravindra ...... MoC3.18 ...... MoC3.9 Randazzo, Marco ...... MoB1.14 ...... WeC3.17 Randy, Mackay ...... TuA3.13 Romano, Amedeo ...... TuB2.3 Ranganathan, Pradeep ...... MoB1.2 Roppenecker, Daniel B...... MoD1.20 Rangaprasad, Arun Srivatsan ...... WeA1.3 Ros, Eduardo ...... TuC3.15 Ranzani, Tommaso ...... MoB2.2 Rosa, Benoît ...... WeC1.11 Rasmussen, Christopher ...... MoC2.9 Rosa, Lorenzo ...... MoA3.14 Ratliff, Nathan ...... MoA1.9 Rosa, Nelson ...... WeA2.11 Ravet, Alexandre ...... TuD3.2 Rosales, Carlos ...... WeB1.18 Régnier, Stéphane ...... WeD1.2 Rosasco, Lorenzo ...... WeB1.20 Rehder, Joern ...... MoB1.10 Roscup, Nathan ...... WeB1.19 Rehg, James ...... MoB2.17 Rosen, Jacob ...... MoC1.19 Reichard, Karl ...... TuE1.6 Rossi, Roberto ...... WeD1.17 Reid, Ian ...... TuC3.7 Rossmann, Juergen ...... MoD3.19 Reid, Jason ...... WeD2.14 Rotella, Nicholas ...... MoC2.6 Reimann, Hendrik ...... MoB2.19 Rouleau, Michael ...... MoC2.8 Reiner, Benjamin ...... WeC2.8 Rounds, Stephen ...... WeA3.5 Reinhart, Rene Felix ...... MoB2.9 Rubenstein, Michael ...... SuFD6.1 ...... MoD2.12 Rudas, Imre J...... MoA1.20 Reis, Luís Paulo ...... TuA3.7 Ruffier, Franck ...... TuB3.13 Reishus, Dustin ...... MoC1.10 Ruggiero, Fabio ...... WeD2.3 Reiter, Austin ...... MoD1.14 Rus, Daniela ...... MoA3.13 Rekleitis, Georgios ...... TuB3.16 ...... MoB2.6 Rekleitis, Ioannis ...... TuD3.8 ...... TuD1.19 Remazeilles, Anthony ...... TuB2.7 ...... WeA3.1 Rembisz, Justine ...... WeC3.17 Rusakov, Andrey ...... MoD3.15 Remy, C. David ...... TuD1.8 Russell, David E...... TuD3.13 ...... TuE1.15 Ruther, Patrick ...... MoD2.20 ...... WeD2.16 Ryan, Corey ...... TuD1.21 Ren, Hongliang ...... MoB1.3 Rykowski, Joshua ...... MoC1.20 Renzaglia, Alessandro ...... WeB3.20 Ryu, Heng Jun ...... MoC1.5 Revell, James ...... MoA2.17 Ryu, Jee-Hwan ...... TuD1.3
257 S Scheutz, Matthias ...... TuD2.10 Sa, Inkyu ...... WeD2.8 ...... WeC1.15 Saafi, Houssem ...... TuA1.16 Schlenoff, Craig ...... ThPM1.1 Saaj, Chakravarthini ...... MoB2.2 Schmidt, Nico M...... TuB2.18 Sabatta, Deon ...... TuC3.18 Schmiedeler, James ...... WeD2.17 Sabattini, Lorenzo ...... TuA2.3 Schneider, Caitlin ...... WeC1.2 ...... WeA3.8 Schneider, Markus ...... WeC2.8 ...... ThFD11. Schneider, Sven ...... MoC1.21 1 Schneider, Ulrich ...... WeC2.12 Sabiron, Guillaume ...... TuB3.13 Schnoes, Florian ...... MoD1.20 Sadat, Abbas ...... TuA2.4 Schoellig, Angela P...... SuFD5.1 Sadler, Brian ...... MoC3.14 Schönbein, Miriam ...... MoB3.9 Saenz-Otero, Alvar ...... TuB3.14 Schöner, Gregor ...... MoB2.19 Saffiotti, Alessandro ...... SuFD4.1 Schonert, Martin ...... MoA1.3 Saglam, Cenk Oguz ...... TuC2.8 Schornick, Jeff ...... WeA3.17 Sagues, Carlos ...... MoA3.15 Schrimpf, Johannes ...... WeC2.14 Saha, Indranil ...... MoD3.10 ...... WeD1.15 Saha, Subir Kumar ...... WeC2.19 Schubert, Bryan ...... WeB1.11 Sahin, Erol ...... SuFD11. Schultz, Joshua ...... MoC3.3 1 Schuster, Martin Johannes ...... TuA2.19 Saida, Masao ...... TuE3.14 Schwager, Mac ...... MoA3.13 Saito, Nobuhito ...... WeA1.10 Schwartz, Ira ...... TuB3.10 Saitoh, Yumi ...... TuA1.18 Schwerin, Michael ...... WeC3.17 Sakaino, Sho ...... WeA1.12 Scioni, Enea ...... TuD2.11 Sakamoto, Naoaki ...... MoC1.6 Scobee, Dexter ...... MoC3.17 Sakar, Mahmut Selman ...... WeB1.14 Scognamiglio, Joao ...... MoB2.4 Salcudean, Septimiu E...... WeC1.2 Seabra Lopes, Luís ...... TuB2.17 Salim, Nurul Dayana ...... WeD2.2 Secchi, Cristian ...... TuA2.3 Salti, Samuele ...... WeD3.3 ...... WeA3.8 Salvi, Giampiero ...... TuD3.3 Seegmiller, Neal Andrew ...... TuE1.8 Samarasekera, Supun ...... MoB3.5 Seehra, Jasjeet Singh ...... WeC3.12 Sanchez, M. Ivan ...... TuE3.8 Segal, Aleksandr V...... TuC3.7 Sanchez Secades, Luis Alonso ...... MoD1.4 Seidel, Daniel ...... WeC1.19 ...... WeD1.8 Seipel, Justin ...... MoB2.10 Sandamirskaya, Yulia ...... TuB2.12 ...... MoC2.4 Sandini, Giulio ...... WeB1.20 Sekar, Karthik Srivatsa ...... MoC3.10 Sandoval, Eduardo ...... MoD2.2 Seki, Masatoshi ...... TuB1.13 Sanfeliu, Alberto ...... TuA2.2 Sekimoto, Masahiro ...... TuB1.16 Sano, Hiroshi ...... TuB1.16 Selman, Bart ...... TuD2.12 Santos, Elerson Rubens da Silva ...... WeA3.2 Seneci, Carlo Alberto ...... MoD1.19 Santos, Luís ...... TuB1.3 Seneviratne, Lakmal ...... TuE1.2 Santos, Vitor ...... TuD3.16 ...... TuE3.2 Santos-Victor, José ...... TuA2.15 Senlet, Turgay ...... TuA3.16 Sanz, Pedro J ...... TuB3.6 Senoo, Taku ...... WeB2.8 Sapkota, Krishna ...... MoA2.20 Sensinger, Jonathon ...... TuB1.12 Sarakoglou, Ioannis ...... MoD1.11 Sentis, Luis ...... SuFD8.1 Saribatur, Zeynep G...... TuD2.5 ...... WeD1.19 Saripalli, Srikanth ...... TuA2.14 Seo, Joonho ...... TuB1.6 Sarne, David ...... TuE2.7 Seok, Jushin ...... TuD1.16 Sasaki, Yoko ...... TuD3.20 Sepehri, Nariman ...... MoD1.5 Sattar, Junaed ...... WeA1.20 Serio, Alessandro ...... MoD1.11 Sattel, Thomas ...... MoD3.3 Serra, Diana ...... WeD2.3 Satzinger, Brian ...... WeD2.14 Seshia, Sanjit A...... MoD3.10 Savatier, Xavier ...... WeB3.13 Seto, Mae ...... MoA2.9 ...... WeB3.17 ...... TuB3.9 Sawodny, Oliver ...... TuC1.9 Setterfield, Timothy Philip ...... TuB3.14 Saxena, Abhijit ...... WeA1.15 Seyfarth, Andre ...... TuC2.7 Saxena, Ashutosh ...... MoB2.18 ...... WeD2.15 ...... TuD2.12 Sfakiotakis, Michael ...... MoA3.7 Sayama, Kazuhiro ...... MoA1.4 Shah, Brual C...... TuB3.11 Scaramuzza, Davide ...... TuC3.19 Shahbazi, Mahya ...... WeA1.15 Scassellati, Brian ...... TuC2.1 ...... WeA1.16 ...... WeC2.9 Shakeri, Moein ...... TuC3.21 Schaal, Stefan ...... MoA1.9 Shang, Jianzhong ...... MoD1.19 ...... MoC2.6 Sharma, Rajnikant ...... MoC3.20 ...... MoC2.10 Shaya, Benjamin ...... TuD1.19 ...... TuB2.21 Shayya, Samah ...... MoB1.15 ...... TuE2.1 ...... TuA1.19 Schamm, Thomas ...... TuE2.8 Sheh, Raymond Ka-Man ...... TuA3.2 Schauerte, Boris ...... MoC2.12 Shell, Dylan ...... ThFD11. Schearer, Eric ...... TuB2.5 1 ...... WeA1.19 Shemer, Natan ...... WeB2.10 Scheding, Steven ...... TuD2.8 Shen, Hsin-Yu Jennifer ...... MoC1.20 Scherer, Sebastian ...... MoB3.4 Shen, Lincheng ...... WeD2.5
258 Shen, Xiaotong ...... WeB3.19 ...... TuE2.6 Sheng, Ming-Wei ...... MoA1.17 Spinello, Luciano ...... WeA3.10 Shepherd, Robert ...... MoB2.7 Spletzer, John ...... TuE3.9 Shi, Chaoyang ...... TuB1.8 Sprinkhuizen-Kuyper, Ida ...... MoD3.20 Shi, Zhan ...... TuB1.11 Sprunk, Christoph ...... MoB1.11 Shigemune, Hiroki ...... MoB2.3 Spyrakos-Papastavridis, Emmanouil ...... MoC2.5 Shim, David Hyunchul ...... WeB2.7 Srinivasa, Siddhartha ...... SuFD11. Shim, Inwook ...... MoC2.14 1 Shim, Vui Ann ...... TuC3.2 ...... MoC1.15 Shima, Takeshi ...... TuC3.16 ...... TuD2.16 Shimotomai, Takayuki ...... TuE2.5 ...... ThFD2.1 Shin, Jiwon ...... MoD3.15 Srinivasan, Mandayam ...... WeB1.19 Shin, Sung Yul ...... TuB1.14 Srivastava, Siddharth ...... SuFD4.1 Shin, Young June ...... MoB1.17 Stachniss, Cyrill ...... MoD2.20 Shirafuji, Shouhei ...... WeB1.4 ...... WeA3.10 Shiratori, Takaaki ...... MoD2.4 Starek, Joseph ...... TuB2.15 Shkurti, Florian ...... TuB3.3 Stavdahl, Øyvind ...... MoA3.6 ...... TuD3.8 ...... MoA3.10 Shomin, Michael ...... WeA2.7 ...... MoC3.7 Siciliano, Bruno ...... TuB2.3 Stegagno, Paolo ...... MoA3.14 ...... WeD2.9 Stegenga, Jan ...... TuE3.15 Sie, Astrini ...... TuB1.10 Steil, Jochen J...... MoB2.9 Siegwart, Roland ...... MoB1.10 ...... MoD2.12 ...... TuC3.18 ...... WeC1.19 ...... TuD3.11 Stein, Procópio ...... TuD3.16 Sigalas, Markos ...... WeB2.16 Steinbuch, Maarten ...... WeB3.8 Sigaras, Alexandros ...... MoD1.14 Stephan, James ...... WeA3.4 Simaan, Nabil ...... ThFD6.1 Stiefelhagen, Rainer ...... MoC2.12 Simeon, Thierry ...... MoA2.14 Stiffler, Nicholas ...... TuA2.10 ...... TuD2.15 Stiller, Christoph ...... SuFD12. Simpson, Richard ...... MoA2.17 1 Singh, Arun Kumar ...... WeB3.7 Stilli, Agostino ...... TuC1.16 Singh, Sanjiv ...... WeD2.4 Stilman, Mike ...... TuC1.20 ...... WeD3.10 ...... TuD2.6 Singh, Surya ...... TuC2.15 ...... WeA2.5 Sinisterra, Armando J...... TuB3.11 ...... WeA2.18 Sirouspour, Shahin ...... ThFD8.1 Stockmann, Ferdinand ...... WeA2.9 Sitti, Metin ...... WeC3.16 Stone, Peter ...... MoA3.19 Sitti, Metin ...... ThFD3.1 Stork, Johannes Andreas ...... TuA1.8 Skidmore, Jeffrey ...... TuB1.17 Stoy, Kasper ...... SuFD6.1 Skubic, Marjorie ...... MoD2.6 Stramigioli, Stefano ...... TuC1.1 Slavnic, Sinisa ...... TuB1.18 ...... TuE3.11 Smart, William ...... MoB3.8 ...... TuE3.15 Smith, Ryan N...... TuB3.2 ...... WeB1.6 Smoljkic, Gabrijel ...... MoC3.2 Stria, Jan ...... MoA1.11 Smutny, Vladimir ...... MoA1.11 Strimel, Grant ...... TuD2.9 Sofge, Donald ...... WeA3.15 Stroffolino, Anthony ...... TuA3.3 Sofia, Giuseppe ...... WeC2.13 Strub, Claudius ...... TuB2.12 Sohel, Ferdous ...... WeD3.2 Stulp, Freek ...... MoD2.13 Sohn, Kiwon ...... MoC2.9 Stump, Ethan ...... TuA3.19 Sokolsky, Oleg ...... WeA2.15 Su, Baiquan ...... TuB1.11 Soltani Naveh, Kianoosh ...... TuC2.15 Su, Hai-Jun ...... TuB3.12 Soltani-Zarrin, Rana ...... TuC1.4 Suay, Halit Bener ...... WeA3.6 Somani, Nikhil ...... MoB3.12 Subirats, Peggy ...... WeB3.17 Sommer, Hannes ...... TuD3.11 Subramanian, Giri Prashanth ...... WeA3.18 Somorjai, Gergo ...... WeA3.20 Sucar, Luis Enrique ...... WeB3.15 Song, Bo ...... MoC1.11 Sudano, Angelo ...... TuD1.7 Song, Dezhen ...... MoC2.21 Sugano, Shigeki ...... TuA3.12 ...... TuD3 C Sugihara, Tomomichi ...... MoB1.18 Song, Hee-Chan ...... WeC2.20 ...... MoC2.7 Song, Jae-Bok ...... WeC2.20 ...... TuC1.10 Song, Joshua ...... TuC2.15 Sugimoto, Kenji ...... MoB2.14 Song, Sukho ...... WeC3.16 Sugimoto, Shigeki ...... TuC3.16 Song, Woneui ...... WeD1.10 Sugita, Naohiko ...... MoD1.21 Song, Yun Seong ...... TuD1.2 ...... TuB1.6 Song, Zhuoyuan ...... TuB3.8 ...... WeA1.10 Songtong, Sira ...... WeC1.13 Sugiyama, Osamu ...... TuA3.9 Sora, Shigeo ...... WeA1.10 Suh, Chansu ...... TuD1.2 Sorrentino, Francesco ...... MoA3.18 Suh, Il Hong ...... TuD3.17 Sovizi, Javad ...... TuD1.14 ...... TuD3.18 Spalanzani, Anne ...... SuFD10. Suh, Jung Seok ...... TuA3.15 1 ...... WeD3.17 ...... TuC2.19 Sukhatme, Gaurav ...... SuAM2.1 ...... TuD3.16 ...... WeA2.8
259 Sukkarieh, Salah ...... WeD2.11 Tapia, Lydia ...... SuFD5.1 Sukthankar, Gita ...... WeC1.16 Tapus, Adriana ...... MoD3.9 Sullivan, Timothy ...... MoC2.4 Tar, József Kázmér ...... MoA1.20 Sumi, Yasushi ...... TuD3.15 Tarabini, Oscar ...... WeB2.15 Sun, Dong ...... TuB1.5 Tarcai, Norbert ...... WeA3.20 ...... WeC3.19 Tartaglia, Vincenzo ...... MoD1.11 ...... WeD1 C Tassa, Yuval ...... TuA1.10 Sun, Liang ...... MoC3.20 Tavakoli, Mahmoud ...... MoA3.3 Sun, Wen ...... TuA2.9 ...... TuA1.6 Sun, Yiling ...... WeD1.10 ...... TuD1.15 Sun, Yu ...... WeA1.6 Taylor, Camillo Jose ...... MoA2.4 Sun, Yu ...... WeC2.11 Taylor, Russell H...... MoD1.13 Sun, Yuandong ...... WeC2.4 ...... WeA1 C Sung, Jaeyong ...... TuD2.12 ...... WeA1.8 SunSpiral, Vytas ...... TuB2.20 Taylor, Vaughn ...... MoC1.20 Suppa, Michael ...... TuA2.19 Teare, Julian ...... MoD1.19 Suzumori, Koichi ...... TuD1.4 Tee, Keng Peng ...... WeB2.14 Svec, Petr ...... TuB3.11 ten Pas, Andreas ...... WeB1.19 Swaney, Philip J...... MoD1.12 Tenorth, Moritz ...... SuFD4.1 Sweet, Larry ...... WeA3.21 Teo, Chee Leong ...... TuB1.21 Sweet, Robert ...... TuB1.2 Teramae, Tatsuya ...... WeA1.17 Sycara, Katia ...... MoA3.20 Tesch, Matthew ...... MoC3.9 ...... MoC3.8 ...... TuB2.19 Symington, Andrew Colquhoun ...... TuE3.3 Tezuka, Taiki ...... TuA3.8 Szedmak, Sandor ...... MoB2.16 Thakker, Rohan ...... MoA3.8 Szewczyk, Jérôme ...... WeC1.11 Thatte, Nitish ...... TuB1.15 Szörényi, Tamás ...... WeA3.20 Thippur, Akshaya ...... TuD2.3 T Thomas, Gray ...... WeD1.19 Ta, Duy-Nguyen ...... WeC3.6 Thomas, Jesse ...... TuB3.2 Tachibana, Miyako ...... TuA1.3 Thomas, Shawna ...... WeA2.17 Tadokoro, Satoshi ...... TuA3 C Thomaz, Andrea Lockerd ...... TuE2.10 ...... TuA3.5 Thorel, Sylvain ...... TuE1.9 ...... TuA3.6 Thrun, Sebastian ...... MoB1.9 Taghavi Namin, Sarah ...... WeD3.5 Tian, Bo ...... TuC3.2 Tagliamonte, Nevio Luigi ...... TuD1.7 Tiemerding, Tobias ...... MoC1.17 Takagi, Kiyoshi ...... TuB1.4 Tikhanoff, Vadim ...... MoD3.14 Takahashi, Takayuki ...... TuC1.7 Timmis, Jon ...... WeA2.19 Takaki, Takeshi ...... MoC1.6 Todorov, Emanuel ...... TuA1.10 Takamatsu, Jun ...... TuE2.2 Tokekar, Pratap ...... TuD3.6 Takanishi, Atsuo ...... TuA2.15 Tokuda, Isao ...... WeD2.13 ...... TuC2.16 Tolio, Tullio A. M...... WeC2.16 Takemoto, Ayumi ...... MoC1.6 Tolley, Michael Thomas ...... MoB2.7 Takemura, Kentaro ...... TuE2.2 Tombari, Federico ...... WeD3.3 Takeuchi, Eijiro ...... TuA3.5 Tomé, Ana Maria ...... TuB2.17 ...... TuA3.6 Tomic, Teodor ...... WeB3.11 Takeuchi, Masaru ...... MoC1.2 Tomizuka, Masayoshi ...... MoB1.13 ...... MoC1.3 ...... MoD2.9 Takhmar, Amir ...... MoD1.15 ...... MoD2.10 Talamadupula, Kartik ...... TuD2.10 ...... MoD2.21 Talasaz, Ali ...... MoD1.15 ...... WeB3.10 TalebiFard, Pouria ...... WeA1.20 Tomlin, Claire ...... WeB3.6 Talnishnikh, Elena ...... WeA3.14 Tonapi, Manas ...... TuD1.13 Tamadazte, Brahim ...... MoB3.13 Tong, Liu Zhu ...... TuB1.21 Tamamoto, Takumi ...... MoA1.4 Toohey, Lachlan ...... WeC3.10 Tamassia, Marco ...... MoC2.18 Torras, Carme ...... MoD2.14 Tan, Boon Hwa ...... MoB1.20 Torres, Fernando ...... MoA1.15 Tan, Jindong ...... MoD1.16 Torres-Torriti, Miguel ...... TuA1.9 Tan, Xiaobo ...... TuD1.10 Toussaint, Marc ...... MoA1.9 Tanaka, Daisuke ...... MoB2.14 ...... MoA1.18 Tanaka, Hideyuki ...... TuD3.15 ...... MoB2.15 Tanaka, Kanji ...... MoA2.2 Traeger, Mattias Felix ...... MoD1.20 Tanaka, Nobuyuki ...... MoC1.7 Trahanias, Panos ...... WeB2.16 Tanaka, Shinichi ...... WeA1.10 Travers, Matthew ...... TuC1.11 Tanaka, Yasufumi ...... TuB2.13 ...... TuC1.17 Tang, Huajin ...... MoB1.20 ...... WeA1.3 ...... TuC3.2 ...... WeA2.10 Tang, Junyue ...... TuB3.20 Trehard, Guillaume ...... TuC3.10 Tang, Lewei ...... WeB1.2 Trentini, Michael ...... TuA3.18 Tang, Xiaoqiang ...... WeB1.2 Tresch, Matthew ...... TuB2.5 Tani, Jun ...... MoB1.20 ...... WeA1.19 Tani, Tohru ...... TuE1.4 Trevor, Alexander J B ...... MoC2.15 Taniguchi, Tadahiro ...... MoB2.13 Triantafyllou, Michael ...... MoC3.10 Tanner, Herbert G...... TuD2.21 Trinkle, Jeff ...... TuE1.12 Tanzmeister, Georg ...... MoB3.2 Trojanek, Piotr ...... MoD3.5
260 Troni, Giancarlo ...... MoB1.8 Veloso, Manuela ...... TuD2.1 Trovato, Gabriele ...... TuC2.16 ...... TuD2.9 Tsagarakis, Nikolaos ...... SuFD8.1 ...... TuE2.3 ...... MoC2.5 Vendittelli, Marilena ...... WeB2.11 ...... MoD1.11 Venture, Gentiane ...... MoC2.2 ...... TuC1.6 Verl, Alexander ...... WeC2.12 Tsai, Chi-Shen ...... WeB3.10 Veruggio, Gianmarco ...... WeC3.7 Tsai, Grace ...... TuA2.16 Vian, John ...... TuE3.4 Tsai, Yun-Hsuan ...... MoB1.19 Viana de Oliveira e Costa, Mateus ...... MoB2.4 Tsakiris, Dimitris ...... MoA3.7 Vicencio, Kevin ...... TuD2.14 Tschakarow, Roko ...... TuB1.18 Vicentini, Federico ...... SuFD3.1 Tseng, Ting-En ...... WeB2.12 Vicsek, Tamas ...... WeA3.20 Tsubouchi, Takashi ...... WeD3.21 Vidal-Calleja, Teresa A...... TuA2.5 Tsuji, Tokuo ...... TuC1.12 ...... TuD3.13 Tsuji, Toshiaki ...... WeA1.12 Viegas, Carlos ...... TuD1.15 Tsukihara, Hiroyuki ...... TuB1.6 Vieira, Marcos ...... WeA3.2 Tumer, Kagan ...... TuB2.20 Vijayakumar, Sethu ...... TuC3.15 Tumova, Jana ...... MoD3 C Villani, Luigi ...... TuB2.3 ...... MoD3.7 Villarroel, José Luis ...... WeC3.9 Tunstel, Edward ...... TuA3.4 Vincze, Markus ...... TuC2.13 Turan, Bilal ...... WeD1.5 ...... WeD3.16 Turnwald, Annemarie ...... MoB3.7 Virágh, Csaba ...... WeA3.20 Tüttemann, Markus ...... TuB1.18 Virk, Gurvinder Singh ...... SuFD3.1 Tweddle, Brent Edward ...... TuB3.14 Visell, Yon ...... ThFD10. Tzeng, Eric ...... WeC2.3 1 U Viswanathan, Anirudh ...... MoA2.10 U, Ningga ...... WeD1.5 Vitiello, Valentina ...... MoD1.19 Uchida, Satoshi ...... MoD1.21 Vogler, Hannes ...... WeB1.14 Ude, Ales ...... TuA2.11 Vogtmann, Dana ...... MoC1.4 Ueda, Jun ...... TuB2.8 Voigt, Thorsten ...... MoA2.6 ...... WeA2.3 von Stryk, Oskar ...... WeD2.15 Ugur, Emre ...... MoB2.16 Vossiek, Martin ...... MoA2.6 Ugurlu, Barkan ...... WeA1.17 Voyles, Richard ...... MoD3.17 Upcroft, Ben ...... WeC3.2 Vysotska, Olga ...... MoD2.20 Urai, Kenji ...... MoB2.21 W Uras, Tansel ...... MoA2.16 Wada, Takahiro ...... TuB1.16 Urbanek, Holger ...... WeA2.13 Wagle, Neeti ...... MoC3.19 Ure, Nazim Kemal ...... TuE3.4 Wagner, Libor ...... MoA1.11 Uto, Soichiro ...... TuC1.12 Wagner, René ...... TuC3.9 V Wahrmann, Daniel ...... WeB3.9 Vadakedathu, Larry ...... MoC2.8 Wakisaka, Naoki ...... TuC1.10 Vaillant, Joris ...... MoC2.3 Walas, Krzysztof, Tadeusz ...... WeD3.14 ...... WeB2.5 Walker, Ian ...... MoA3.11 Valbuena, Luis ...... MoA3.18 ...... TuD1.13 Valdivia y Alvarado, Pablo ...... MoC3.10 ...... WeB2.9 Valigi, Paolo ...... TuE2.9 Walker, Phillip ...... MoC3.8 Vallicrosa, Guillem ...... TuB3.6 Wan, Lei ...... MoA1.17 ...... TuB3.7 Wang, Chao ...... WeD3.9 Valls Miro, Jaime ...... TuA2.5 Wang, Charlie C.L...... WeB2.20 ...... TuD3.13 Wang, Cong ...... MoD2.21 van de Molengraft, Marinus Jacobus Gerardus ...... WeB3.8 Wang, Ji-Hyeun ...... MoB1.17 van der Smagt, Patrick ...... WeA2.13 Wang, Jianhua ...... WeA1.18 van der Stappen, Frank ...... WeC2.15 Wang, Jiaole ...... MoB1.3 Van Ham, Ronald ...... TuD1.6 Wang, Kai ...... MoB3.17 Van Why, Johnathan ...... TuC2.6 Wang, Qiaosong ...... MoC2.9 Vander Hoff, Evan ...... MoD2.15 Wang, Wei-Wen ...... WeA1.14 Vander Poorten, Emmanuel B ...... MoC3.2 Wang, Xiaochen ...... MoB2.2 Vander Sloten, Jos ...... MoC3.2 Wang, Xun ...... WeD2.5 Vanderborght, Bram ...... SuFD8.1 Wang, Yan ...... MoC2.19 ...... TuD1.6 Wang, Yue ...... MoD1.7 Várkonyi, Teréz Anna ...... MoA1.20 Wang, Yue ...... WeB2.9 Vásárhelyi, Gábor ...... WeA3.20 Wang, Zhan ...... TuA2.17 Vasilopoulos, Vasileios ...... WeD2.12 ...... WeD2.7 Vasquez, Dizan ...... MoD2.3 Wani, Umar ...... MoB2.8 Vasquez-Gomez, J. Irving ...... WeB3.15 Waslander, Steven Lake ...... WeD2.7 Vasseur, Pascal ...... MoA2.5 Watanabe, Atsushi ...... TuE2.4 ...... MoB1.7 Wawerla, Jens ...... TuA2.4 ...... WeB3.13 Weber, Xavier ...... TuA1.20 ...... WeB3.17 Webster III, Robert James ...... MoD1.12 Vaughan, Richard ...... TuA2.4 Wehner, Michael ...... MoB2.7 ...... WeA3 C Wei, Hongchuan ...... MoA1.13 Vega, Victor ...... TuE3.8 ...... MoA1.16 Vejdani, Hamid Reza ...... TuC2.10 Weimer, James ...... WeA2.15 Velagapudi, Prasanna ...... WeC3.17 Weisz, Jonathan ...... TuB2.11
261 Wen, John ...... MoB3.19 Yamanashi, Yuki ...... TuD1.11 Wensing, Patrick ...... WeB2.2 Yamane, Katsu ...... MoD2.4 Wettels, Nicholas ...... TuE2 C ...... WeA3.12 ...... WeB3.21 Yamate, Soichiro ...... TuA1.3 Weyn, Maarten ...... TuA2.13 Yamato, Masayuki ...... MoC1.7 White, Connor ...... TuE3.16 ...... WeD1.9 Whitesides, George ...... MoB2.7 Yamauchi, Genki ...... TuA3.13 Whitney, David ...... TuD3.8 Yamawaki, Tasuku ...... TuC1.14 Whitney, John ...... TuD1.5 Yamazaki, Kimitoshi ...... TuD3.14 Wieber, Pierre-Brice ...... MoB3.21 Yamokoski, John ...... MoD3.13 Wightman, Brian ...... MoD3.13 Yan, Chengping ...... WeD2.5 Wiktor, Adam ...... MoC3.17 Yan, Rui ...... MoB1.20 Williams, Ryan ...... SuAM2.1 ...... WeB2.14 ...... WeA3.7 Yang, Guang-Zhong ...... MoD1.19 Williams, Stefan Bernard ...... WeC3.10 ...... TuB1.8 Willig, Andrew ...... WeC3.17 ...... WeA1.5 Wiltsie, Nicholas ...... TuB3.12 Yang, Jie ...... TuB1.5 Wimboeck, Thomas ...... TuA1.4 Yang, Jie ...... WeB2.13 Winek, Michael ...... TuB1.10 Yang, Jing ...... TuD2.17 Winfield, Alan ...... WeA2.19 Yang, Seung Ung ...... TuA3.15 Wisse, Martijn ...... MoA2.19 ...... WeD3.17 ...... TuC1.13 Yang, Sungwook ...... MoD1.17 Wittmann, Robert ...... TuC2.11 Yangali, Teodoro Andree ...... MoB2.4 ...... WeB3.9 Yashima, Masahito ...... TuC1.14 Woern, Heinz ...... MoA1.3 Yasuda, Takashi ...... WeD1.7 Wojke, Nicolai ...... WeB2.18 Yebes, José Javier ...... TuD3.9 Wolcott, Ryan ...... MoA2.8 Yehoshua, Roi ...... TuD2.20 Wolf, Daniel ...... TuC2.13 Yi, Byung-Ju ...... WeC3.8 Wolfe, Kevin ...... TuA3.4 Yi, Jingang ...... TuA3.16 Wolfe, Stephen ...... MoA3.4 ...... TuE2.11 Wolff, Eric ...... MoD3.2 ...... WeB2.19 Wolfslag, Wouter ...... MoA2.19 Yi, Seung-Joon ...... MoC2.8 Wollherr, Dirk ...... MoB3.2 Yim, Mark ...... TuA3.3 ...... MoB3.7 ...... TuD1.12 ...... WeB3.3 Yokoi, Kazuhito ...... MoC2.1 Wong, Weng-Keen ...... TuE2.14 Yol, Aurélien ...... TuE3.10 Wood, Robert ...... MoB2.7 Yoshida, Eiichi ...... MoC2.2 ...... TuD1.17 ...... WeB2.5 ...... TuE3.5 ...... ThFD12...... WeB1.21 1 ...... WeD1.1 Yoshida, Kazuya ...... TuA3.13 Wörgötter, Florentin ...... TuB2.12 Yoshiike, Takahide ...... MoA1.21 Wörtche, Heinrich ...... TuE3.15 Yoshinaka, Kiyoshi ...... TuB1.6 ...... WeA3.14 Youakim, Kareem ...... WeD1.8 Wu, Albert ...... TuC2.9 Yousif, Khalid ...... TuC3.4 Wu, Liang ...... MoA2.3 Youssefi, Shahbaz ...... TuA1.11 Wu, Liao ...... MoB1.3 Yu, Jingjin ...... MoA3.13 Wuensche, Hans J ...... TuC3.14 Yu, Kaiyan ...... WeB2.19 ...... WeA2.6 Yu, Shengwei ...... WeA3.11 Wurdemann, Helge Arne ...... TuC1.16 Yuan, Miaolong ...... TuC3.2 Wyatt, Jeremy ...... WeC2.6 Yuan, Wenzhen ...... WeB1.19 X Yuan, Yixuan ...... WeD3.15 Xi, Ning ...... MoC1.11 Yue, C. Patrick ...... MoA2.3 ...... TuA1.7 Yue, Tao ...... MoC1.3 Xi, Weitao ...... TuE1.15 Yuen, Michelle ...... MoB2.10 Xi, Zhonghua ...... WeB3.4 Yun, Chang-ho ...... MoB2.4 Xiao, Jing ...... MoD1 C Yun, Youngmok ...... MoB2.20 Xiao, Jizhong ...... MoA3.17 Yusa, Akiko ...... WeD1.10 Xie, William ...... MoC1.20 Yuta, Shinichi ...... TuA3.13 Xing, Dengpeng ...... MoB3.16 Z Xinjilefu, X ...... MoC2.11 Zamzuri, Hairi ...... WeD2.2 Xu, Danfei ...... TuE3.13 Zanchettin, Andrea Maria ...... WeB3.2 Xu, De ...... MoB3.16 ...... ThFD4.1 Xu, Junchao ...... TuC2.17 Zanne, Philippe ...... WeA1.9 Xu, Yangsheng ...... MoA1.6 Zapolsky, Samuel ...... TuE1.16 ...... WeC2.4 Zarrouk, David ...... TuD2.21 Xu, Yiming ...... TuE1.3 Zastrow, Tyson ...... TuC2.15 Xu, Zhe ...... TuC2.14 Zavlanos, Michael M...... MoA3.15 Xue, Jianru ...... WeD3.8 Zefran, Milos ...... WeC1.6 Y Zeghloul, Said ...... TuA1.16 Yalla, Ganesh ...... TuD3.19 Zelek, John S...... MoB3.20 Yamada, Atsushi ...... TuE1.4 Zell, Andreas ...... WeB3.18 Yamamoto, Akina ...... TuD1.4 ...... WeC3.11 Yamamoto, Ko ...... TuC2.4 Zemiti, Nabil ...... MoD1.4
262 Zevallos, Nico ...... MoC3.6 Zha, Hongbin ...... WeD3.9 Zhang, Daibing ...... WeD2.5 Zhang, Hong ...... TuC3.21 Zhang, Ji ...... WeD3.10 Zhang, Jianwei ...... TuB2 C ...... TuC1.18 ...... WeA1.6 ...... WeD2.5 Zhang, Lin ...... WeA1.5 Zhang, Peng ...... WeA1.6 Zhang, Qiwen ...... TuD3.8 Zhang, Wenlong ...... MoD2.9 Zhang, Yanliang ...... SuPM1.1 Zhang, Yizhai ...... TuE2.11 ...... WeB2.19 Zhang, Yu ...... WeD2.5 Zhang, Zijian ...... WeD1.18 Zhao, Boxin ...... WeD2.5 Zhao, Huijing ...... WeD3.9 Zhao, Jianguo ...... MoC1.11 Zhao, Yu ...... MoD2.21 Zhao, Zhe ...... MoB3.10 Zheng, Gang ...... WeA2.4 Zheng, Nanning ...... WeD3.8 Zheng, Ronghao ...... WeC3.19 Zheng, Yang ...... WeB2.20 Zhou, Dianle ...... WeD2.5 Zhou, Yu ...... MoC1.20 Zhu, Pingping ...... MoA1.13 ...... MoA1.16 Zibner, Stephan Klaus Ulrich ...... MoB2.19 Zillich, Michael ...... ThFD5.1 Zimmermann, Soeren ...... MoC1.17 Zinn, Michael ...... WeC1.5 Zisimatos, Agisilaos ...... TuE1.7 Zöllner, Johann Marius ...... TuE2.8 ...... WeD2.18 Zug, Sebastian ...... MoC3.12 Zurek, Sebastian ...... WeC2.6 Ž Žlajpah, Leon ...... TuA2.11
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