IEEE ICRA 2017 Conference Digest Day 2

ROGRAM P Day 2 Wednesday, 31 May

May 29-June 3, 2017 ・Singapore

IEEE International Conference on Robotics and Automation Session WeA1 Rm. 4011 Wednesday, May 31, 2017, 09:30–10:45 Kinematics and Dynamics Chair Hiromi Mochiyama, University of Tsukuba Co-Chair Yukio Takeda, Tokyo Institute of Technology

09:30–09:35 WeA1.1 09:35–09:40 WeA1.2

Inverse Kinematics with Strict Nonholonomic On Orientation Control of Constraints on Mobile Manipulator Functional Redundant Robots KangKyu Lee, Jaesung Oh, Okkee Sim and Hyoin Bae Department of Mechanical Engineering, KAIST, Republic of Korea Leon Žlajpah Dept. of Automation, Biocybernetics and Robotics Jun-Ho Oh Jožef Stefan Institute, Slovenia Department of Mechanical Engineering, KAIST, Republic of Korea

• It is possible to violate the nonholonomic • We present an approach for the orientation constraint on mobility by distorting the related functional redundancy resolution, Jacobian which is based on the task space rotation. • Application of strict nonholonomic constraints • A time-variant task frame is defined, where the can address the issue of Jacobian distortion functional redundancy is represented as one • A proposition to correct for slip error in order to or more rows of the Jacobian matrix. increase the speed of convergence. The • In the proposed control algorithms the non- Two-arm KUKA LWR avoiding velocity vectors are then adjusted to controlled rotations are excluded from the task robot system performing account for this error space and are used for the self-motion. „buzz wire“ task

09:40–09:45 WeA1.3 09:45–09:50 WeA1.4

Recursive Second-Order Inverse Dynamics Multi-Arm Snake-Like Robot for Serial Manipulators Andreas Mueller Yannick S. Krieger, Daniel B. Roppenecker, Ismail Kuru Institute of Robotics, Johannes Kepler University and Tim C. Lueth Linz, Austria Institute of micro technology and medical device technology (MiMed) of the Technische Universität München, Munich, Germany

• Higher-order derivatives of inverse dynamics solutions needed for flatness-based control of • Selective laser sintered manipulator serial elastic manipulators and optimal control system for gastroscopic interventions with a purely mechanical control concept. • Lie group recursive O(n) algorithms for inverse dynamics are compact and coordinate invariant • Monolithical snake-like overtube structure for standard endoscopes with two • Here two Lie group O(n) algorithms are manipulator arms (each 4 DoF). presented for first and second derivatives • Evaluation of the system in a lab • The first in terms of body-fixed and the second experiment and further clinical evaluation Manipulator system with a purely one in terms of hybrid representation of twists. in a clinical trial. mechanical control concept • Kinematics in terms of intrinsic geometric Geom. parameters parameters instead of DH-parameters for example

09:50–09:55 WeA1.5 09:55–10:00 WeA1.6

Position Analysis of Spherical Linkages via O(log n) Algorithm for Forward Kinematics Angle-Bound Smoothing under Asynchronous Sensory Input Josep M. Porta and Federico Thomas Ryo Wakatabe*’**, Yasuo Kuniyoshi** and Gordon Cheng* Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Spain * The Institute for Cognitive Systems, The Technical Univ. of Munich, Germany ** Department of Mechano-Informatics, The Univ. of Tokyo, Japan • This paper generalizes bound-smoothing to deal with points on a sphere. • The angular distance between points on a • Conventional FK assumes synchrony of all sphere are lengths of arcs of great circles. sensory information, which is disadvantage when high DoF. • The proposed method is based on constraints involving sets of four points • Preferable for hardware systems, less derived from Gram determinants. processors idleness and real-time computation of hyper-redundant robots • The position analysis of two spherical mechanisms is presented to validate the • Real-time algorithm. An example of how AFK approach. The position of points on a sphere • Computation time with over 50000 links takes works. determines the forward kinematics less than 35 us for 1 query. of a spherical manipulator.

2017 IEEE International Conference on Robotics and Automation Session WeA1 Rm. 4011 Wednesday, May 31, 2017, 09:30–10:45 Kinematics and Dynamics Chair Hiromi Mochiyama, University of Tsukuba Co-Chair Yukio Takeda, Tokyo Institute of Technology

10:00–10:05 WeA1.7 10:05–10:10 WeA1.8

Real-time Shape Estimation of Kirchhoff Parallel Dynamics Computation using Elastic Rod Based on Force/Torque Sensor Prefix Sum Operations

Ryo Takano and Hiromi Mochiyama Yajue Yang1, Yuanqing Wu2 and Jia Pan1 University of Tsukuba, Japan 1 Department of Mechanical and Biomedical Engineering, Naoyuki Takesue City University of Hong Kong, China Tokyo Metropolitan University, Japan 2 Department of Industrial Engineering, University of Bologna, Italy • A real-time spatial shape estimation method for an elastic rod is proposed with • A new parallel framework for fast computation using a single six-axis force/torque sensor of dynamics of articulated robots is proposed. placed near one end of elastic rod. • The parallel prefix sum algorithm is applied for • The proposed method is based on a parallelizing linear recurrences within the discretized Kirchhoff elastic rod model dynamics computation. and the real-time computation can be • Several parallel and sequential-parallel hybrid achieved stably because its dynamics algorithms are implemented. Fig. 1: Computation time computational time is linear in the partition An actual ‘S’-shape of an elastic strip is calculated based on the • The experiments performances are compared comparison between serial number for the discretization. force/torque sensor information and analyzed. and parallel inverse dynamics • Experimental results show the validity of in real-time and drawn on a implementations the proposed method. display.

2017 IEEE International Conference on Robotics and Automation Session WeA2 Rm. 4111 Wednesday, May 31, 2017, 09:30–10:45 Mapping 1 Chair José Neira, Universidad de Zaragoza Co-Chair Fabio Ramos, University of Sydney

09:30–09:35 WeA2.1 09:35–09:40 WeA2.2

Dense Monocular Reconstruction using Surface Learning Highly Dynamic Environments Normals with Stochastic Variational Inference Ransalu Senanayake and Fabio Ramos Chamara Saroj Weerasekera, Yasir Latif, Ravi Garg, Ian Reid The University of Sydney, Australia School of Computer Science, University of Adelaide, Australia Simon O’Callaghan Data61/CSIRO, Australia • We propose a surface normal-based inverse- depth regularizer for efficient dense monocular • Learning the long-term occupancy of an environment mapping is important for safer and reliable path planning. • Surface normals are predicted from a deep • The proposed method can build such long-term occupancy maps in dynamic environments using a CNN, capturing high and low level image stream of laser data. information • We make use of “Big Data Gaussian Process” models • The proposed regularizer helps determine a for building continuous occupancy maps by more accurate solution to a multi-view considering spatiotemporal relationships. • The model learns all key parameters itself and hence photometric cost Dense reconstruction of an the accuracy does not rely on heuristic parameter office desk obtained using • Demonstrates better performance than choices. Top: the world the normal-based prior standard inverse-depth smoothness • It does not require any underlying motionBottom: modelOccupancy or map built over time regularization in a variety of indoor scenes object trackers.

09:40–09:45 WeA2.3 09:45–09:50 WeA2.4

Robust Stereo Matching with Surface Normal Prediction Robot mapping and localisation in metal water pipes using hydrophone induced vibration and Shuangli Zhang1, Weijian Xie1, Guofeng Zhang1, Hujun Bao1, Michael Kaess2 1State Key Lab of CAD&CG, Zhejiang University, China map alignment by dynamic time warping 2Robotics Institute, Carnegie Mellon University, USA Ke Ma, Michele M. Schirru, Ali Hassan Zahraee, Rob Dwyer- Joyce, Joby Boxall, Tony J. Dodd, Richard Collins and • Significantly improve stereo matching in Sean R. Anderson textureless, occluded and reflective regions by University of Sheffield, United Kingdom combining the predicted surface normal with deep learning. Input Output • The aim is to develop mapping and level level • Propose a reliable disparity confidence localization for metal water pipes. estimation method by combining LRD-based

and plane-fitting based confidence • But… water pipes are relatively featureless Water measurements. and lack landmarks for navigation. Water Butt level • Detect and fuse edges with multiple cues to • Our novel approach is to excite pipe vibration Hydrophone locate discontinuity boundaries. using a hydrophone to create a map. Concrete • Convert surface normal to disparity by solving a • We align multiple maps using dynamic time sparse linear system incorporating both normal warping and localize by EKF or particle filter. and depth constraints. Steel Pipe Left image Disparity map

09:50–09:55 WeA2.5 09:55–10:00 WeA2.6

Incremental Contour-Based Topological Semantic Classification by Reasoning on the Segmentation for Robot Exploration Whole Structure of Buildings using Statistical Relational Learning Techniques L. Fermin-Leon, J. Neira and J. A. Castellanos Matteo Luperto, Alessandro Riva, and Francesco Amigoni DIIS, University of Zaragoza, Spain Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy

• Alternative approach: Contour-Based • Semantic classification of places is usually Segmentation using Dual Decomposition. based on local features • Tuning of a single parameter. • We propose a statistical relational learning • Incremental version reuses the last approach to reason on the global structure of segmentation to produce faster and equally buildings accurate results. • We use the kLog framework to perform • Tests demonstrate that the incremental version semantic classification tasks Graphicalized outperforms the state of the art. • Experiments include place (room) Entity/Relation Example classification, building classification, and representation of a simple simulated environment classification tasks environment

10:00–10:05 WeA2.7 10:05–10:10 WeA2.8

SkiMap: An Efficient Mapping Framework for Multirobot Online Construction of Robot Navigation Communication Maps Jacopo Banfi1, Alberto Quattrini Li2, Nicola Basilico3, Ioannis Rekleitis2, Francesco Amigoni1 Daniele De Gregorio, Luigi Di Stefano 1 DISI, University of Bologna, Italy DEIB, Politecnico di Milano, Italy 2Dept. of Computer Science and Engineering, University of South Carolina, USA 3Dept. of Computer Science, University of Milan, Italy • Novel mapping framework for Robot • Knowledge about possibility of Navigation with multi-level querying system: establishing wireless communication links 2D, 2.5D and 3D between arbitrary pairs of locations, a.k.a. • Suitable for large scale environments and for communication map, is fundamental for any kind of integrable data (RGB, Occupancy, reliable multirobot systems SDF) • Problem: efficiently building a • Based on SkipList data structure to ensure communication map of an environment O(log n) for random voxel access • Our solution: model communication maps with Gaussian Processes and use leader- • Radius Search is an intrinsic feature of the 3D View of Data architecture that outperforms Octree Structure follower strategies for deciding where to sample Turtlebots building communication maps

2017 IEEE International Conference on Robotics and Automation Session WeA3 Rm. 4311/4312 Wednesday, May 31, 2017, 09:30–10:45 Visual Learning Chair Hao Zhang, Colorado School of Mines Co-Chair Tamim Asfour, Karlsruhe Institute of Technology (KIT)

09:30–09:35 WeA3.1 09:35–09:40 WeA3.2

Sequence-based Multimodal Apprenticeship Minimum Uncertainty Latent Variable Models for Learning For Robot Perception and Decision Making Robot Recognition of Sequential Human Activities 1 2 3 1 Fei Han1 and Xue Yang1 and Yu Zhang2 and Hao Zhang1 Fei Han and Christopher Reardon and Lynne E. Parker and Hao Zhang 1. Computer Science Department, Colorado School of Mines, USA 1. Computer Science Dept., Colorado School of Mines, USA 2. US Army Research Laboratory, USA 2. Computer Science and Engineering Dept., Arizona State University, USA 3. EECS Department, University of Tennessee, USA • Integration of real-time • A new approach for multisensory robot perception sequential human activity and decision making to learn recognition based on tasks from humans in Minimum Uncertainty Hidden challenging environments Conditional Random Fields • A novel representation of world • A novel regularization states in reinforcement learning capturing the uncertainty in modeling latent underlying temporal • Capability to address perceptual Overview of the SMAL method to patterns An example of utilizing HCRFs to model achieve robot apprenticeship learning aliasing by simultaneously • Theoretical proof that the a sequential “tennis-serve” activity fusing temporal information and formulated objective function multimodal data has a closed form

09:40–09:45 WeA3.3 09:45–09:50 WeA3.4

Learning a Deep Network with Spherical Part Model for 3D Hand Pose Estimation Tzu-Yang Chen, Pai-Wen Ting, Min-Yu Wu, Li-Chen Fu Visual Stability Prediction for Robotic Manipulation Department of Computer Science and Information Engineering, National Taiwan University, Taiwan Wenbin Li1, Ales Leonardis2, Mario Fritz1 Max Planck Institute for Informatics, Germany1 School of Computer Science, University of Birmingham, UK2 • Present a novel 3D hand pose estimation system based on depth images • End-to-end learning of intuitive physics for • Propose a deep convolutional neural stability prediction. network framework that integrates hand • Accompanied human subject study showing detection and pose estimation our model achieves comparable or even better • Design a Spherical part model (SPM) as results. physical constraints to improve the • Investigate the discriminative image regions training model from the model for intuitive interpretation. • Demonstrate outstanding results of our • Integrate visual stability prediction into experiments in three challenging datasets manipulation. Pipeline of our approach.

09:50–09:55 WeA3.5 09:55–10:00 WeA3.6

Semantics-aware Visual Localization Simultaneous Feature and Body-Part Learning for under Challenging Perceptual Conditions Real-Time Robot Awareness of Human Behaviors Fei Han1 and Xue Yang1 and Christopher Reardon2 Tayyab Naseer, Gabriel Oliveira, and Yu Zhang3 and Hao Zhang1 Thomas Brox and Wolfram Burgard 1. Computer Science Dept., Colorado School of Mines, USA Computer Science Department, University of Freiburg, Germany 2. US Army Research Laboratory, USA 3. Computer Science and Engineering Dept., Arizona State University, USA

• A novel approach to learn a discriminative • A novel approach for real-time and robust scene description. robot awareness of human behaviors • Semantically labeled dataset capturing extreme perceptual and structural dynamics. • A new optimization formulation with simultaneous learning of • Learn salient image regions based on the discriminative human body parts geometrically stable image semantics. and skeletal features • Leverage the robust semantic-aware scene • An optimization algorithm to description for visual robot localization. solve the robot learning problem • Outperforms off-the-shelf features from deep with theoretical convergence Simultaneous learning of discrinimative human body parts and skeletal features convolutional neural networks. capability

10:00–10:05 WeA3.7 10:05–10:10 WeA3.8

Unsupervised Linking of Visual Features to Textual Visual Closed-Loop Control for Pouring Liquids Descriptions in Long Manipulation Activities Connor Schenck and Dieter Fox Department of Computer Science & Engineering E. E. Aksoy1, E. Ovchinnikova1, A. Orhan1, Y. Yang2 and T. Asfour1 University of Washington, USA 1H2T, Karlsruhe Institute of Technology, Germany 2CIDSE, Arizona State University, AZ, USA. • In this paper we show how a robot can pour precise amounts of liquid using closed-loop visual feedback. • We present a novel unsupervised framework, which links visual features and symbolic textual descriptions of manipulation activity videos. The proposed • First, the robot detects the liquid framework allows robots: using a fully-convolutional recurrent neural network. (1) to autonomously parse, classify, and label sequentially and/or concurrently performed atomic manipulations • Next, the robot uses this to estimate the volume of liquid in the target (2) to simultaneously categorize container. and identify manipulated objects without using any standard feature- 3 11 7 3 11 3 11 3 11 7 3 11 7 9 9 7 9 7 8 9 9 • Finally, the robot feeds the difference 2 6 2 8 6 8 6 6 2 6 based recognition methods, 4 4 2 4 4 4 between this estimate and the target Diagram of raw images to liquid 5 10 5 10 5 10 2 5 10 5 10 detections, to volume estimate, to (3) to generate textual descriptions 1 1 1 1 1 volume to a PID controller. The person takes a yellow cup from a big red cup The person takes the green The person hides the green control signal for long activities. and reveals a green apple hidden under the yellow cup. apple from the big red cup. apple with the yellow cup.

2017 IEEE International Conference on Robotics and Automation Session WeA4 Rm. 4411/4412 Wednesday, May 31, 2017, 09:30–10:45 Sensor and Robtoic Networks Chair Michael Beetz, University of Bremen Co-Chair Fumitoshi Matsuno, Kyoto University

09:30–09:35 WeA4.1 09:35–09:40 WeA4.2

Distributed Consistent Data Association A Cloud Service for Robotic Mental Simulations via Permutation Synchronization Asil Kaan Bozcuoğlu and Michael Beetz S. Leonardos, X. Zhou and K. Daniilidis Institute for Artificial Intelligence, Bremen, Germany Department of Computer and Information Science, University of Pennsylavnia, USA. - In this work, we extend openEASE cloud system to be capable of acting • Given noisy pairwise associations, find as a remote mental permutations so that simulation service. - People and robots can

define a problem within • Analogous to rotation synchronization problem a semantically- from relative measurements. annotated map with • Proposed solution: distributed averaging on Prolog queries. the set of doubly stochastic matrices: - Then, openEASE runs the selected learning algorithm and returns results

09:40–09:45 WeA4.3 09:45–09:50 WeA4.4

Mobile Robots for Learning Spatio-temporal Unsupervised Camera localization Interpolation Models in Sensor Networks – in Crowded spaces The Echo State Map Approach Erik Schaffernicht, Victor Hernandez B., and Achim J. Lilienthal Alexandre Alahi, Judson Wilson, Li Fei-Fei, Silvio Savarese AASS Research Centre, Örebro University, Sweden Stanford University

Tracklets from uncalibrated cameras • Calibration and interpolation in sensor networks with the help of robot measurements • Echo State Networks for temporal interpolation

and Gaussian Processes spatial interpolation Inferred topology • Novel combination of Echo State Networks and Gaussian Processes to create Echo State Maps • Evaluation in simulation and for occupational health monitoring in an industrial environment

09:50–09:55 WeA4.5 09:55–10:00 WeA4.6

Automated Sequencing of Swarm Behaviors for Persistent Surveillance of Events with Unknown, Supervisory Control of Robotic Swarms Time-varying Statistics

Sasanka Nagavalli*, Nilanjan Chakraborty†, Katia Sycara* Cenk Baykal, Guy Rosman, Sebastian Claici, and Daniela Rus CSAIL, Massachusetts Institute of Technology, USA *Robotics Institute, Carnegie Mellon University, USA †Mechanical Engineering, Stony Brook University, USA • Given a library of swarm behaviors and a performance criterion encoding the task at hand, what is the optimal sequence of swarm behaviors to accomplish the desired task? • Formalization of swarm behavior sequencing problem Swarm robot trajectories • Algorithm for monitoring stochastic events with time-varying rates • Algorithm for finding the best swarm behavior resulting from execution of • Bridges the Multi-Armed Bandit problem and persistent surveillance sequence for given decision time points with chosen behavior sequences optimality (or bounded suboptimality) and for navigation (left) and • Long-run average optimal policies under temporal variation constraints completeness guarantees area coverage (right) applications • Simulation results in real-world inspired persistent surveillance scenarios • Simulation results for (1) swarm navigation and (2) dynamic area coverage applications

10:00–10:05 WeA4.7 10:05–10:10 WeA4.8

Decentralized Navigation for Heterogeneous Distributed Voronoi Neighbor Identification from Swarm Robots with Limited Field of View Inter-Robot Distances

Ryuma Maeda, Takahiro Endo and Fumitoshi Matsuno Matthew Elwin, Randy Freeman, and Kevin Lynch Department of Mechanical Engineering and Science, Northwestern University, USA Kyoto University, Japan

• A connectivity-maintenance method for a • A large group of robots has range-only heterogeneous swarm. measurements to other robots • A single leader navigates the other followers • Robots identify their Voronoi neighbors without without communication. localization • Improves efficiency of distributed algorithms • Each robot has a different sensing range, relevant to large multi-robot systems limited field of view, and physical limitations. • Distances estimated with XBee Received • The proposed method is fully decentralized, Signal Strength Indicator (RSSI) which provides scalability.

2017 IEEE International Conference on Robotics and Automation Session WeA5 Rm. 4511/4512 Wednesday, May 31, 2017, 09:30–10:45 Aerial Robot 1 Chair Woosoon Yim, University of Nevada, Las Vegas Co-Chair Stefano Stramigioli, University of Twente

09:30–09:35 WeA5.1 09:35–09:40 WeA5.2

Application of Substantial and Sustained Force Three Dimensional Moving Path Following for to Vertical Surfaces using a Quadrotor Fixed-Wing Unmanned Aerial Vehicles Han Wopereis, Jim Hoekstra, Tiago Oliveira Tjark Post, Geert Folkertsma, Stefano Stramigioli Portuguese Air Force Academy, Portugal RAM, University of Twente, The Netherlands A. Pedro Aguiar Matteo Fumagalli Faculty of Engineering, University of Porto, Portugal RVMI, Aalborg University Copenhagen, Denmark Pedro Encarnação Católica Lisbon School of Business & Economics, Portugal • This work presents a control algorithm capable of controlling a quadrotor in high-force • MPF allows an autonomous vehicle to follow a path that is moving interaction. w.r.t. an inertial frame; • The controller is based on LQR-optimized • Lyapunov-based control law using a quaternion state feedback, coupling roll and yaw control. formulation; • Experiments demonstrate sustained The quadrotor applying • Flight test results: interaction forces exceeding the quadrotor's substantial force. - Autonomous landing on a (emulated) weight. moving vessel; ANTEX-X02 UAV - Tracking a 3D moving lemniscate path.

09:40–09:45 WeA5.3 09:45–09:50 WeA5.4

Modeling and Control of a Saucer Type Implementation of a Parametrized Infinite- Coandă Effect UAV Horizon MPC Scheme with Stability Guarantees Jameson Lee and Woosoon Yim Mechanical Engineering, University of Nevada, Las Vegas, USA M. Muehlebach, C. Sferrazza, and R. D’Andrea Seung Hwan Song, Hyun Wook Shon, and Hyouk Ryeol Choi Institute for Dynamic Systems and Control, ETH Zurich, Switzerland Mechanical Engineering, Sungkyunkwan University, Republic of Korea

• A dynamic model and controller for a prototype • Parametrized Infinite-Horizon Model Predictive Coandă effect drone was developed. Control Scheme • Experimental validation of model parameters • Retain Infinite Prediction Horizon by using was performed to improve the controller and Basis Functions -> Inherent Closed-Loop model simulation performance. Stability • A custom flight stack was developed using the • Experimental Evaluation on an 8kg-UAV that ArduPilot firmware to affect the derived servo Initial Flight Test of the uses Thrust Vectoring for Stabilization mapping. S-Coandă Drone with the • Initial flight tests were performed on the Developed Controller prototype using the experimental flight stack

09:50–09:55 WeA5.5 09:55–10:00 WeA5.6

A global controller for flying wing tailsitter Short-term UAV Path-Planning vehicles with Monocular-Inertial SLAM in the Loop

Robin Ritz and Raffaello D’Andrea Ignacio Alzugaray, Lucas Teixeira and Margarita Chli Institute for Dynamic Systems and Control, ETH Zurich, Switzerland Vision for Robotics Lab, ETH Zurich, Switzerland

• We present a global controller for A novel path-planning pipeline with monocular-inertial SLAM in the loop of tracking nominal trajectories with a finding a path. flying wing tailsitter vehicle • An outer control loop computes a • Designed for robotic platforms with desired attitude keeping the vehicle in high-mobility & limited onboard coordinated flight computational capacity, such as small aircraft. • An inner control loop tracks the desired attitude using a lookup table • Allows structured exploration to a with precomputed optimal trajectories goal destination without requiring a The IDSC Tailsitter. This vehicle is map of the scene known a priori. • The proposed controller can be used for experimental validation of implemented on a typical the proposed controller. • Avoids newly appearing obstacles microcontroller and the performance is on the fly via quick re-planning. Façade Inspection: the Planned Path to reach the Goal is constantly updated to demonstrated in various experiments avoid the obstacles perceived on the fly

10:00–10:05 WeA5.7 10:05–10:10 WeA5.8

Control of Statically Hoverable Multi-Rotor Aerial ICRA 2017 Digest Template Vehicles and Application to Rotor-Failure Robustness Efficient Aerial-Aquatic Locomotion with a for Hexarotors Single Propulsion System Giulia Michieletto1,2 , Markus Ryll1 and Antonio Franchi1 Yu Herng Tan Rob Siddall and Mirko Kovac 1 LAAS-CNRS, Université de Toulouse, CNRS, France. Department of Aeronautics, Imperial College London, UK 2 Dep. of Information Engineering, University of Padova, Italy. • Aerial-aquatic propulsion is challenging because of the dramatically different  Algebraic conditions to ensure static properties of air and water. hover (zero linear and angular • While small aerial propellers can operate momenta) for any multi-rotor platform efficiently underwater, a single motor with generically oriented rotors cannot drive the propeller efficiently in both media  Cascaded controller based on a preferential direction in the null-space • We have designed a two speed epicyclic gearbox which maximises efficiency in air of the control moment matrix A miniature robot propelling itself and water. A tilted-propeller hexarotor efficiently in air and water/  analysis on the hoverability recovering from a failure thanks to • The robot can change gear simply by capabilities of hexarotor platforms the analysis and the controller reversing motor direction, and no when a rotor fails proposed in the paper. additional actuation is required.

2017 IEEE International Conference on Robotics and Automation Session WeA6 Rm. 4611/4612 Wednesday, May 31, 2017, 09:30–10:45 Cognitive Robotics Chair Minoru Asada, Osaka University Co-Chair Fulvio Mastrogiovanni, University of Genoa

09:30–09:35 WeA6.1 09:35–09:40 WeA6.2

Gesture-based Robot Control: Learning Individual Motion Preferences From Design Challenges and Evaluation with Humans Audience Feedback of Motion Sequences Junyun Tay1,2 and Manuela Veloso1 Enrique Coronado, Jessica Villalobos, 1Department of Mechanical Engineering, Carnegie Mellon University, USA Barbara Bruno and Fulvio Mastrogiovanni I-Ming Chen2 Department of Informatics, Bioengineering, Robotics and Systems Engineering, 2School of Mechanical and Aerospace Engineering, University of Genoa, Italy Nanyang Technological University, Singapore

• We introduce a control framework for mobile • Goal: Select the most preferred motion robots relying on human gestures and discuss sequence for the robot to animate an input signal the related design principles. • Audience’s feedback comprises the ratings of the motions used and motions’ ratings are • Gestures are modelled using 6D inertial unknown initially information of the person’s wrist. • Observation of audience feedback at the end of the motion sequence queried is noisy • We tested the framework on the Husqvarna • MAK selects sequences to query and learns the Overview of Approach – Research Platform robot, with 27 volunteers. motions’ ratings to determine most preferred Multi-Armed bandit and

sequence Kalman filter (MAK) • The developed software is available online.

09:40–09:45 WeA6.3 09:45–09:50 WeA6.4

Semantic Web-Mining and Deep Vision for Lifelong Predicting Task Intent From Surface Object Discovery Electromyography Using Layered Hidden Markov Models Jay Young and Lars Kunze and Nick Hawes Yosef Razin Intelligent Robotics Lab, University Of Birmingham, UK School of Aerospace Engineering, Georgia Institute of Technology, USA Valerio Basile Kevin Pluckter and Jun Ueda INRIA, WIMMICS, France School of Mechanical Engineering, Georgia Institute of Technology, USA Barbara Caputo Karen Feigh University de Roma, Sapienza, Italy School of Aerospace Engineering, Georgia Institute of Technology, USA • First successful application of HMM-based learning to physiological data, e.g. arm sEMG A novel approach for predicting the semantic identity of unknown, • Our Layered Hidden Markov Model (LHMM) is everyday objects based on web-mining using distributional semantics a modular bi-layer system for classification and Deep Vision. and prediction Utilised as part of a fully autonomous lifelong object discovery pipeline • LHMM outperformed six other common for mobile robots, and deployed long-term in an active workplace. classifiers, achieving an F1 of .735 Allows the robot to constrain the meaning of objects it discovers using • With the highest performing features, LHMM Layered Hidden Markov both spatial-semantic context and visual features. reached 82% intent prediction accuracy over Model for Intent Prediction the next second

09:50–09:55 WeA6.5 09:55–10:00 WeA6.6

Deep Multimodal Embedding: Deep Visual Foresight for Planning Robot Motion Manipulating Novel Objects with Point-clouds, Language and Trajectories Chelsea Finn and Sergey Levine Jaeyong Sung*§ Ian Lenz* Ashutosh Saxena‡ Google Brain, Mountain View, CA, USA *Cornell University Dept. of Computer Science, UC Berkeley, CA, USA §Stanford University ‡Brain of Things, Inc.

• Learns a semantically meaningful • Combine a learned action-conditioned embedding space of point-clouds, predictive model of images (i.e. a visual language and trajectories. imagination) with model-predictive control to • A novel approach to manipulation plan to push objects via shared multi-modal embedding • Entirely self-supervised approach, requiring with deep neural networks. minimal human involvement A robot uses a learned predictive model of • An algorithm for unsupervised images to push objects. pre-training of multi-modal features. • Tested on Robobarista dataset and on a PR2 robot.

10:00–10:05 WeA6.7 10:05–10:10 WeA6.8

Learning to Represent Haptic Feedback Learning to guide task and motion planning for Partially-Observable Tasks using score-space representation Jaeyong Sung1,2 J. Kenneth Salisbury1 Ashutosh Saxena3 Beomjoon Kim and Leslie Pack Kaelbling and

1 Stanford University Tomas Lozano-Perez 2 Cornell University Computer Science and Artificial Intelligence Laboratory, 3 Brain of Things, Inc. Massachusetts Institute of Technology, USA

• We introduce an algorithm • We propose an algorithm that speeds up which learns a task relevant planning by learning from past experience representation of haptic feedback • Predict constraints on the search space in • A framework for modifying a order to afford good generalization while nominal manipulation plan for reducing computation time interactions that involve haptic • Representing a planning problem with scores feedback of previously attempted plans gives direct An instance of a planning • The model, parametrized by deep information about similarity among constraints problem where the robot recurrent neural networks, utilizes and problem instances needs to pick-and-place variational Bayes methods the black object from one table to another in the other room

2017 IEEE International Conference on Robotics and Automation Session WeA7 Rm. 4711/4712 Wednesday, May 31, 2017, 09:30–10:45 Grippers and Other End-Effectors Chair Wei Lin, SIMTech, A*STAR Co-Chair Shinichi Hirai, Ritsumeikan Univ.

09:30–09:35 WeA7.1 09:35–09:40 WeA7.2

Design of a Novel Variable Stiffness Gripper Force and Moment Constraints of a Curved Surface Using Permanent Magnets Gripper and Wrist for Assistive Free Flyers Amirhossein H. Memar and Ehsan T. Esfahani Matthew A. Estrada, Hao Jiang, Bessie Noll, Mechanical and Aerospace Engineering Department, University at Buffalo, USA Marco Pavone, Mark R. Cutkosky Nicholas Mastronarde Stanford University, USA Electrical Engineering Department, University at Buffalo, USA Elliot W. Hawkes UC Santa Barbara, USA • A robot gripper with compliantly actuated Wrist Design Wrist

fingers to improve safety in manipulation • Design considerations of wrist mechanism for free Active or Passive • Use of repulsive magnets in antagonistic flying robots equip with gecko inspired adhesive. 7 6 Wrist allows a robot to apply moments in addition to 5 4 configuration as nonlinear springs [N] y

F 3 2 forces. 1 0 20 • Estimation of external forces without the need -0.1 0 0.1 -20 0 M [Nm] F [N] z x • Establish limitations on the forces/moments that the of Surface Limit for force sensor at each finger Constraints Gripper wrist can impart, subject to adhesion capabilities. • Experimentally validated the gripper’s Variable Stiffness Gripper functionality during stiff collisions • Present analysis for tuning a passive wrist mechanism, or controlling an active wrist, along with experiments and simulation. and Geometry Geometry and Adhesion Capabilities Adhesion

09:40–09:45 WeA7.3 09:45–09:50 WeA7.4

Design of Parallel-Jaw Gripper Vision-Based Model Predictive Control for Within-Hand Tip Surfaces for Robust Grasping Precision Manipulation with Underactuated Grippers Menglong Guo, David V. Gealy, Jacky Liang, Jeffrey Mahler, Aimee Goncalves, Stephen McKinley, Berk Calli and Aaron M. Dollar Juan Aparicio Ojea, Ken Goldberg Department of Mechanical Engineering and Material Science, Yale University, UC Berkeley AUTOLAB and Siemens, Berkeley CA, USA U.S.A. • 37 gripper jaw surface designs were created using 3D printed casting molds and silicon • Precision manipulation with underactuated rubber. hands is challenging due to difficulties in modeling the process. • 1377 physical grasp trials using a 4-axis • Conventional visual servoing methods provide robot (with automated reset). a degree of robustness to modeling uncertainties. • Most effective surface design compared in • However, if inaccuracies are large, significant Vision-based within-hand 320 trials with ABB robot against: std. performance degradation is observed. gripper surface, std. gripper wrapped with precision manipulation with Model T42 hand. tape, and gecko-inspired gripper surface. • To attain high performance even with rough models, we propose a novel Model Predictive Control-based visual servoing method.

09:50–09:55 WeA7.5 09:55–10:00 WeA7.6

Optimal Design of a Soft Robotic Gripper with High Design and Analysis of a Soft-Fingered Hand Mechanical Advantage for Grasping Irregular Objects with Contact Feedback Chih-Hsing Liu, and Chen-Hua Chiu Van Ho Department of Mechanical Engineering, National Cheng Kung University, Taiwan JAIST, Japan Shinichi Hirai • An optimal design procedure (including Department of Robotics, Ritsumeikan Univ., Japan topology optimization and size optimization) has been presented to synthesize compliant mechanisms with high mechanical advantage. • This paper presents a novel approach to the fabrication of a soft robotic hand with contact • The proposed topology optimization method Topology optimization feedback for grasping delicate objects. can consider both mechanical advantage and geometric advantage of the analyzed compliant • Each finger has a multilayered structure, mechanism with multiple output ports. consisting of a main structure and sensing • Experimental results (including mechanical elements. The main structure includes a softer advantage test, geometric advantage test, layer much thicker than a stiffer layer. adaptability test, and grasping test) show the • The gripping energy of the fingers is generated developed gripper is with higher payload, faster from the elastic energy of the pre-stretched softer response, better adaptability and stability in layers, and controlled by simple tendon strings Compliant gripper overall among the three analysis cases. pulled/released by a single actuation

10:00–10:05 WeA7.7 10:05–10:10 WeA7.8

Reliable Grasping of Three-Dimensional Variable-grasping-mode underactuated soft gripper Untethered Mobile Magnetic Microgripper for with environmental contact-based operation Autonomous Pick-and-Place Jiachen Zhanga, Onaizah Onaizaha, Kevin Middletonb, Toshihiro Nishimura, Kaori Mizushima, Lidan Youa,b, and Eric Dillera Yosuke Suzuki, Tokuo Tsuji and Tetsuyou Watanabe a Department of Mechanical & Industrial Engineering, Univ. of Toronto, Canada Natural science and Technology, Kanazawa University, Japan b Institute of Biomaterials & Biomedical Engineering, Univ. of Toronto, Canada

• The first example of reliable autonomous • Development of the robotic gripper with soft 3D micrograsping and cargo delivery with surface and underactuated joints. different cargo shapes • With one actuator, three grasping mode, i.e., • The microgripper is controlled by a global parallel gripper, pinching and enveloping, are magnetic field with simple controllers and realized by utilizing contact with an limited feedback environment, such as a supporting surface.

• The microgripper can grasps repeatedly Figure caption is optional, • The range of graspable objects is wide and and each attempt takes less than 1 use Arial 18pt included soft, rigid, deformable, fragile, small, second large, thin and heavy objects • The microgripper is biocompatible and • The grasping test for various 68 items was does not harm cells in contact conduced to validate the gripper’s capability.

2017 IEEE International Conference on Robotics and Automation Session WeA8 Rm. 4613/4713 Wednesday, May 31, 2017, 09:30–10:45 Physical Human-Robot Interaction Chair Alin Albu-Schäffer, DLR - German Aerospace Center Co-Chair Jun Kinugawa, Tohoku University

09:30–09:35 WeA8.1 09:35–09:40 WeA8.2

A Framework For Robot-Assisted Dofﬁng of A System for Learning Continuous Human-Robot Personal Protective Equipment Interactions from Human-Human Demonstrations 1 2 Antonio Umali and Dmitry Berenson 1 2 1 1 David Vogt , Simon Stepputtis , Steve Grehl , Computer Science Department, Worcester Polytechnic Institute, USA 1 2 2EECS Department, University of Michigan, USA Bernhard Jung , Heni Ben Amor 1 Faculty of Mathematics and Informatics, TU Bergakademie Freiberg, Germany • Health workers treating Ebola are at high risk 2 School of Computing, Informatics, Decision Systems Engineering, Arizona of infection during the doffing of Personal State University, Tempe, USA Protective Equipment (PPE) • We introduce a semi-autonomous robot doffing • From two-person task demonstration assistant to reduce risk and human effort an Interaction Model is extracted • We segment the doffing procedure into a • During runtime the model is sequence of human and robot actions. The employed in a human-robot setting robot only assists when necessary, the human • The model allows spatio-temporal performs the more intricate parts. adaptation of demonstrated tasks • Robot motions are planned autonomously Baxter helping to doff an • Two complex, sequential assembly using new cost functions with TrajOpt. apron tasks show the effectiveness of the approach • Experiments on five doffing tasks suggest that In a collaborative Lego assembly task, the safety can be improved in some tasks while robotic assistant continuously coordinates effort can be reduced in all five. its behavior with the human co-worker.

09:40–09:45 WeA8.3 09:45–09:50 WeA8.4

A Study of Bidirectionally Telepresent Tele- A Game-Theoretic Approach for action During Robot-mediated Handover Adaptive Action Selection in Close Proximity Human-Robot-Collaboration Jianqiao Li and Kris Hauser Electrical and Computer Engineering Department, Duke University, USA V. Gabler, T. Stahl, G. Huber, O. Oguz, and D. Wollherr Zhi Li Technical University of Munich Department of Mechanical Engineering, Worcester Polytechnic Institute, USA • Problem: Adaptive action-selection in close proximity Human-Robot-Collaboration(HRC). • How does communication affect physical Approach: interaction between a human and human- • Define HRC as an iterative game controlled robot? with personal and interactive costs to reflect mutual influence. • Concept: Bidirectionally Telepresent Teleaction • Experimental Evaluation: Dyadic joint pick- • User study: telepresence improves intimacy and-place scenario in close proximity and workload in object handover • Result/Contribution: Online application of an • Did not actually improve performance, but autonomous decision framework based on subjects perceived improved performance Object handover experiment game theory incorporating mutual influences Exemplary joint amongst the agents involved. pick-and-place HRC-scenario

09:50–09:55 WeA8.5 09:55–10:00 WeA8.6

An EMG-Driven Assistive Hand Exoskeleton Admittance Control Parameter Adaptation for for Spinal Cord Injury Patients: Maestro Physical Human-Robot Interaction

Youngmok Yun, Paria Esmatloo, Alfredo Serrato, Priyanshu Agarwal and Ashish D. Deshpande Chiara Talignani Landi, Federica Ferraguti, Dept. of Mechanical Engineering, The University of Texas at Austin, USA Lorenzo Sabattini, Cristian Secchi, Cesare Fantuzzi Sarah Dancausse DISMI, University of Modena and Reggio Emilia, Italy Dept. of Mechanical Engineering, ENISE, France Curtis A. Merring • In physical Human-Robot Interaction, Brain & Spine Recovery Center, Seton Brain & Spine Institute, USA instability occurs when the operator stiffens his/her arm • We developed an EMG-driven assistive • We propose a heuristic for detecting the hand exoskeleton for SCI patients. deviation from the “nominal behavior” • SCI patients with the exoskeleton grasped • Adjustment of the admittance parameters various objects required in daily activities. while guaranteeing the passivity of the • Sollerman hand function test results show system, exploiting energy tanks the improved hand functions of SCI • Experiments validated on a KUKA LWR 4+ patients. Hand Assistive Exo

10:00–10:05 WeA8.7 10:05–10:10 WeA8.8

Dance Teaching by a Robot: Combining Cognitive Interactive Force Control of an Elastically Actuated Bi-articular Two-link and pHRI for Supporting the Skill Learning Process manipulator Chan Lee, Sehoon Oh (DGIST, KOREA) Mechanism : Control : Diego F. Paez G., Jun Kinugawa, and Kazuhiro Kosuge Bi-articular Robotic Arm Disturbance Observer Robotics Department, Tohoku University, Japan The bi-articular mechanism is an To achieve high performance of the emerging configuration, which is cPEA, a model-based control is known to have the advantage of torque designed utilizing Disturbance Breno A. Yamamoto Hiroko Kamide transmissibility. Observer (DOB) and feedforward (FF) Multi-degree-of-freedom impedance control. University of Uberlandia , Brazil Nagoya Univeristy, Japan control of robots is a still challenging The model-based force control can problem. High precision force control achieve high performance of force at the actuator level is required. tracking Fig. 1: Schematic diagram of proposed Fig. 3: Proposed model-based control for robot arm. cPEA and its closed-loop performance. • Design of a robot teacher with the role of Actuator : compact Planetary geared Conclusion guiding a human partner in a dance scenario. Elastic Actuator(cPEA) The cPEA incorporates a planetary Taking the advantage of the high force • A novel cumulative performance score system gear for series elastic torque generation. control performance, _ the impedance The following features can be realized control of the developed robotic arm that modifies the robot’s behavior during thorough this design: can be achieved in the workspace. 1)minimized backlash of gear train, The results of impedance control interactions with each student. 2)spring linearity, experiment will be presented by a video. Fig. 2: A compact Planetary geared 3)compactness of the actuator. • A progressive teaching methodology for Elastic Actuator. Fig. 4: Workspace impedance controller. adapting low-level control to the student’s state during the learning process.

2017 IEEE International Conference on Robotics and Automation Session WeA9 Rm. 4811/4812 Wednesday, May 31, 2017, 09:30–10:45 TRO Session - Actuation, Locomotion, Grasping Chair Patrick Wensing, Massachusetts Institute of Technology Co-Chair Pey Yuen Tao, SIMTech

09:30–09:45 WeA9.1 09:45–10:00 WeA9.2

Proprioceptive Actuator Design in the MIT Energy Efficient Monopod Running with Large Cheetah: Impact Mitigation and High-Bandwidth Payload Based on Open Loop Parallel Elastic Physical Interaction for Dynamic Legged Robots Actuation Patrick M. Wensing, Albert Wang, Sangok Seok, David Otten, Fabian Guenther ETH Zurich, Switzerland Jeffrey Lang, and Sangbae Kim Fumiya Iida Massachusetts Institute of Technology, USA University of Cambridge, United Kingdom • Introduces an actuator paradigm to handle impact and manage physical interaction • Simulation and experimental analyses of a monopod running robot CARGO • Presents central principles through modal analysis of a simple leg model and • World record of energy efficiency in hopping dimensional analysis of DC motor geometry robot locomotion (Total Cost of Transport 0.10 at Velocity 0.19m/s with a total body mass of • Introduces the impact mitigation factor (IMF) 183kg) to quantify backdrivability at impact • Open-loop locomotion stability over variations • Includes results from bounding experiments of carrying payload from 0 to 150kg Energy Efficient Monopod with the MIT Cheetah II robot, highlighting Proprioceptive actuators Robot CARGO force tracking in highly-dynamic regimes provide impact mitigation for dynamic locomotion

10:00–10:15 WeA9.3 10:15–10:30 WeA9.4

Stabilizing Series-Elastic Point-Foot Bipeds Comparative Design, Scaling, and Control of Using Whole-Body Operational Space Control Appendages for Inertial Reorientation

1 2 3 Donghyun Kim, Ye Zhao, Gray Thomas, Benito R. Fernandez, Thomas Libby , Aaron M. Johnson , Evan Chang-Siu , Robert J. Full1 and Daniel E. Koditschek4 Luis Sentis 1Univ. of California at Berkeley; 2Carnegie Mellon University; 3California State Mechanical Engieering, University of Texas at Austin, US University Maritime Academy; 4University of Pennsylvania; USA

• Planning algorithms for achieving unsupported • Inertial Reorientation: agility via orientation control dynamic balancing on our point-foot biped • Simple model (template): links design to tasks • Force feedback control of the internal forces to regulate contact interactions with the complex • Detailed models (anchors): real morphology environment. •“Morphological Reduction:” • Experimental validation the efficacy of our new - collapses dimension from anchor to template Whole-Body Operational Space Control and - facilitates design planning strategies via balancing over a - enables comparison of diverse bodies disjointed terrain and attaining dynamic Point foot biped robot, • Thanks to NSF: balance without a mechanical support Hume - CiBER-IGERT Award DGE-0903711 - CABiR Award CDI-II 1028237

10:30–10:45 WeA9.5

Hierarchical Fingertip Space: A Unified Framework for Grasp Planning and In-Hand Grasp Adaptation K. Hang1, M. Li2, J. A. Stork1, Y. Bekiroglu1, F. T. Pokorny1, A. Billard2 and D. Kragic1 1RPL/CAS, KTH Royal Institute of Technology, Sweden 2LASA, École Polytechnique Fédérale de Lausanne, Switzerland

• Formulates a unified optimization framework based on a hierarchical representation of contact candidates • Optimizes grasp stability, hand reachability, and adaptability • Integrates grasp optimization, control, and stability estimation • Allows fingertip grasp synthesis, grasp adaptation, and finger gaiting on arbitrary shapes

2017 IEEE International Conference on Robotics and Automation Session WeA10 Rm. 4911/4912 Wednesday, May 31, 2017, 09:30–10:45 Medical Robots and Systems 4 Chair Atsuo Takanishi, Waseda University Co-Chair Robert James Webster III, Vanderbilt University

09:30–09:35 WeA10.1 09:35–09:40 WeA10.2

An Intervening Ethical Governor for a robot Autonomous Retroflexion of a Magnetic mediator in patient-caregiver relationship: Flexible Endoscope Implementation and Evaluation Piotr Slawinski, Addisu Taddese and Kyle Musto Mechanical Engineering, Vanderbilt University, USA Jaeeun Shim, Ronald Arkin, and Michael Pettinatti Keith Obstein Mobile Robot Laboratory, Georgia Institute of Technology, USA Vanderbilt University Medical Center, USA Pietro Valdastri • An intervening ethical governor (IEG) School of Electronic and Electrical Engineering, University of Leeds, UK enables a robot mediator to ethically intervene in a situation where patients • We have developed an algorithm that or caregivers cross accepted ethical optimizes an applied magnetic wrench to boundaries ! achieve retroflexion • Developed and implemented four intervention rules • The nature of the dipole field dictates how • Angry, Quiet/withdrawn, Stay-in-the-room, Safety-first rules much torque can be applied about a device’s particular axis • Evaluated the IEG model by conducting a qualitative study (interviews) with the target population - adults 60 years of age or older • This is the first demonstration of an autonomous maneuver in magnetically actuated colonoscopy

09:40–09:45 WeA10.3 09:45–09:50 WeA10.4

Toward Monocular Camera-Guided Retinal Vein Through the Eustachian Tube and Beyond: A New Cannulation with an Miniature Robotic Endoscope to See into the Middle Actively Stabilized Handheld Robot L. Fichera1, N.P. Dillon1, D. ZhangEar2 , I.S. Godage1, M. A. Siebold2, B.I. Hartley3, J.H. Noble2, P.T. Russell III4, R.F. Labadie4, R.J. S. Mukherjee, S. Yang, R. A. MacLachlan, L. A. Lobes, Webster1 Jr., J. N. Martel, C. N. Riviere 1Dept. of Mechanical Engineering and 2 Dept. of Electrical Engineering and The Robotics Institute, Carnegie Mellon University, USA Computer Science, Vanderbilt University, United States 3Dept. of Radiology and 4Dept. of Otolaryngology, Vanderbilt University Medical Center, United States • Monocular camera-based surface • We present a novel miniature steerable reconstruction and homography matrix endoscope for minimally-invasive surveillance of estimation, using surgical laser scanning. the Middle Ear (diameter: 1.80 mm) • Targets defined in image coordinates are • Kinematic requirements for the device are projected on to robot’s global coordinate derived based on medical images system. Motion scaling for precise cannula positioning around the target. • The device is deployed in a 3D plastic phantom • Experiments demonstrate more accurate • Results show that the device provides > 74% Tool, laser, and eye surface reconstruction and more precise visibility coverage of the sinus tympani (see Endoscope insertion in the phantom approach to the vessels. figure) compared to only 6.9% using a straight, Middle Ear. The dashed non-articulated endoscope line indicates the location of the sinus tympani.

09:50–09:55 WeA10.5 09:55–10:00 WeA10.6

A Curved-Drilling Approach in Core A Balloon Endomicroscopy Scanning Device for Decompression of the Femoral Head Diagnosing Barrett’s Oesophagus Osteonecrosis Using a Continuum Manipulator Siyang Zuo, Michael Hughes, and Guang-Zhong Yang Farshid Alambeigi, Shahriar Sefati, Ryan J. Murphy, Iulian Hamlyn Centre for Robotic Surgery, Imperial College London, UK Iordachita, Russel H. Taylor, Harpal Khanuja, and Mehran Armand Laboratory for Computational Sensing and Robotics,Johns Hopkins University • A new robotic catheter for controlled, Yu Wang School of Biological Science and Medical Engineering, Beihang University large area scanning and mosaicing Robotic

of the oesophagus catheter Cong Gao • Encapsulated in an inflatable balloon Department of Electronic Engineering, Tsinghua University

• Suitable for deployment through an • Design and fabrication of a novel steerable drill endoscope working channel using a continuum dexterous manipulator. • Ex vivo swine oesophagus tissue Quantitative performance and efficiency results are demonstrated, illustrating 69mm • a viable scanning approach for evaluation of the tool in robot-assisted treatment of core decompression of osteonecrosis. oesophagus endomicroscopy Combined with • Verification experiments for S-shape and endoscope multiple-branch drilling performed on both Mosaic images simulated and human cadaveric bones.

10:00–10:05 WeA10.7 10:05–10:10 WeA10.8

Development and Evaluation of Concurrent A Single-Port Robotic System for Transanal Control for Osteolytic Lesion Treatment Micro-Surgery – Design and Validation Paul Wilkening, Farshid Alambeigi, Russell H. Taylor, and Mehran Armand Jianzhong Shang, Konrad Leibrandt, Petros Giataganas, Laboratory for Computational Sensing and Robotics, Johns Hopkins University, USA Ryan J. Murphy and Mehran Armand Valentina Vitiello, Carlo Seneci, Piyamate Wisanuvej, Jindong Liu, Research and Exploratory Development Department, JHU Applied Physics Laboratory, USA Gauthier Gras, James Clark, Ara Darzi and Guang-Zhong Yang The Hamlyn Centre, Imperial College London, UK • Osteolysis treatment surgery requires a high degree of dexterity within a • This paper introduces a single-port robotic confined area to clear lesion material platform for Transanal Endoscopic Micro- • Our system concurrently controls a Surgery robotic arm and a continuum dexterous • The system is based on master-slave manipulator within the hip implant robotically controlled tele-manipulation • This system guides the manipulator • Design considerations of the robotic system while enforcing safety barriers to prevent collisions with the implant are introduced Full thickness dissection • Results from benchtop tests, ex-vivo animal on bovine tissue using the • The controller reliably followed a goal tissue evaluation and in-vivo studies are micro-IGES surgical robot path with a mean error of 0.42 mm Proposed robotic system for osteolysis treatment presented JHU Laboratory for Computational Sensing and Robotics

2017 IEEE International Conference on Robotics and Automation Session WeA11 Rm. 4813/4913 Wednesday, May 31, 2017, 09:30–10:45 Automation Chair Ron Lumia, University of New Mexico Co-Chair Rolf Johansson, Lund University

09:30–09:35 WeA11.1 09:35–09:40 WeA11.2

Design of a Flexure-Based Micro-Motion Stage Iteratively Learned and Temporally Scaled Force Control with With Constant Output Force Application to Robotic Assembly in Unstructured Environments

Piyu Wang and Qingsong Xu Johannes Bös, Arne Wahrburg, and Kim D. Listmann Department of Electromechanical Engineering ABB Corporate Research Germany University of Macau, Macau, China

• A new flexure-based precision positioning • Iterative Learning Control (ILC) micro-motion stage with constant output force applied to robotic assembly is designed and analyzed • Compliance introduced by • The zero-stiffness mechanism is realized by admittance control, reference combining a bistable mechanism and a trajectories modified by ILC positive-stiffness mechanism • Simultaneous increase of speed of • Analytical modeling and finite element analysis operation and reduction of contact simulation are conducted forces during assembly • A prototype is fabricated using 3D printing for • Experimental validation on 7 DoF experimental verification manipulator (ABB YuMi)

09:40–09:45 WeA11.3 09:45–09:50 WeA11.4

A Distributed Approach to Automated A Probabilistic Data-Driven Model Manufacturing Systems with Complex for Planar Pushing Structures using Petri Nets Maria Bauza and Alberto Rodriguez Yan Yang and HeSuan Hu Mechanical Engineering Department, School of Electro-mechanical Engineering, Xidian University Xi’an, Shaanxi, P. R. China Massachusetts Institute of Technology, United States Yang Liu School of Computer Science and Engineering, Nanyang Technological University, Republic of Singapore • Data-driven approach to predict the most likely outcome of a push and its variance. • First, this paper presents an innovative solution for distributed • The learned model outperforms analytical supervisor based on AMSs with flexible routes and assembly models with less than 100 samples. operations, thus allowing an extension to a broader class of AMSs; • Second, instead of collecting and distributing the global • Results are validated against a collected information from all nodes to different control points, our method dataset of repeated pushes. allows implementing global goals through local observation, control, and execution upon processes; • The model captures the stability of • Third, in case some resources are failed, our method can easily different pushes and their variability. adapt to such contingencies through on-line updating current resource information so that the available information on the resources can be incorporated in our method's logic.

09:50–09:55 WeA11.5 09:55–10:00 WeA11.6

UAV-Based Crop and Weed Classification NimbRo Picking: Versatile Part Handling for Smart Farming for Warehouse Automation Philipp Lottes1, Raghav Khanna2, Johannes Pfeipfer2, Max Schwarz, Anton Milan*, Christian Lenz, Aura Muñoz, Roland Siegwart 2 and Cyrill Stachniss1 Arul Selvam Periyasamy, Michael Schreiber, Sebastian Schüller and Sven Behnke 1 University of Bonn, Germany, 2 ETHZ, Switzerland Autonomous Intelligent Systems, University of Bonn, Germany * ACVT, University of Adelaide, Australia

• UAV-based field monitoring using • System for the Amazon Picking Challenge also an out-of-the-box Phantom 4 2016: Second and third place • Multiclass detection of sugar beets • Two deep-learning approaches for object and typical weed types using a detection and semantic segmentation regular RGB and RGB+NIR data • Model registration and heuristic grasp • Tested on fields in different countries selection • Classification accuracies: 86-96% • Parametrized motion primitives using a custom inverse kinematics solver

10:00–10:05 WeA11.7 10:05–10:10 WeA11.8

Planning and Executing Optimal Non-Entangling Peduncle Detection of Sweet Pepper for Autonomous Paths for Tethered Underwater Vehicles Crop Harvesting - Combined Colour and 3D Information Inkyu Sa1, Chris Lehnert2, Andrew English2, Chris McCool2, Feras Dayoub2, Ben Upcroft2, and Tristan Perez2 Seth McCammon and Geoffrey A. Hollinger 1 Autonomous Systems Lab., ETH Zürich, Switzerland School of Mechanical, Industrial, and Manufacturing Engineering 2 Science and Engineering Faculty, Queensland University of Technology, Australia Oregon State University • Motivation: Cutting the peduncle cleanly is one of the most difficult stages of the harvesting process and important for the • Formulate Non-Entangling extension to the crop quality. Travelling Salesman Problem (NE-TSP) • Approach: Fusing colour and 3D geometry • Compute optimal solution to NE-TSP with information of sweet peppers acquired from Mixed Integer Programming on a homotopy an RGB-D sensor with a supervised- augmented graph learning framework. • MIP method outperforms greedy and heuristic • Results: Quantitative and qualitative evaluations are performed with field-grown methods in simulated trials Non-entangling path for sweet pepper dataset and achieved average • Simulated results validated in pool test and tethered vehicle 0.71 AUC 3 for red, mixed-, green crops. Experimental setup (top-left), quantitative wharf inspection with Seabotix vLVB300 AUV • Releasing annotated 3D sweet peppers and (bottom-left), and qualitative (right) results for peduncle image dataset. red-green sweet peppers’ peduncle detection (marked in red from the right figure). 3 the Area-Under-the-Curve

2017 IEEE International Conference on Robotics and Automation Session WeB1 Rm. 4011 Wednesday, May 31, 2017, 11:05–12:20 Compliance Chair Kensuke Harada, Osaka University Co-Chair Christian Ott, German Aerospace Center (DLR)

11:05–11:10 WeB1.1 11:10–11:15 WeB1.2

A Sliding Mode Controller Design for the Robust Realizing Natural Springy Motion of Robotic Leg Position Control Problem of Series Elastic by Cancelling the Undesired Damping Factors Actuators Emre Sariyildiz and Haoyong Yu Jungsoo Cho and Kyoungchul Kong Biomedical Engineering, National University of Singapore, Singapore Mechanical Engineering Department, Sogang University, Korea

Huiming Wang actuator Automation, Chongqing University of Posts and Telecommunications, China • Realization of the SLIP model for running of impedance legged robots is challenged by the undesired • Robust position controller design for Series practical damping factors Elastic Actuators (SEAs) • The damping factors include mechanical • A novel Sliding Mode Controller design using impedance of actuators, friction and backlash disturbance estimation in power transmission mechanism, etc. • Improving robustness and suppressing • The proposed control method presents ideal chattering using second order Disturbance springy motion of a robotic leg by cancelling Observer (DOb) resistive forces resulted from the damping • Cancelling collocated and non-collocated factors disturbances power transmission friction / backlash Novel Series Elastic material Actuator viscosity

11:15–11:20 WeB1.3 11:20–11:25 WeB1.4

3DFlex: A rapid prototyping approach for multi- Compliant, Bi-stable Mechanisms with Multiple material compliant mechanisms in millirobots Stiffnesses through Controlled Spring Buckling

Ryan St. Pierre, Noah Paul, and Sarah Bergbreiter Brian LaFerriere, Carson Schlect, and John Swensen Department of Mechanical Engineering and Institute for Systems Research, School of Mechanical and Materials Eng., Washington State University, USA University of Maryland, College Park, MD USA

• The rigid components are 3D printed, and • Design and modeling of bi-stable mechanism flexures are inserted into the rigid with multiple stiffnesses. components, creating the final mechanism. • Bi-stability generated through precise control • The assembled mechanisms are robust, compression spring buckling. requiring over 1 N of force to delaminate, • Mathematical model presented to provide and surviving 150,000 cycles of bending ability optimize the potential energy profile. without failure • Design, fabrication, and analysis of prototype Figure caption is optional, • A 6 g walking quadrupedal millirobot is mechanism is demonstrated. use Arial 18pt presented as a case study for the design A 30 mm long, 6 g millirobot made and manufacturing methodology. with 3D printed rigid components and Kapton flexures

11:25–11:30 WeB1.5 11:30–11:35 WeB1.6

Passive Hierarchical Impedance Control Eigenmodes of Nonlinear Dynamics: Definition, via Energy Tanks Existence, and Embodiment into Legged Robots 1 2 1 1 with Elastic Elements A. Dietrich , X. Wu , K. Bussmann , C. Ott , 1 1 1,2 A. Albu-Schäffer1,2, and S. Stramigioli3 Dominic Lakatos , Werner Friedl , and Alin Albu-Schäffer 1Institute of Robotics and Mechatronics, German Aerospace Center (DLR), 1 Institute of Robotics and Mechatronics, DLR, Germany Germany 2 Department of Informatics, TUM, Germany 2Department of Informatics, Technical University Munich, Germany 3 University of Twente, the Netherlands

• Concept: invariant, linear 1-D submanifolds of • Proof of passivity for hierarchical multi- the configuration space of multibody systems objective control of redundant robots with joint elasticities called eigenmodes of • Two approaches based on virtual energy nonlinear dynamics tanks (local & global tanks) • Method: embodiment of task related •Comparison with the classical, null- eigenmodes in the dynamics of compliantly space-based approach and discussion actuated robotic systems by mechanical design Geometrical • Simulations and experiments on DLR’s representation of humanoid robot Justin • Example: three-segment pantograph leg with eigenmode dynamics on Source of activity in the embodied SLIP dynamics by selection of torus manifold classical approach realizable design parameters

11:35–11:40 WeB1.7 11:40–11:45 WeB1.8

On the Role of Stiffness Design for Fingertip Legged Elastic Multibody Systems: Adjusting Limit Trajectories of Underactuated Modular Soft Hands Cycles to Close-to-Optimal Energy Efficiency 2 1,2 1,2 1,2 I. Hussain , G. Salvietti , M. Malvezzi , D. Prattichizzo 1,2 2 2 1 Department of Advanced Robotics, Istituto Italiano di Tecnologia, Italy Philipp Stratmann , Dominic Lakatos , Mehmet C. Özparpucu , 1,2 2 Department of Information Engineering and Mathematics, Alin Albu-Schäffer 1 University of Siena, Italy Department of Informatics, TU Munich, Germany 2Institute of Robotics and Mechatronics, DLR, Germany • In this work, we propose a method to compute the stiffness of flexible joints and its realization in order • Passive compliant elements used for Motors Sensors to let the fingertips track a certain predefined energy-efficient movement. trajectory. • Leg with multiple bodies subject to • The stiffness computation is obtained leveraging on nonlinear dynamics and damping. the the mechanics of tendon-driven hands and on compliant systems, while for its implementation • Optimal control of hybrid dynamical beam theory has been exploited. system, experiments with Monte Carlo parameter screening, video. • We validate the proposed framework both in simulation and with experiments using a wearable • Linear coordinate transformation Controller robot for grasping compensation in patients with a induces close-to-optimal movement and paretic hand. allows adjustment to changing Linear Coordinate resonance conditions Transformation

2017 IEEE International Conference on Robotics and Automation Session WeB2 Rm. 4111 Wednesday, May 31, 2017, 11:05–12:20 Mapping 2 Chair Martin Magnusson, Örebro University Co-Chair Jaime Valls Miro, University of Technology Sydney

11:05–11:10 WeB2.1 11:10–11:15 WeB2.2

AtomMap: A Probabilistic Amorphous 3D Map Bayesian Generalized Kernel Inference for Representation for Robotics and Surface Reconstruction Occupancy Map Prediction Kevin Doherty, Jinkun Wang and Brendan Englot David Fridovich-Keil, Erik Nelson, and Avideh Zakhor Stevens Institute of Technology, USA Electrical Engineering and Computer Sciences, UC Berkeley, USA • A novel supervised learning formulation of occupancy mapping is proposed that • Novel occupancy map representation, with leverages Bayesian nonparametric inference, optional signed distance field a sparse kernel, and efficient data structures • More accurate than grid methods near surfaces • Predictive and accurate 3D, real-time viable mapping is achieved over sparse range data • Represent space as identical, non-overlapping spheres • Reverts to a specified prior when there is insufficient training data to reliably predict • Utilize approximate surface normals for occupancy improved accuracy • Exact recursive updates allow stable long-term performance under repeated observation of the same portions of the map, in contrast with other methods

11:15–11:20 WeB2.3 11:20–11:25 WeB2.4

Coupling Conditionally Independent Submaps for Deliberative Object Pose Estimation in Clutter Large-Scale 2.5D Mapping with Gaussian Markov Venkatraman Narayanan and Maxim Likhachev Random Fields The Robotics Institute, Carnegie Mellon University, USA Liye Sun , Teresa Vidal-Calleja, •Identification and pose estimation of 3D object and Jaime Valls Miro instances from depth data is a fundamental Centre for Autonomous Systems, University of Technology Sydney, Australia perception task: e.g., Amazon Picking Challenge •Generative methods such as PERCH were introduced recently to address limitations of • A generic submapping method for fusing multi- discriminative methods (sensitivity to occlusions modal uncertain data in a correlated way. and training-data) • Computation gain by combining •While PERCH casts multi-object localization as Gaussian Markov Random Fields, an efficient optimization over hypothesized Fusion in information form, and scenes, it assumes that scenes contain only “known” objects Conditional Independence. •We extend PERCH to be applicable in scenes • Novel information propagation that allows containing extraneous unmodeled clutter as well linear time recovery of the optimal global map. as for providing pose uncertainty estimates, Multiple pose predictions thereby increasing its practical applicability with uncertainty estimates

11:25–11:30 WeB2.5 11:30–11:35 WeB2.6

Warped Gaussian Processes Occupancy Automatic Room Segmentation from Unstructured 3D Data of Indoor Environments Mapping with Uncertain Inputs Rareș Ambruș KTH Royal Institute of Technology, Sweden Maani Ghaffari Jadidi, Jaime Valls Miro, and Sebastian Claici Gamini Dissanayake CSAIL, MIT, USA University of Technology Sydney, Australia Axel Wendt Bosch Research and Techology Center, USA • We account for the complication of the robot's perception noise using Warped Gaussian Processes (WGPs) in the occupancy mapping problem. • This approach allows for non- • We present an automatic method for reconstructing 2D floor plans. Gaussian noise in the observation • Our approach emphasizes accurate and robust primitive detection, and space and captures the possible ease of use. nonlinearity in that space better than • We provide detailed qualitative and quantitative experimental results. standard GPs.

11:35–11:40 WeB2.7 11:40–11:45 WeB2.8

Enabling Flow Awareness for Mobile Robots 3D Map Merging on Pose Graphs in Partially Observable Environments

Tomasz Piotr Kucner, Martin Magnusson, Erik Schaffernicht, Taigo Maria Bonanni, Bartolomeo Della Corte, and Giorgio Grisetti Dept. Computer, Control, and Management Eng., Sapienza Univ. of Rome, Italy Victor Hernandez Bennetts, and Achim J. Lilienthal AASS Research Centre, Örebro University, Sweden

• Traditional map merging approaches are • Probabilistic multi-modal flow modelling based on single rigid transformations with Circular-Linear Flow Field map • If input maps are noisy, distortions are (CliFF-map). propagated in the merged output • Method for building dense maps based on • Our approach uses piece-wise deformations sparsely distributed measurement and graph optimization to reduce noise and locations of pedestrian flow and air flow. Human- artifacts a) and b) are two input • Representation applicable in • First map merging approach for 3D maps, also maps. c) is the distorted Robot Interaction and Mobile Robot capable of dealing with noisy input outpu Olfaction. People velocity measurements and resulting map of people flow

2017 IEEE International Conference on Robotics and Automation Session WeB3 Rm. 4311/4312 Wednesday, May 31, 2017, 11:05–12:20 Visual Localization Chair Giorgio Metta, Istituto Italiano di Tecnologia (IIT) Co-Chair Edwin Olson, University of Michigan

11:05–11:10 WeB3.1 11:10–11:15 WeB3.2

Efficient Descriptor Learning Feature-based Localization between Air and Ground for Large Scale Localization Antonio Loquercio1, Marcin Dymczyk1, Bernhard Zeisl2, Simon Lynen2, Igor Gilitschenski1, Roland Siegwart1 Xipeng Wang, Steve Vozar and Edwin Olson 1Autonomous System Laboratory, ETH Zurich, Switzerland Computer Science & Engineering, University of Michigan, USA 2Google Inc., Zurich, Switzerland

•A novel learning strategy trains efficient • FLAG allows ground robot to perform global projections of visual descriptors: matching positioning by recognizing landmarks in an becomes fast and highly robust. aerial image. •A low latency linear projection increases • FLAG has comparable performance to LIDAR- the retrieval of input descriptors while based scan-matching localization in indoor decreasing memory and computational and outdoor environment. costs. • FLAG could be used as a replacement or FLAG updates global •With context information, we substantially augmentation for GPS. position by matching large increase the discriminability of low level vertical features from the Difficult descriptor matches under features as edges, corners or blobs. ground to features in an strong viewpoint changes. aerial image

11:15–11:20 WeB3.3 11:20–11:25 WeB3.4

Action Recognition: From Static Datasets to Visual Place Recognition Moving Robots with Probabilistic Voting F. Rezazadegan, S. Shirazi, B.Upcroft, M. Milford Department of Electrical Engineering and Computer science, Queensland Mathias Gehrig, Elena Stumm, Timo Hinzmann University of Technology, Australia and Roland Siegwart Autonomous Systems Lab, ETH Zürich, Switzerland Place recognition Incorporating Prior Action recognition • A DCNN algorithm for moving robots to Knowledge recognize human actions in non-informative

Predicting Human Motion Places 205VGG  backgrounds Boundaries using Spatial & Place recognition based on nearest neighbor Network Temporal Cues descriptor voting instead of BoW. • Generating action region proposals extracting ......

Places 205VGG one human action in unconstrained videos Network • Detect revisited places using probabilistic

regardless of camera motion A Matrix of scoring of vote count per image. recognized place labels & probabilities • Demonstrating the outperformance compared ConvNet • State-of-the-art results for feature based for each action

to the state-of-the-art in two benchmarks and P(Si)=0.8 P(Si|Ai)=0 P(Ai)=0.86 localization running at > 20 Hz on Laptop

Abnormal Human two new datasets Behavior is Detected CPU. • Validating action recognition method in an Figure1. Overview of our abnormal behavior detection scenario to approach for unbiased human improve workplace safety action recognition on a sample of the Guiabot robot dataset

11:25–11:30 WeB3.5 11:30–11:35 WeB3.6

Incremental Robot Learning of New Objects Map Quality Evaluation for Visual Localization with Fixed Update Time Raffaello Camoriano*,a,b,c, Giulia Pasquale*,a,b,c, Carlo Cilibertob, Hamza Merzić, Elena Stumm, Marcin Dymczyk, Lorenzo Natalea, Lorenzo Rosascob,c and Giorgio Mettaa Roland Siegwart, and Igor Gilitschenski Autonomous Systems Lab, ETH Zurich, Switzerland a iCub Facility / b LCSL, Istituto Italiano di Tecnologia, Italy c DIBRIS, Università degli Studi di Genova, Italy

• Efficient algorithm for evaluating map quality • Motivated by visual recognition in lifelong • A way of visualizing map quality robot learning, we propose a novel incremental classification algorithm • Evaluations performed on both indoor and outdoor environments through the use of • New classes can be learned without retraining ground and flying agents from scratch or storing past data • A demonstration of the algorithm applied to • Unbalanced class proportions, occurring when generating belief for path planning under Path planning under learning new objects, are efficiently iCub learning a new uncertainty uncertainty using map quality rebalanced, significantly increasing accuracy object as the belief measure • Empirical evaluations on several benchmark datasets are presented

11:35–11:40 WeB3.7 11:40–11:45 WeB3.8

Temporal Persistence Modeling for Object Deep Learning Features at Scale for Visual Place Search Recognition Zetao Chen Russell Toris ETH Zurich, Switzerland Worcester Polytechnic Institute, USA Adam Jacobson, Niko Sünderhauf, Ben Upcroft and Michael Milford Sonia Chernova Queensland University of Technology, Australia Georgia Institute of Technology, USA Lingqiao Liu, Chunhua Shen and Ian Reid University of Adelaide, Australia • This work addresses object search for domains in which object permanence cannot be • Developed a massive place recognition- assumed. specific dataset containing 1000s of places under changing conditions; • We formalize object search as a failure analysis problem and contribute a probabilistic temporal • Trained two CNN models to learn condition- persistence modeling algorithm. invariant features for place recognition across extreme appearance conditions; • Results are reported in two domains, large scale GPS person tracking, and multi-object • By analyzing the network responses, we tracking on a mobile robot operating over a 2- provide insights into what a network learns week period. when training for place recognition.

2017 IEEE International Conference on Robotics and Automation Session WeB4 Rm. 4411/4412 Wednesday, May 31, 2017, 11:05–12:20 Sensor Fusion and Control Chair Markus Miezal, University of Kaiserslautern Co-Chair Fumin Zhang, Georgia Institute of Technology

11:05–11:10 WeB4.1 11:10–11:15 WeB4.2

Ground Substrate Classification A Stable Adaptive Attitude Estimator on SO(3) for True-North Seeking Gyrocompass System for Adaptive Quadruped Locomotion Xiaoqi Li1,2, Wei Wang1,2 and Jianqiang Yi1,2 1Institute of Automation, Chinese Academy of Sciences, Beijing, China Andrew R. Spielvogel and Louis L. Whitcomb 2 University of Chinese Academy of Sciences, Beijing, China Department of Mechanical Engineering, Johns Hopkins University, USA • Presenting a COG adjustment method and combining CPGs with a foot path planning method to improve the • Theory behind the stable adaptive attitude estimator for true-North gyrocompass system. performance of the quadruped walk gait generated by CPGs. • Preliminary simulation of a rotating system employing a KVH 1775 IMU. • Collecting the foot-ground contact force • Data suggest the convergence of the adaptive and gyroscope information during identifier’s attitude estimate to the true attitude. locomotion on different ground • Future studies will address the general-use- substrates, and classifying the ground case of simultaneously rotating and translating Attitude estimate error. substrates with the feature vector instrument configuration. extracted from the collected data using The quadruped robot Biodog locomotes on SVM algorithm. different ground substrates in walk gait.

11:15–11:20 WeB4.3 11:20–11:25 WeB4.4

Monocular Vision-based Human Following on Daily Activity Recognition with Inertial Ring and Miniature Robotic Blimp Bracelet: an Unsupervised Approach Ningshi Yao, Qiuyang Tao, Sungjin Cho and Fumin Zhang Electrical and Computer Engineering, Georgia Institute of Technology, USA Alessandra Moschetti, Laura Fiorini, Dario Esposito, Emily Anaya Paolo Dario and Filippo Cavallo Electrical and Computer Engineering, Wisconsin-Madison, Madison, USA The BioRobotics Institute, Scuola Superiore Sant’Anna, Pontedera, Italy Hongrui Zheng College of Computing, Georgia Institute of Technology, USA • Eight gestures from ADLs recognized through two IMUs on the wrist and index finger; • The first human and robotic blimp interaction • Two unsupervised approaches (KM and GMM) demonstration on Georgia Tech Miniature with inter-subject and intra-subject analysis to Autonomous Blimp (GT-MAB) discriminate gestures; • Detecting and following an uninstrumented • Comparison with two supervised algorithms human using one onboard monocular camera (RF and SVM); • Reliable and safe flying robotic platform with • Good value of Accuracy and F-measure for long flight time for Human Robot Interaction GT-MAB follows the KM inter-subject analysis (0.917 and 0.920 research human user respectively).

11:25–11:30 WeB4.5 11:30–11:35 WeB4.6

Real-time inertial lower body kinematics and Photometric Patch-based Visual-Inertial ground contact estimation at anatomical foot Odometry points for agile human locomotion Xing Zheng*, Zack Moratto†, Mingyang Li† and Markus Miezal, Bertram Taetz, Gabriele Bleser Anastasios I. Mourikis* Research group wearHEALTH, University of Kaiserslautern, Germany * Dept. of Electrical & Computer Engineering, UC Riverside, USA † Google Inc., USA

• Extension to inertial body tracking approaches • Visual-inertial odometry algorithm that directly for improving segment orientation estimation uses intensities of image patches as under locomotion measurements • Enables global translation estimation (agile • Models the irradiance at each pixel, illumi- motion possible) nation gains and biases as random variables • Direct state-less calculation without need for a • Accounts for the camera response function stationary (stance) phase Experimental results: and lens vignetting proposed direct method • Allow detection of locomotion parameters and outperforms point-based patterns • Testing on 50 datasets: 23% lower estimation method in estimation error errors compared to point-based method

11:35–11:40 WeB4.7 11:40–11:45 WeB4.8

Ergodic Exploration Using Binary Sensing for Non-Parametric Shape Estimation Robust Sensor Fusion for Finding HRI Partners in a CrowdIan Abraham, Ahalya Prabhakar, Mitra J.Z. Hartmann, Todd D. Murphey Shokoofeh Pourmehr, Jack Thomas,Mechanical Jake and Bruce, Biomedical Engineering Department, Northwestern University, United States

Jens Wawerla and Richard Vaughan School of Computing Science, Simon Fraser University, Canada

• A method for sensor fusion of human detectors, selecting the most engaging person to approach. • Demonstrating this method in a robotic attention system for distant human interaction through outdoor experiments. • Evaluating this interaction system's performance in a user study with non-expert users. Time series shape estimation of diamond and clover shape. • a ROS-based implementation, freely available Husky robot approaching • Ergodic exploration is used to demonstrate active tactile sensing for shape estimation. online: interested human. • Algorithm shows successful shape estimation that is independent of the number of objects. https://github.com/AutonomyLab/autonomy_hri.git

2017 IEEE International Conference on Robotics and Automation Session WeB5 Rm. 4511/4512 Wednesday, May 31, 2017, 11:05–12:20 Aerial Robot 2 Chair Antonio Franchi, LAAS-CNRS Co-Chair Davide Scaramuzza, University of Zurich

11:05–11:10 WeB5.1 11:10–11:15 WeB5.2

Stability of Load Lifting by a Quadrotor Safe Certificate-Based Maneuvers for Teams of under Attitude Control Delay Quadrotors Using Differential Flatness Li Wang and Magnus Egerstedt Pedro Pereira and Dimos Dimarogonas Electrical and Computer Engineering, Georiga Tech, USA Automatic Control, KTH Royal Institute of Technology, Sweden

Aaron D. Ames Mechanical and Civil Engineering, Caltech, USA

• Simple PID-like control law • Barrier certificates for safe quadrotor team • Minimally-invasive trajectory modification • Inclusion of extra term for augmenting stability to avoid collisions • Provable safety guarantee • Compensation of battery drainage and model • Algorithm implemented on a team of five uncertainties by means of integral action palm-sized quadrotors! Fig: Safe quadrotor spiral • Lower bound on attitude control gain that guarantees stability of equilibrium Quadrotor-Slung-Load System

11:15–11:20 WeB5.3 11:20–11:25 WeB5.4

Crazyswarm: UAV with Two Passive Rotating Hemispherical A Large Nano-Quadcopter Swarm Shells for Physical Interaction and Power Tethering

James A. Preiss*, Wolfgang Hönig*, C.J. Salaan, K. Tadakuma, Y. Okada, E. Takane, Gaurav S. Sukhatme, and Nora Ayanian K. Ohno and S. Tadokoro Department of Computer Science, University of Southern California, USA Graduate School of Information Sciences, Tohoku University, Japan

• System architecture for 49 Crazyflie • A new mechanism for UAV suitable in a quadcopters flying in dense formation indoors complex environment is proposed. • Off-the-shelf hardware (27 grams, palm-sized) • The whole spherical shell is cut into two • Control, state estimation, hemispherical shells to provide a gap. trajectory planning & evaluation onboard • The gap allows physical interaction and power • Minimal communication requirements: tethering while the UAV is protected and kept 17 robots per radio stable. • High-level Python scripting layer • The capabilities of the new system are verified using the experimental prototype. • All software open-source

11:25–11:30 WeB5.5 11:30–11:35 WeB5.6

Real-time Motion Planning for Aerial Videography Thrust Mixing, Saturation, and Body-Rate Control with Dynamic Obstacle Avoidance and Viewpoint for Accurate Aggressive Quadrotor Flight Optimization Matthias Faessler, Davide Falanga, and Davide Scaramuzza Tobias Naegeli1, Javier Alonso-Mora2,3, Alexander Domahidi4, Robotics and Perception Group, University of Zurich, Switzerland Daniela Rus3 and Otmar Hilliges1 ETH Zurich1, TU Delft2, MIT3, Embotech4

Improving trajectory tracking for aggressive quadrotor flight through: • A real-time receding horizon planner • Iterative thrust mixing that autonomously records scenes • Prioritizing thrust with moving targets saturation • Novel LQR body-rate • We formulate the minimization control with feedback problem under constraints as a MPC linearization and feed problem that fulfills aesthetic forward objectives, adheres to non-linear model and can be solved in real-time (20Hz).

11:35–11:40 WeB5.7 11:40–11:45 WeB5.8

Piccolissimo: Observability-Aware Trajectory Optimization for The Smallest Micro Aerial Vehicle Self-Calibration with Application to UAVs Karol Hausman, James Preiss, Gaurav Sukhatme Matthew Piccoli and Mark Yim University of Southern California, CA, USA Mechanical Engineering and Applied Mechanics, University of Pennsylvania,

USA Stephan Weiss Alpen-Adria-Universitat, Austria

• Passively stabilized, single actuator rotorcraft • Observability-aware trajectory optimization • 28 mm, 2.5 g, vertical motion version framework for nonlinear systems • 39 mm, 4.5 g, 3 DOF control version • Prediction of the state estimation quality based on the vehicle’s ego-motion • Mathematical model for passive stability and controllability presented • Novel approximation of the local observability Gramian that captures states not directly • Experimental flights demonstrate flight time visible in the sensor model and steering Maneuverable (left) and Mini (right) Piccolissimo • Experiments on simulated and real quadrotors compared to a US quarter in self-calibration and waypoint-navigation dollar coin. scenarios

2017 IEEE International Conference on Robotics and Automation Session WeB6 Rm. 4611/4612 Wednesday, May 31, 2017, 11:05–12:20 Policy Search Chair Raja Chatila, ISIR Co-Chair Ruben Martinez-Cantin, Centro Universitario de la Defensa

11:05–11:10 WeB6.1 11:10–11:15 WeB6.2

PLATO: Policy Learning using Bayesian Optimization with Adaptive Trajectory Optimization Adaptive Kernels for Robot Control

Gregory Kahn1, Tianhao Zhang1, Sergey Levine1, Pieter Abbeel123 Ruben Martinez-Cantin 1 EECS, UC Berkeley, USA Spanish University Center for Defense 2OpenAI, USA 3ICSI, USA

• Bayesian optimization (BO) is a sample • Continuous, reset-free RL algorithm that trains efficient optimization method ideal for a neural network control policy policy search. • Uses an adaptive model-predictive controller • It can be applied efficiently with complex during training simulations and real setups without prior • Avoids dangerous on-policy actions knowledge. during training • We propose a new adaptive kernel (SBO) • Prove policy has good long-term performance Simulated quadrotor for Bayesian optimization which learning to fly in a forest outperforms standard kernels. Hovering helicopter • The new kernel is specially suitable for problem from RL-challenge reward functions in robot learning.

11:15–11:20 WeB6.3 11:20–11:25 WeB6.4

Target-driven Visual Navigation in Indoor A Robust Stability Approach to Robot Scenes using Deep Reinforcement Learning Reinforcement Learning Based on a Yuke Zhu1, Roozbeh Mottaghi2, Eric Kolve2, Joseph Lim1, Parameterization of Stabilizing Controllers Abhinav Gupta2,3, Li Fei-Fei1, Ali Farhadi2,4 Stefan Friedrich and Martin Buss 1Stanford University, 2Allen Institute for Artificial Intelligence, Chair of Automatic Control Engineering, 3Carnegie Mellon University, 4University of Washington Technical University of Munich, Germany

target-driven visual navigation update • Learning target-driven visual navigation observation new observation target 2 • Goal: performance enhancement by models using end-to-end deep reinforcement act target 1 safe learning for closed-loop controllers learning observation • Approach: construct parameterization action: turn left

• AI2-THOR framework, providing a 3D Deep of stabilizing controllers based on a PD target 2 RL

environment with photo-realistic indoor scenes target 3 controller and an idealized model and a physics engine • Learning: RBF approximation of filter • Generalization to new targets, to new scenes, target coefficients and episodic optimization and from simulation to real robots • Experiment: simulation study and hardware experiment with a rigid-link

SCITOS Test environment robot

11:25–11:30 WeB6.5 11:30–11:35 WeB6.6

Reset-Free Guided Policy Search: Efficient Deep Path Integral Guided Policy Search Reinforcement Learning with Stochastic Initial States 1 2 2 2 William Montgomery Yevgen Chebotar , Mrinal Kalakrishnan , Ali Yahya , Adrian Li , 1 3 CSE, University of Washington, USA Stefan Schaal , Sergey Levine 1 2 3 Anurag Ajay, Chelsea Finn, Pieter Abbeel, Sergey Levine University of Southern California, USA X, USA Google Brain, USA

EECS, University of California, Berkeley, USA • Learn complex neural network policies that map camera images directly to motor torques • Deep reinforcement learning can learn complex with guided policy search. policies, but is often sample inefficient • Guided policy search (GPS) methods are • Model-free local trajectory optimization with efficient, but require consistent initial states PI2 for tasks with discontinuous dynamics and • We extend GPS to more general case of non-differentiable costs. stochastic initial states • • Learns faster/more stably than standard GPS, RFGPS outperforms GPS Sample global neural network policies and significantly outperforms other deep RL and standard deep RL using raw observations to train on random task instances and increase generalization. Door opening and

Pick-and-place tasks

11:35–11:40 WeB6.7 11:40–11:45 WeB6.8

Deep Reinforcement Learning for Robotic Optimized Vehicle-Specific Trajectories for Cooperative Manipulation with Async Off-Policy Updates Process Estimation by Sensor-Equipped UAVs

Shixiang Gu and Ethan Holly Juliane Euler and Oskar von Stryk Google Brain, University of Tübingen, University of Cambridge Dept. of Computer Science, Technische Universität Darmstadt, Timothy Lillicrap and Sergey Levine Germany, www.sim.tu-darmstadt.de Google DeepMind, UC Berkeley • Sequential optimum design approach for • Learned manipulation policies using estimating parameters of an atmospheric Normalized Advantage Function for dispersion process model continuous control Q-learning. • Demonstrated accelerated learning through • Provides optimized waypoint sequences for parallelized data collection across multiple cooperating sensor-equipped UAVs robotic platforms. • Decentralized data-driven online control • Learned policies on real-world robots for Door opening with Q opening a door in a fixed location. scheme coupling parameter estimation, learning policy waypoint calculation, and vehicle control

• Effectiveness demonstrated in simulations

2017 IEEE International Conference on Robotics and Automation Session WeB7 Rm. 4711/4712 Wednesday, May 31, 2017, 11:05–12:20 Robotic Manipulation Chair Rüdiger Dillmann, Karlsruhe Institute of Technology (KIT) Co-Chair Metin Sitti, Max-Planck Institute for Intelligent Systems

11:05–11:10 WeB7.1 11:10–11:15 WeB7.2

Efficient Kinematic Planning for Mobile Design and Actuation of a Magnetic Millirobot Manipulators with Non-holonomic Constraints under a Constant Unidirectional Magnetic Field Using Optimal Control Markus Giftthaler, Farbod Farshidian, Timothy Sandy, Onder Erin1,2, Joshua Giltinan1,2, Luke Tsai2, and Metin Sitti1,2 1Max Planck Institute for Intelligent Systems, Stuttgart, Germany Lukas Stadelmann and Jonas Buchli 2Mechanical Engineering Department, Carnegie Mellon University, USA Agile & Dexterous Robotics Lab ETH Zürich, Switzerland

• MRI-compatible 3-DOF translational and • Constrained Sequential Linear Quadratic rotational actuation of an untethered magnetic robot on a 2D surface Optimal Control for Kinematic Trajectory Planning • Magnet orientation is independent from robot orientation. • Efficiency through linear time-complexity • Translation and rotation of the magnetic • Constraint-consistent kinematic feedback laws robot is accomplished by using planar • 100 Hz replanning frequency in a real-world magnetic pulling forces. Depiction of the magnetic robot experiment on a tracked mobile manipulator • The dependence of the coupling ratio with the magnetic actuation signal and robot dimensions is studied.

11:15–11:20 WeB7.3 11:20–11:25 WeB7.4

Empirical Evaluation of Common Contact Optimal, Sampling-Based Manipulation Planning Models for Planar Impact Philipp S. Schmitt, Werner Neubauer, Wendelin Feiten, Nima Fazeli, Elliott Donlon, and Alberto Rodriguez Mechanical Engineering Department, MIT, USA Kai M. Wurm and Georg v. Wichert Siemens Corporate Technology, Germany Evan Drumwright

Toyota Research Institute, USA Wolfram Burgard Autonomous Intelligent Systems, University of Freiburg, Germany

• Experimental evaluation of contact model • Robotic manipulation requires reasoning about prediction for planar impact. a sequence of grasps, placements and robot motions. • A post-hoc hybrid model outperforms any • These sequences form paths in the combined single model, indicating consensus models configuration space of robot and object. may outperform individual models. • We propose a manipulation planner that determines these paths in an asymptotically • Perturbation analysis demonstrates the Roadmap construction for optimal manner. a pick and place task limits of predictions of models and possible Example of a planar impact bifurcation of predictions. • Extensive simulations show significant outperformance of an existing approach.

11:25–11:30 WeB7.5 11:30–11:35 WeB7.6

Design of a Simplified Compliant Integrating Motion and Hierarchical Fingertip Anthropomorphic Robot Hand Grasp Planning Tuomas Wiste ELI Beamlines, CZ Joshua A. Haustein, Kaiyu Hang and Danica Kragic Robotics, Perception, and Learning Lab Michael Goldfarb KTH Royal Institute of Technology, Sweden Center for Intelligent Mechatronics, Vanderbilt University, USA

• Self-contained and compliantly actuated • We integrate hierarchical fingertip grasp with • Low grasp impedance motion planning for grasping in clutter. • 5 motors • Our algorithm simultaneously explores a robot's hand-arm configuration space as well • Novel bidirectional underactuated finger as a grasp space. design that biases actuator force toward finger flexion • The grasp search is guided by proximity to collision-free configurations explored in the • Additive manufactured motion planning process. • Low cost and weight • High durability • Readily applied to variety of platforms

11:35–11:40 WeB7.7 11:40–11:45 WeB7.8

Analyzing Achievable Stiffness Control Bounds A Two-Fingered Robot Gripper of Robotic Hands With Coupled Finger Joints with Large Object Reorientation Range Walter G. Bircher and Aaron M. Dollar Prashant Rao, Gray Thomas, Luis Sentis and Ashish D. Department of Mechanical Engineering and Materials Science Deshpande Yale University, USA Mechanical Engineering, The University of Texas at Austin, USA Nicolas Rojas Dyson School of Design Engineering, Imperial College, UK

• Tendon-driven multi-DOF robotic fingers have coupled joint stiffness. • Proposed passivity analysis of achievable stiffness control bounds for such fingers. • Results show that maximum controller stiffness is bounded by passive stiffness. • Such analysis can lead to intelligent mechanical design of robotic fingers with intrinsic stability.

2017 IEEE International Conference on Robotics and Automation Session WeB8 Rm. 4613/4713 Wednesday, May 31, 2017, 11:05–12:20 Humanoid Robots 1 Chair J.W Grizzle, University of Michigan Co-Chair Ko Yamamoto, University of Tokyo

11:05–11:10 WeB8.1 11:10–11:15 WeB8.2

Robust Walking by Resolved Viscoelasticity Control Explicitly Considering Structure- Context-Driven Movement Primitive Adaptation Variability of a Humanoid 1 1 1,2 Ko Yamamoto Daniel Wilbers and Rudolf Lioutikov and Jan Peters 1 Department of Mechanical Engineering, University of Tokyo, Japan Intelligent Autonomous Systems, TU Darmstadt, Germany 2Max Planck Institute Tuebingen

• The author extends the previous work on the resolved viscoelasticity control (RVC) by • We optimize trajectory distributions to considering structure-variability. environment changes while staying close to • The method now considers an open kinematic human demonstrations chain in the single support phase and a closed • Simultaneously learning activations for kinematic chain in the double support phase. different primitives allows us to adapt to • This extension helps realize stable and robust unseen situations walking motion on uneven terrains. • Our optimization is a new REPS variant, which Avoiding an obstacle with • The proposed method is validated using Walking on a slope is realized bounds the KL-Divergence to demonstrations. a context-adapted forward dynamics simulations. by the RVC method. • Applied within the ProMP framework primitive.

11:15–11:20 WeB8.3 11:20–11:25 WeB8.4

Dynamic Manipulability of the Center of Mass Supervised Learning for Stabilizing Underactuated Bipedal Robot Locomotion, with Outdoor Experiments on the Wave Field Morteza Azad1, Jan Babic2 and Michael Mistry3 1University of Birmingham, UK 2Jozef Stefan Institute, Slovenia 3University of Edinburgh, UK

• Tool to study, analyse and measure physical ability of robots to accelerate the CoM.

• Velocity independent metric which depends only on configuration and inertial parameters.

Xingye Da, Ross Hartley and Jessy W. Grizzle • Evaluates a robot’s physical ability independent of any choice of controller.

• Proper tool to study physical ability of legged robots to balance. Manipulability with different weighting matrices

11:25–11:30 WeB8.5 11:30–11:35 WeB8.6

A Study of Nonlinear Forward Models for Invariant Funnels for Dynamic Walking Underactuated Dynamic Walking Robots

Yangwei You, Chengxu Zhou and Nikos Tsagarakis Justin Z. Tang, A. Mounir Boudali and Ian R. Manchester Department of Advanced Robotics, Istituto Italiano di Tecnologia, Italy Australian Centre for Field Robotics (ACFR), University of Sydney, Australia Zhibin Li School of Informatics, University of Edinburgh, United Kingdom

• Constrained COM height is no longer • This paper addresses the problem of finding required resulting more natural gaits; useful invariant funnels for dynamic walking • Leg dynamics is taken into account; robots. • Leg kinematics is included which • We show that for typical models of walking eliminates the knee singularity issue; robots the construction of such funnels can be significantly simplified. • The change of mechanical energy due to ground impact is included; • Hardware verification of the resulting funnels Two nonlinear models derived are also presented. • Actuator dynamics can be incorporated from a full robot model. into the forward simulation. Top: walking robot used Bottom: verified funnel

11:35–11:40 WeB8.7 11:40–11:45 WeB8.8

Robust Bipedal Locomotion Control Based on The Energetic Benefit of Robotic Gait Selection Model Predictive Control and Divergent A Case Study on the Robot RAMone Component of Motion Milad Shafiee-Ashtiani, Aghil Yousefi-Koma and Nils Smit-Anseeuw, Rodney Gleason, Ram Vasudevan Masoud Shariat-Panahi and C. David Remy Center of Advanced Systems and Technologies(CAST), Mechanical Engineering, University of Michigan, USA University of Tehran, Iran.

• We employ a single MPC which uses a combination of CoP and CMP modulation • Energy optimal gaits found across range of and step adjustment to design a robust walking controller. speeds for realistic model of RAMone • we exploit the concept of time-varying • Compass gait walking is optimal at low speeds DCM to generalize our walking controller • Spring mass running with backwards knees is for walking on uneven surfaces. optimal at high speeds • Performance verified on push recovery • Both gaits show striking similarity to biological simulations for walking on surfaces with a equivalents very limited feasible area for stepping (such as rock)

2017 IEEE International Conference on Robotics and Automation Session WeB9 Rm. 4811/4812 Wednesday, May 31, 2017, 11:05–12:20 Biologically-Inspired Robots 1 Chair Inaki Rano, Ulster University Co-Chair Fengzhen Tang, Shenyang Institute of Automation， Chinese Academy of Sciences

11:05–11:10 WeB9.1 11:10–11:15 WeB9.2

Path Following for a Biomimetic Underwater A Drift Diffusion Model of Biological Source Vehicle Based on ADRC Seeking for Mobile Robots Inaki Rano and Kongfatt Wong-Lin Rui Wang, Shuo Wang, Yu Wang, and Chong Tang Intelligent Systems Research Centre, Ulster University, UK State Key Laboratory of Management and Control for Complex Systems, Mehdi Khamassi Institute of Automation, Chinese Academy of Sciences, China ISIR, University Pierre & Marie Curie, France • Animals excel at target reaching even under • Biomimetic underwater vehicles (BUVs), adverse conditions stronger disturbance rejection, more excellent • We extend a model of biological source maneuverability, and quieter actuation seeking to include sensor noise • Close-loop control law for a BUV propelled by • The analysis of the corresponding non-linear undulatory fins to ensure path following SDE shows: • Line-of-sight guidance system decouples the • Differences between the deterministic system to steer the surge speed and the Example of animal target model and stochastic average reaching in adverse course respectively • Bound in the dispersion (2nd moment) conditions • Active disturbance rejection control is used in development of surge speed controller and • Results of interest for: bio-robotics, low-cost course controller robots, micro robots

11:15–11:20 WeB9.3 11:20–11:25 WeB9.4

Closed-Loop Path Following of Traveling Wave High speed trajectory control using an experimental Rectilinear Motion Through Obstacle-Strewn Terrain maneuverability model for an insect-scale legged robot Benjamin Goldberg, Neel Doshi, and Robert J Wood Alex H. Chang and Patricio A. Vela Harvard University, Cambridge, MA, USA School of ECE, Georgia Institute of Tech., United States

• Derived dynamics of a traveling wave rectilinear gait lead to a mapping • Holonomic trajectory following from gait parameter space to averaged steady-behavior body velocity with a legged microrobot (a) • The system bears resemblance to a fixed forward-velocity unicycle • Towards a highly maneuverable, • Average body curvature serves as the control input driving angular autonomous, insect-scale robot velocity of the system • Using this approach, motion planning and path following through various obstacle arrangements are successfully completed (b) (a) Harvard Ambulatory MicroRobot (b) Holonomic trajectory following

11:25–11:30 WeB9.5 11:30–11:35 WeB9.6

Learning Multisensory Cue Integration on Adaptive Lévy-taxis for Odor Source Localization Mobile Robots in Realistic Environmental Conditions Chong ZHANG and Bertram E. SHI Department of Electronic and Computer Engineering, Romain Emery, Faezeh Rahbar, Ali Marjovi, Alcherio Martinoli Hong Kong University of Science and Technology, Hong Kong Distributed Intelligent Systems and Algorithms Laboratory, Jochen TRIESCH EPFL, Switzerland Frankfurt Institute for Advanced Studies, Germany

Wheels Inertial Visual Inputs Inputs Inputs A • Designed a new algorithm called Adaptive Lévy- Sensory • We have proposed a bio-inspired robotic Inputs Taxis (ALT) to address odor plume tracking. system to learn multisensory integration and eye movements • ALT compared with three well-established image stabilization. (learned) Afferent algorithms inspired by moth behaviors (casting,  ()V  ()H • Our model learns autonomously and accounts Inputs surging towards the wind, and spiraling). for the development of both multimodal + + Eye • All the methods thoroughly evaluated in a wind sensory processing and motor action.  ()V  ()H System tunnel under various environmental conditions • Instead of giving fixed weights to the different + + (different wind speeds and odor source u ()V u ()H

sensory cues, our model learns the weights AS AS Sensorimotor concentrations). automatically. z ()V z ()H Transformation Sample trajectories by all 4 … … • ALT shows consistently good performances y y y y algorithms: (a) casting (b) I W V E under all environmental conditions. … Efference surge-cast, (c) spiral-surge (d) x Copy V ALT

11:35–11:40 WeB9.7 11:40–11:45 WeB9.8

From Rousettus aegyptiacus (bat) Landing to A Prey-Predator Model for Efficient Robot Robotic Landing: Regulation of CG-CP Distance Tracking Using a Nonlinear Closed-Loop Feedback Fengzhen Tang and Bailu Usman A. Syed, Alireza Ramezani and Seth Hutchinson State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese University of Illinois Urbana-Champaign, USA Academy of Science, China Soon Jo Chung Daxiong Ji Graduate Aerospace Laboratory, California Institute of Ocean College, Zhejiang University, China Technology, USA • Bats perform agile maneuvers such as • Novel robotic tracking strategy inspired by the roosting (landing) with great composure. hunting strategies of predators • Reconstructing bat landing maneuvers with a • Heading and speed of pursuer automatically Micro Aerial Vehicle (MAV) called Allice. adjusted according to the position and velocity • Allice is capable of adjusting the position of its of prey CG with respect to its CP using a nonlinear • Three prediction methods for missing closed-loop feedback. Allice:1-DoF robotic observations of prey with various trajectory platform used to validate types • The input-output feedback linearization based the landing model of a bat Tracking trajectory nonlinear control law, enables attitude • Tracking simulations under two scenarios regulations through variations in CG-CP demonstrating the efficiency of the proposed distance. tracking scheme

2017 IEEE International Conference on Robotics and Automation Session WeB10 Rm. 4911/4912 Wednesday, May 31, 2017, 11:05–12:20 Medical Robots and Systems 5 Chair Max Q.-H. Meng, The Chinese University of Hong Kong Co-Chair Ren Luo, National Taiwan University

11:05–11:10 WeB10.1 11:10–11:15 WeB10.2

Development of a Tele-Nursing Mobile In Vivo Tracking and Measurement of Pollen Manipulator for Remote Care-Giving in Tube Vesicle Motion Chengzhi Hu, Jan T. Burri, Naveen Shamsudhin and Bradley J. Quarantine Areas Nelson Peter Moran, Qingyuan Dong, Ryan Shaw and Kris Hauser Electrical and Computer Department, Duke University, USA Institute of Robotics and Intelligent Systems, ETH Zurich, Switzerland Hannes Vogler and Ueli Grossniklaus Zhi Li Robotics Engineering, Worcester Polytechnic Institute, USA Department of Plant and Microbial Biology University of Zurich, Switzerland • We developed a Tele-Robotic Intelligent • Optical flow methods with the KLT tracker are Nursing Assistant (TRINA) in response studied to solve the difficulties for in vivo to the need of patient-caring for highly vesicle tracking and its motion detection in infectious diseases (e.g. Ebola). growing pollen tubes. • TRINA is developed to be human-safe, • Grid filtering is used to eliminate the effect of versatile, usable by novices, rapidly bidirectional movement of vesicles, resulting in assembled, and relatively inexpensive. Tele-Robotic Intelligent an improved estimate of vesicle flow speed. • We evaluated TRINA’s capability on 26 Nursing Assistant • Both the optical and fluorescent images can frequently performed nursing tasks in a (TRINA) be processed. simulated patient room at the Nursing School of Duke University.

11:15–11:20 WeB10.3 11:20–11:25 WeB10.4

Autonomous Scanning for Endomicroscopic Introducing BigMag – A Novel System for 3D Mosaicing and 3D Fusion Magnetic Actuation of Flexible Surgical Manipulators

1 1 1 Lin Zhang, Menglong Ye, Petros Giataganas, Michael Hughes and J. Sikorski , I. R. Dawson , A. Denasi , E.E.G. Hekman1 and S. Misra1,2 Guang-Zhong Yang 1University of Twente, The Netherlands 2University of Groningen The Hamlyn Centre for Robotic Surgery, Imperial College London, UK and University Medical Center Groningen, The Netherlands

• Automation of surgical robots provides • We present an array of rotating augmented ability, allowing surgeons to electromagnetic coils for magnetic steering of perform surgical task more accurately and surgical continuum manipulators. intuitively. • We derive, calibrate and validate a • An autonomous system for endomicroscopy mathematical model of the magnetic field scanning and mosaicing using the da Vinci within the workspace of the device. surgical robot is proposed. • The field is estimated with an average error of • Laparoscopic and microscopic images are 15.21 % (magnitude) and 9.40º (direction). used to servo the robot. • We demonstrate user-controlled steering of • 3D fusion of surface reconstruction and continuum manipulators using BigMag. cellular-scale endomicroscopy mosaic images.

11:25–11:30 WeB10.5 11:30–11:35 WeB10.6

Experimental Validation of the Pseudo-Rigid- Robot Assisted Tapping Control for Body Model of the MRI-Actuated Catheter Therapeutical Percussive Massage Applications Tipakorn Greigarn, Russell Jackson, Ren C. Luo, Chin-Po Tsai and Kai-Chun Hsieh Taoming Liu, M. Cenk Cavusoglu International Center of Excellence on Intelligent Robotics and Automation Department of Electrical Engineering and Computer Science Research(iCeiRA), Nation Taiwan University, Taiwan Case Western Reserve University, USA

• This paper presents experimental validation •A well massage tapping could be determined and parameter optimization of the Pseudo- by force, contact time and impulse. Rigid-Body (PRB) model of the MRI-Actuated • Cartesian impedance control is utilized to Catheter. control both the position and force during • The parameters of the PRB model is first robotic massage. optimized to improve its accuracy without • Virtual target points are implemented to adjust increasing the degrees of freedom of the the force to ingratiate different desired forces. model. Experimental setup of the Catheter • Our work demonstrates that the robotic • The PRB models with standard and optimal tapping motion for therapeutical percussive parameters are validated with experimental massage is feasible. data.

11:35–11:40 WeB10.7 11:40–11:45 WeB10.8

Visual Servoing Controller for Time-Invariant 3D Analysis of joint and hand impedance during Path Following with Remote Centre of Motion teleoperation and free-hand task execution Constraint Bassem Dahroug and Brahim Tamadazte and Nicolas Andreff Jacopo Buzzi, Cecilia Gatti, Giancarlo Ferrigno, Elena De Momi FEMTO-ST Institute, AS2M department, Univ. Bourgogne Franche- Department of Electronics, Informatics and Bioengineering, Comte/CNRS/ENSMM, Besançon, France Politecnico di Milano, Italy

• Formulate a geometric method for describing • Non disruptive hand stiffness matrix the Remote Centre of Motion (RCM) in the estimation during simulated suturing tasks task-space based on users’ arm kinematics acquisition • Perform the RCM movement along side the • Comparison between free-hand and path following controller under the vision teleoperated tasks execution with serial and guidance parallel link master device in terms of: • Show the stability of the path following • Task performance controller Experimental system configuration with the • Maximal stiffness

various reference frames. • Stiffness orientation

2017 IEEE International Conference on Robotics and Automation Session WeB11 Rm. 4813/4913 Wednesday, May 31, 2017, 11:05–12:20 Service Robotics 1 Chair Shaojie Shen, Hong Kong University of Science and Technology Co-Chair Pablo Valdivia y Alvarado, Singapore University of Technology and Design, MIT

11:05–11:10 WeB11.1 11:10–11:15 WeB11.2

The Robotanist: A Ground-Based Agricultural Deep Fruit Detection in Orchards Robot for High-Throughput Crop Phenotyping Suchet Bargoti and James Underwood Australian Centre for Field Robotics, The University of Sydney, Australia Tim Mueller-Sim, Merritt Jenkins, Justin Abel, and George Kantor The Robotics Institute, Carnegie Mellon University, United States of America • Fruit detection on outdoor orchard images using the Faster R-CNN detection architecture. • Design of a novel robotic ground-based • Analysis of data augmentation strategies sensor platform for crop phenotyping. and transfer learning between orchards. • Capable of autonomously navigating below • Modified framework for detecting over the canopy of row crops such as sorghum or 1000 fruit on high resolution images. maize. • Published datasets for different fruit and • Utilizes a custom manipulator to collect 1 an annotation toolbox . contact measurements of the plant. • Deployed and tested in several Sorghum Detecting apples, mangoes bicolor test plots across South Carolina, USA. and almonds.

1http://data.acfr.usyd.edu.au/ag/treecrops/2016-multifruit

11:15–11:20 WeB11.3 11:20–11:25 WeB11.4

Autonomous Sweet Pepper Harvesting for Counting Apples and Oranges with Deep Protected Cropping Systems Learning: A Data Driven Approach Christopher Lehnert, Andrew English, Christopher McCool, Adam W. Tow and Tristan Perez Steven W Chen, Shreyas S Shivakumar, Sandeep Dcunha* School of Electrical Engineering and Computer Science Jnaneshwar Das, Edidiong Okon, Chao Qu Queensland University of Technology, Australia Camillo J Taylor, and Vijay Kumar GRASP Laboratory, University of Pennsylvania, USA *University of Masschusetts, Amherst, USA • We present a new robotic harvester

(Harvey) that can autonomously harvest sweet pepper in protected cropping • http://label.ag, a web-based crowd-sourced environments. labeling framework to quickly collect ground- • Scans, detects crop, selects grasp and truth labels and store in SVG format cutting poses and then attaches and • Fully Convolutional Network (FCN) to detaches fruit using novel harvesting tool segment fruit clusters from images • Field trials in a real greenhouse • Convolutional Network (CNN) to count Nighttime Apple: environment demonstrate a 58% harvest number of fruit in each cluster Left original image; success rate. Right segmented fruit clusters Above is Harvey which can harvest sweet peppers autonomously.

11:25–11:30 WeB11.5 11:30–11:35 WeB11.6

Improving Octree-Based Occupancy Maps using Feasibility Study of IoRT Platform Environment Sparsity with Application to Aerial Robot Navigation “Big Sensor Box” Ryo Kurazume1, Kazuto Nakashima1, Akihiro Kawamura1 Jing Chen and Shaojie Shen 1 ISEE, Kyushu University, Japan ECE Department, HKUST, Hong Kong, China Yoonseok Pyo2, Tokuo Tsuji3 2 ROBOTIS Co., Ltd, Korea 3 • We equipped the octree-based occupancy Mechanical Engineering, Kanazawa University, Japan map with two operations: • ROS-based CPS (Cyber Pysical System) 1. accelerated ray tracing update software platform named “ROS-TMS ver.4.0” 2. efficient volumeric occupacny query is introduced.

• Hardware platform for an informationally • It significantly outperforms OctoMap, structured environment named “Big Sensor taking advantages of the octree structure Box” is proposed. • it is integrated in a complete navigation • Robot service experiments using ROS-TMS pipeline for autonomous flight in cluttered Illustration of the Big Sensor Box oocupancy map and the and Big Sensor Box are successfully environments generated trajectory for conducted. autonomous flight

11:35–11:40 WeB11.7 11:40–11:45 WeB11.8

High-Precision Microinjection Autonomous Robotic System using Non-Destructive of Microbeads into C. elegans Evaluation methods for Bridge Deck Inspection Trapped in a Suction Microchannel Tuan Le, Spencer Gibb, Nhan Pham, Hung La, Logan Falk, and Masahiro Nakajima1, Yuki Ayamura1, Masaru Takeuchi1, Tony Berendsen Naoki Hisamoto1, Strahil Pastuhov1, University of Nevada, Reno, Nevada, USA 1 2,3 3 Yasuhisa Hasegawa , Toshio Fukuda , Qiang Huang 1Nagoya University, Japan, 2Meijo University, Japan, 3 . This paper presents an autonomous Beijing Institute of Technology, China robotic system integrated with multiple • High-precision microinjection of Inlet non-destructive evaluation (NDE) sensor fluorescent micro-gel beads into C. elegans for bridge deck inspection. Caenorhabditis elegans (C. elegans) ① . Automated rebar detection algorithm trapped in a suction microchannel ③ Suction hole based on machine learning for ground • The focal plane of the target nerve ② penetrating radar (GPR) is developed. ④ Pipette axon matches that of the fluorescent . The robot is able to provide automated microbead in the microinjection tool, ⑤ bridge deck condition maps during • The head-first navigation alignment of inspection. C. elegans along the microchannel Outlet was controlled by electrotaxis. Bridge Deck Inspection Robot Microchannel

2017 IEEE International Conference on Robotics and Automation Session WeC1 Rm. 4011 Wednesday, May 31, 2017, 14:30–15:45 Tendon/Wire Robotics Chair Sunil Agrawal, Columbia University Co-Chair Domenico Campolo, Nanyang Technological University

14:30–14:35 WeC1.1 14:35–14:40 WeC1.2

A Feasibility Study on Tension Control of Wire-Tension Control using Compact Planetary geared Elastic Actuator Bowden-Cable Based on a Dual-Wire Scheme Jihoo Kwak, Chan Lee, Junyoung Kim, Shinyoon Kim and Sehoon Oh • Introduction • Conclusions Useok Jeong and Kyu-Jin Cho Tension control of rope, wire or tape has been In this research, a tension control system by a important, but difficult issues for wide fields. novel SEA called cPEA is proposed. The School of Mechanical and Aerospace Engineering, experiment conducted to verify the SEA(Series Elastic Actuator) makes sensing and performance of the algorithm, and the Seoul National University, Korea controlling output force available through its results has validated the following points. Elasticity. 1) The proposed cPEA can successfully Compact Planetary-geared Elastic Actuator measure and control the tension (cPEA) is utilized for the precise control of wire tension, and its performance is verified through 2) The propsed tension controller can control experiments. the tension of wire even under dynamic tension references 3) It is shown that cPEA can be utilized for • Control and Experiment sensor-less wire tension control. DOB-Based tension controller is implemented and conditional impedance compensator is cascaded. W-shaped experimental setup is proposed to evaluate the tension control • Changing friction of the Bowen-cable depending on the bend angle of The result verifies that tension is controlled the cable restricts the size and simple design of the robot. to track the reference with highly suppressed fluctuation and overshoot. • A novel bend sensing method is proposed that takes advantage of the Motion Control Lab, DGIST 1 position error of the Bowden-cable. • Output tension of the Bowden-cable can be controlled without the output force sensor using the friction compensation with the bend estimation.

14:40–14:45 WeC1.3 14:45–14:50 WeC1.4

Design of a 6-DOF Collaborative Robot Arm with Position and Orientation Control of Counterbalance Mechanisms Passive Wire-Driven Motion Support System Won-Bum Lee, Sang-Duck Lee, and Jae-Bok Song Using Servo Brakes School of Mechanical Engineering, Korea University, Republic of Korea Yasuhisa Hirata, Ryo Shirai, and Kazuhiro Kosuge Department of Robotics, Tohoku University, Japan CBM: Counterbalance mechanism • Collaborative robot arm with 6 DOFs. • Multi-DOF counterbalance mechanism • We developed a passive wire-driven motion CBM 1 based on double parallelogram linkage is CBM 2 support system without any motors. embedded inside the robot links. • The system can adjust the wire tension by • The use of counterbalance mechanisms controlling 7 servo brakes. saves the energy consumption of the robot in various tasks. • It ensures a safe interaction as the main driving force is applied by the user. • It can support the user while following a target form by a passive control method considering Passive Wire-Driven System both position and orientation. for Tennis Beginner

14:50–14:55 WeC1.5 14:55–15:00 WeC1.6

Passive Returning Mechanism for Twisted String Using Compliant Leg Designs for Impact Attenuation Actuators of Airdrop Landings of Quadruped Robots Muhammad Usman, Bhivraj Suthar, Hyunseok Seong, Igor Gaponov and Jee Hwan Ryu Yeeho Song and Dirk Luchtenburg Mechanical Engineering, KoreaTech, Rep. of Korea Mechanical Engineering, Cooper Union for the Advancement of Elliot Hawkes Science and Art, USA Mechanical Engineering, University of California, Santa Barbara, CA, USA • Two passive buckling return mechanisms • Compliant legs are designed for both walking are proposed for bi-directional actuation of and airdrop impact attenuation. twisted string actuators • Lumped element models are used for design • Utilizing the beam buckling concept, a nearly and analysis. constant stiffness spring is made which • Experiments confirm that these models are assists TSA in untwisting useful for initial design. • Dynamic and kinematic properties of both • Experiment show that compliant legs perform mechanisms are experimentally evaluated and compared better than rigidly actuated legs with active Picture of the Robot used for the Research damping. Passive return mechanism : slit mechanism (right) | Telescopic mechanism (left)

15:00–15:05 WeC1.7 15:05–15:10 WeC1.8

Designing Anthropomorphic Robot Hand with Performance Evaluation of a New Design of Active Dual-Mode Twisted String Actuation Cable-Suspended Camera System Mechanism and Tiny Tension Sensors Saeed Abdolshah, Univ. of Padova, Italy Damiano Zanotto, Stevens Inst. of Technology, USA Seok-Hwan Jeong, Kyung-Soo Kim and Soohyun Kim Giulio Rosati, Univ. of Padova, Italy Mechanical Engineering, KAIST, Ref. Korea Sunil Agrawal, Columbia University, USA

• We investigated the application of adaptive • Design of Anthropomorphic Robot Hand cable-driven robots to cable-suspended camera systems • Miniature Power transmission mechanism (wide operating area) • Results show that the adaptive design outperforms the traditional one in terms of • Twisted String Actuation (TSA) mechanism dexterity, elastic stiffness index, and stiffness • Tiny tension sensor based on Photo- magnitude. interrupter • A method is presented to derive the smallest Adaptive cable-suspended • Force feed-back control adaptive design capable of achieving ideal camera system dexterity and target levels of stiffness within a Robot Hand based on given workspace. TSA mechanism

2017 IEEE International Conference on Robotics and Automation Session WeC2 Rm. 4111 Wednesday, May 31, 2017, 14:30–15:45 Motion and Path Planning 1 Chair Daniel D. Lee, University of Pennsylvania Co-Chair Leslie Kaelbling, MIT

14:30–14:35 WeC2.1 14:35–14:40 WeC2.2

Path Following Control of Skid-Steered Wheeled Mobile Adaptive Motion Planning Robots at Higher Speeds on Different Terrain Types with High-Dimensional Mixture Models Jinwook Huh, Bhoram Lee, and Daniel D. Lee Goran Huskić and Sebastian Buck and Andreas Zell GRASP, University of Pennsylvania, USA Chair of Cognitive Systems, University of Tübingen, Germany • Adaptive approach to fast sampling-based motion planning by learning Gaussian mixture models (GMMs) of collision and • A new nonlinear path following collision-free regions in configuration spaces control law for skid-steered robots at • Rapidly adaptation to environmental higher speeds (up to 2.5 m/s) is changes by using inverse kinematics to proposed transform the parameters of the GMMs • Robotnik Summit XL is used in the • The transformed model is continually experimental evaluation updated and refined as the RRT planning • Comparison with two state-of-the-art algorithm proceeds in real-time algorithms is made • Computationally efficient compared with • Experiments are conducted in three traditional approaches on a number of The prediction and update different terrain scenarios (grass, experimental robot arm planning scenarios vinyl, and macadam)

14:40–14:45 WeC2.3 14:45–14:50 WeC2.4

On-line Trajectory Planning with Time-variant Motion Focused Model-Learning and Planning for Constraints for Industrial Robot Manipulators Non-Gaussian Continuous State-Action Systems Zi Wang Stefanie Jegelka Ran Zhao and Svetan Ratchev Leslie Pack Kaelbling Tomás Lozano-Pérez Institute for Aerospace Manufacturing Computer Science and Artificial Intelligence Laboratory, Faculty of Engineering, University of Nottingham, UK Massachusetts Institute of Technology, USA • A new framework for model learning • An algorithm is proposed to generate trajectories with non-constant and planning for continuous state- kinematic constraints. action and non-Gaussian transitions • Dealing with an arbitrary state of motion whose values exceed the • Flexible interface for learning models kinematic constraints. • Planner BOIDP uses learned models • Simple and computational efficiency. efficiently via “lazy access” and focused computation on relevant • An extension of the current cubic-polynomial trajectory planning library. A quasi-static pushing problem: the states and actions pusher has a velocity controller with • Theoretical and empirical results low gain, resulting in non-Gaussian shows the asymptotic optimality and transitions. the effectiveness of our method.

14:50–14:55 WeC2.5 14:55–15:00 WeC2.6

Dynamic Risk Tolerance: Motion Planning by Densification Strategies for Anytime Motion Balancing Short-term and Long-Term Stochastic Planning over Large Dense Roadmaps Dynamic Predictions Hao-Tien Chiang1, Baisravan HomChaudhuri2, Abraham Vinod2, Shushman Choudhury, Oren Salzman, Sanjiban Choudhury Meeko Oishi2 and Lydia Tapia1 and Siddhartha Srinivasa 1Computer Science Dept., University of New Mexico, USA The Robotics Institute, Carnegie Mellon University, USA 2 Electrical & Computer Engineering Dept., University of New Mexico, USA • Search increasingly dense r-disk Edge batching G Vertex batching subgraphs of the complete roadmap ) Hybrid batching • Dynamic Risk Tolerance (DRT) planning balances |E| • Edge Batching (EB): Use all vertices and avoidance of imminent collision with long-term plans ✓ ◆ add edges by increasing r |V| in environments with stochastic dynamic obstacles 2 guaranteed

• Vertex Batching (VB): Increase number Number of Edges( solution • DRT achieves this through a time-varying upper V|) RRT with constant bound of vertices and use all edges each time f (| bound on acceptable collision probability of states of collision probability easy nmin hard n along a path • Hybrid Batching (HB): Add both vertices Number of Vertices(|V|) and edges based on dispersion • Obstacle prediction done by Forward Stochastic Theoretical Analysis Reachable sets and Monte Carlo simulation • We empirically validate our analysis on EB has better effort-quality tradeoff random scenarios in and and on for low-clearance, and • Empirically evaluated in crowded environments with manipulation planning problems VB for high-clearance problems. fast and stochastically moving obstacles tries to RRT with DRT HB balance.

15:00–15:05 WeC2.7 15:05–15:10 WeC2.8

Stochastic Functional Gradient for Motion Consistent Sparsification for Efficient Decision Making Planning in Continuous Occupancy Maps Under Uncertainty in High Dimensional State Spaces Khen Elimelech Gilad Francis, Lionel Ott and Fabio Ramos Robotics and Autonomous Systems Program (TASP), Technion, Israel The School of Information Technologies, University of Sydney, Australia Vadim Indelman Department of Aerospace Engineering, Technion, Israel

• Functional gradient path optimisation in • Using a sparse version of the information continuous occupancy maps – instead of matrix to examine candidate actions. sampling-based methods (RRT, PRM, etc.) • The sparse approximation is action-consistent,

i.e. has no influence on the action selection. • Utilises stochastic samples as path support to ensure optimisation convergence. • Maintaining the same quality of solution, while reducing the computational complexity. • Expolits continuous map for fast, online • A significant improvement in runtime in a gradient computation. SLAM simulation. Sparsification Example

2017 IEEE International Conference on Robotics and Automation Session WeC3 Rm. 4311/4312 Wednesday, May 31, 2017, 14:30–15:45 Visual Servoing Chair Peter Corke, QUT Co-Chair Francois Chaumette, Inria Rennes-Bretagne Atlantique

14:30–14:35 WeC3.1 14:35–14:40 WeC3.2

A Unified Leader-Follower Scheme for Mobile Visual Servoing through mirror reflection Robots with Uncalibrated On-board Camera Eric Marchand1 and François Chaumette2 Dejun Guo1, Hesheng Wang2, Weidong Chen2, 1Université de Rennes, IRISA, Rennes France 2 Ming Liu, Zeyang Xia, and Kam K. Leang1 Inria, IRISA, Rennes, France 1University of Utah Robotics Center, USA 2 Department of Automation, Shanghai Jiao Tong University, China • Complete theoretical background of visual servoing through planar mirror reflection • Adaptive image-based leader-follower C xP • Able to control a mirror mounted on a robot formation control scheme for mobile robots  f  Z l Z f F end-effector • Uncertain camera parameters for either l FC P  Camera X f l • Proof that, in practice, only 3 mirror d.o.f. are perspective camera or omnidirectional camera Ff Leader X f C y P actually controllable mirror • Lyapunov approach used for stability analysis Follower • Experiments using a mirror mounted on the • Experimental results show good performance end-effector of a 6 d.o.f robot validates the proposed approaches.

camera

14:40–14:45 WeC3.3 14:45–14:50 WeC3.4

A robotic control framework for 3-D quantitative Towards markerless visual servoing of grasping ultrasound elastography tasks for humanoid robots Pedro Vicente1, Lorenzo Jamone2,1, Alexandre Bernardino1 Pedro A. Patlan-Rosales and Alexandre Krupa 1 INRIA Rennes-Bretagne Atlantique, France ISR, Técnico-Lisboa, Univ. de Lisboa, Lisbon, Portugal 2 ARQ, School of Electronic Engineering and Computer Science, Queen Mary University of London, UK

 Robot control based on elastic 3-D • Eye-to-hand 3D Position-Based Visual information from a volume of interest Servoing on the iCub humanoid robot: (VOI) inside a tissue. • Markerless estimation of the hand pose  Teleoperation of the ultrasound probe orientation using a haptic device to • 3D model-based hand pose estimation with GPU increase the field of view (FOV). • Sequential Monte Carlo parameter estimation  Automatic tracking of stiff tissue in the VOI to keep it in the center of the FOV • Online calibration of the eye-to-hand map while teleoperation is performed. • Open-loop vs Visual Servo Control A precise grasping task by the iCub Humanoid • Grasping task was successful with closed-loop Robot • Position error decreased 2X

14:50–14:55 WeC3.5 14:55–15:00 WeC3.6

Exploring Convolutional Networks for End-to- Image-based Visual Servoing with Unknown End Visual Servoing Point Feature Correspondence Aseem Saxena, Harit Pandya, Gourav Kumar, Ayush Gaud Aaron McFadyen and Peter Corke and K. Madhava Krishna Science and Engineering Faculty (SEF), Queensland University of Technology, Australia International Institute of Information Technology, Hyderabad, India. Marwen Jabeur Institute for Flight Mechanics (IFR), University of Stuttgart, Germany • We aim to learn visual feature representations suitable for servoing tasks in unstructured and unknown • New image-based visual servoing approach environments. that simultaneously solves the feature correspondence and control problem • We present an end-to-end learning based approach for visual servoing in diverse • Feature tracking is not required by considering scenes using convolutional neural the problem exclusively in the control domain. Given a goal image and current networks. • Preliminary experimental results using a small image seen by the robot, our • Our approach is able to do visual servoing network estimates the velocities unmanned quadrotor are presented. in the wild where the knowledge of required to move the robot towards Visual control of a quadrotor with camera parameters and scene geometry the goal. non-unique image features is not available apriori. (unknown feature correspondence)

15:00–15:05 WeC3.7 15:05–15:10 WeC3.8

Visual servoing in an optimization framework Determining the Singularities for the for the whole-body control of humanoid robots Observation of Three Image Lines

1 1,2 3 Don Joven Agravante, Giovanni Claudio, Sébastien Briot , Philippe Martinet and François Chaumette 1 Lab. des Sciences du Numérique de Nantes (LS2N), CNRS, Nantes, France Fabien Spindler, and François Chaumette 2 Ecole Centrale de Nantes, Nantes, France Lagadic group, Inria Rennes - Bretagne Atlantique, France 3 INRIA at IRISA, Rennes, France

• A visual servoing task is formulated • For the first time, we provide the singularity within a QP for whole-body control cases in the observation of three image lines by using a concept named the “hidden robot” • Visual inequality constraints account • We prove that in the most general case, for occlusion or field-of-view limits singularities appear when the origin of the • Tests on HRP4 and Romeo observed object frame is either on a quadric or a cubic surface Relative motion of the • In simpler cases where at least two lines belong camera wrt the three to the same plane, these two surfaces can observed orthogonal lines degenerate into simpler geometrical loci (e.g. and singularity location planes, cylinders, lines).

2017 IEEE International Conference on Robotics and Automation Session WeC4 Rm. 4411/4412 Wednesday, May 31, 2017, 14:30–15:45 SLAM 1 Chair Sebastian Scherer, Carnegie Mellon University Co-Chair Guillermo Gallego, University of Zurich

14:30–14:35 WeC4.1 14:35–14:40 WeC4.2

PennCOSYVIO: A Challenging Visual Inertial MSGD: Scalable Back-end Odometry Benchmark for Indoor Magnetic Field-based GraphSLAM

Bernd Pfrommer, Nitin Sanket, and Kostas Daniilidis Chao Gao and Robert Harle Dept. of Computer and Information Science, University of Pennsylvania, USA Computer Laboratory, University of Cambridge, UK Jonas Cleveland Cognitive Operational Systems LLC, USA

• Benchmark/dataset for hand-held VIO • A back-end system optimised for very dense algorithms sequence-based loop closures • VI sensor, Google Tango, GoPro Hero4 • Extensive real datasets were used to evaluate • Indoor/outdoor transitions, 150m path against state-of-the-art algorithms length • Code and datasets with high-accuracy • Ground truth from fiducial markers groundtruths are open sourced glass, repetitive structures

14:40–14:45 WeC4.3 14:45–14:50 WeC4.4

Direct Monocular Odometry Using Multi-UAV Collaborative Monocular SLAM Points and Lines Patrik Schmuck and Margarita Chli Shichao Yang, Sebastian Scherer Robotics Institute, Carnegie Mellon University, USA • Centralized collaborative monocular SLAM; the server is a ground station and the agents are aerial vehicles. • A real-time monocular visual odometry • Two-way communication between incorporating points and edges, especially agents & server, handling time delays suitable for texture-less environments. • Real-time visual odometry runs • Provide an uncertainty analysis and uninterrupted on each agent, probabilistic fusion of points and lines in both expensive tasks run on server (e.g. tracking and mapping. place recognition, map optimization) • Develop analytical edge based regularization • Outperform or comparable to existing VO in • Server maintains agents’ experiences, Map constructed by two aerial vehicle agents. many datasets ensuring consistent, shared maps Following detection of scene overlap, the server fuses their experiences into a common map, enabling the agents’ collaboration.

14:50–14:55 WeC4.5 14:55–15:00 WeC4.6

Attention and Anticipation in Fast 4D Crop Monitoring: Visual-Inertial Navigation Spatio-Temporal Reconstruction for Agriculture

Luca Carlone and Sertac Karaman Jing Dong and Byron Boots and Frank Dellaert Laboratory for Information & Decision Systems, MIT, USA College of Computing, Georgia Institute of Technology, USA John Gary Burnham and Glen Rains • We propose an attention mechanism for Department of Entomology, University of Georgia, USA Visual Inertial Navigation (VIN)

• An approach for 4D reconstruction for • Our attention mechanism selects a small fields with continuously changing scenes, subset of relevant visual features to targeting crop monitoring applications. reduce the computation in VIN • A robust data association algorithm for • The selection is aware of the motion of images with highly duplicated structures the robot, picking features that remain in selected features and significant appearance changes. the field of view during aggressive motion X discarded features • A ground vehicle field dataset with ground truth crop statistics for evaluating spatio- • The selection can be implemented tracked features temporal reconstruction and crop efficiently and enjoys suboptimality During a sharp left turn, our feature selector picks monitoring algorithms. guarantees via submodularity features on the left-hand side, which will remain in the field of view during the maneuver

15:00–15:05 WeC4.7 15:05–15:10 WeC4.8

Active Exposure Control for Robust Visual EVO: A Geometric Approach to Event-based Odometry in HDR Environments 6-DOF Parallel Tracking and Mapping in Real-time

Zichao Zhang, Christian Forster, Davide Scaramuzza Henri Rebecq*, Timo Horstschaefer*, Guillermo Gallego Robotics and Perception Group, University of Zurich, Switzerland and Davide Scaramuzza Robotics and Perception Group, University of Zurich, Switzerland • We propose an active exposure control method to maximize the information for VO • Event cameras are novel sensors with low- • We propose a robust gradient-based image latency (1μs), high-dynamic range (140 dB), quality metrics and optimize the metrics based and no motion blur on the response function of the camera • EVO is a 6-DOF pose tracking and 3D • Evaluation of different exposure compensation reconstruction algorithm for event cameras, methods in VO that runs in real-time on a CPU • Improved performance in challenging HDR • Robust to high-speed motions and challenging environments is achieved by combining the high-dynamic range lighting conditions proposed active exposure control and the Trajectory and semi-dense exposure compensation in VO 3D map generated by EVO * equal contribution using events only.

2017 IEEE International Conference on Robotics and Automation Session WeC5 Rm. 4511/4512 Wednesday, May 31, 2017, 14:30–15:45 Aerial Robot 3 Chair Alexis Lussier Desbiens, Université de Sherbrooke Co-Chair Kenjiro Tadakuma, Tohoku University

14:30–14:35 WeC5.1 14:35–14:40 WeC5.2

Bringing Mobile Robot Olfaction to the Next Design and Experiments for a Transformable Dimension – UAV-based Remote Sensing of Solar-UAV Gas Clouds and Source Localization Ruben D’Sa, Travis Henderson, Devon Jenson, Michael Calvert, Thaine Heller, Bobby Schulz, Jack Kilian, and Nikolaos Papanikolopoulos P. P. Neumann1, H. Kohlhoff1, D. Hüllmann1, A. J. Lilienthal2, and M. Kluge1 Department of Computer Science and Engineering, University of Minnesota, 1BAM, Germany. 2Örebro University, Sweden. USA • Novel robotic platform for aerial remote gas sensing that combines • Discussion of the airframe design and » open-path gas detector with performance. » 3-axis gimbal for stabilizing and aiming • Evaluation of a variable pitch propulsion • Outdoor evaluation of gas sensing system methodology. and aiming performance • Aerial platform enables • Energetic results from solar flight testing. » tomographic reconstruction of gas Fixed-wing (top) and quad- plumes and rotor states (bottom). » localization of gas sources

14:40–14:45 WeC5.3 14:45–14:50 WeC5.4

Design and Implementation of a Quadrotor Tail- Sampling-based Motion Planning for sitter VTOL UAV Active Multirotor System Identification

Ximin Lyu, Haowei Gu, Ya Wang, Rik Bähnemann, Michael Burri, Enric Galceran, Zexiang Li, Shaojie Shen, and Fu Zhang Roland Siegwart, and Juan Nieto ECE, Hong Kong University of Science and Technology, China Autonomous Systems Lab, ETH Zürich, Switzerland

• Vehicle design including: addressing wind • We present a real-time capable MAV motion disturbance, vibration attenuation, and landing planning framework for parameter gear design. identification experiments. • We use rapidly-exploring random belief trees • Modeling, controller design with aerodynamic (RRBT) to find a maximum informative feed forward, and simulation result trajectory. • Our approach is extendable to other platforms An automatically generated • Indoor test and outdoor test to show the The quadrotor tail-sitter and calibration problems. MAV calibration routine vehicle performance prototype • Experiments in simulation and on the real platform show the feasibility and repeatability of our approach.

14:50–14:55 WeC5.5 14:55–15:00 WeC5.6

Model-based Transition Optimization Model-Based Wind Estimation for for a VTOL Tailsitter a Hovering VTOL Tailsitter UAV

S. Verling, T. Stastny, G. Bätting and R. Siegwart Youssef Demitri, Sebastian Verling, Thomas Stastny, Amir Melzer, ASL, ETH Zurich, Switzerland Roland Siegwart K. Alexis Autonomous Systems Lab, ETH Zurich, Switzerland University of Nevada, Reno, United States of America

•Vertical take-off and landing (VTOL) UAV • Closed Loop trajectory optimization combines multi-copter and fixed-wing UAV capabilities. • Transition from cruise to hover •The vertical wing in hover configuration is highly • Minimal altitude deviation susceptible to wind disturbances. • Verified in simulation and Experiments •A wind estimator has been developed, based on an aerodynamic model of the aircraft. VTOL Tailsitter UAV •The estimator results have been successfully validated on outdoor flight data.

15:00–15:05 WeC5.7 15:05–15:10 WeC5.8

Air Flow Modelling Using Turbulent and Laminar Design of a Passive Vertical Takeoff and Landing Characteristics for Ground and Aerial Robots Aquatic UAV V. Hernandez B.1, T. P. Kucner1, E. Schaffernicht1, P. P. Neumann2, H. Fan1 and A. J. Lilienthal1 Richard-Alexandre Peloquin, Dominik Thibault and 1Örebro University, Sweden. 2BAM, Germany. Alexis Lussier Desbiens Airflow map • Air Flow Modeling (AFM) conveys Department of Mechanical Engineering, Université de Sherbrooke, Canada useful information to UAV navigation and surveillance robots • Design of a flying wing UAV able to dive • Novel algorithm that models airflow as a linear combination of turbulent land and passively takeoff from lakes and laminar components • Development of a dynamic model of the ‒ Joint representation PDFs (wind passive takeoff sequence speed/direction) and turbulence indicators • Prediction of diving accelerations for ‒ AFM-specific extrapolation from sparse various impact speeds measurement locations • Validation in real world environments • Prototype capable of repeated cycles of ‒ Experiments with UAV and ground robots flying, diving, self-righting, and takeoff Time lapse of the takeoff sequence ‒ The proposed algorithm outperforms conventional extrapolation techniques with a high stability to parameter selection Turbulence map Predicted joint PDF

2017 IEEE International Conference on Robotics and Automation Session WeC6 Rm. 4611/4612 Wednesday, May 31, 2017, 14:30–15:45 RGB-D Perception Chair Kazunori Umeda, Chuo University Co-Chair Tom Drummond, Monash University

14:30–14:35 WeC6.1 14:35–14:40 WeC6.2

Joint Pose and Principal Curvature Refinement De-noising, Stabilizing and Completing 3D Using Quadrics Reconstructions On-the-go using Plane Priors Maksym Dzitsiuk1,2, Jürgen Sturm2 Andrew Spek and Tom Drummond Robert Maier1, Lingni Ma1, Daniel Cremers1 Electrical Engineering, Monash University, Australia 1Technical University of Munich, Germany 2Google

• A method that jointly optimizes for • Real-time 3D reconstruction of indoor curvature and pose estimates for RGB-D environments on mobile devices data using locally fit surface quadrics. • Detect planar surfaces by directly • We demonstrate the improvement in fitting planes to voxel volumes performance of solving both tasks, by • Find global planes by merging local jointly optimizing, instead of separately planes • Can be used in a tracking pipeline to • Noise reduction and hole filling in greatly reduce the drift in tracking. incomplete 3D reconstructions • Object-level and semantic segmentation (e.g. walls)

14:40–14:45 WeC6.3 14:45–14:50 WeC6.4

Fast Task-Specific Target Detection via Graph Fast Odometry and Scene Flow from Based Constraints Representation and Checking RGB-D Cameras based on Geometric Clustering Mariano Jaimez1,2, Christian Kerl2, Wentao Luan, Yezhou Yang, Javier Gonzalez-Jimenez1 and Daniel Cremers2 ISR, Univ. of Maryland, USA CIDSE, Arizona State University, USA 1Dept. of System Engineering and Automation, University of Malaga, Spain Cornelia Fermüller, John S. Baras 2Dept. of Computer Science, Technical University of Munich, Germany CV lab, Univ. of Maryland, USA ISR, Univ. of Maryland, USA

• Scene segmented into static/moving parts to compute odometry and • Introduces target description early into the segmentation scene flow, respectively. and candidate proposal process for object detection • K-Means-based geometric clustering to accelerate scene flow estimation. • Proposes a method to optimize the constraints checking order and proves its performance • Overall runtime: 80 milliseconds on multi-core CPU (code on Github). • Demonstrate framework’s performance by one rigid one non-rigid object detection • Derives a human-robot interaction application from our detection framework.

14:50–14:55 WeC6.5 14:55–15:00 WeC6.6

Tracking Objects with Point Clouds RISAS: A Novel Rotation, Illumination, Scale from Vision and Touch Invariant Appearance and Shape Feature Gregory Izatt, Geronimo Mirano, Kanzhi Wu, Ravindra Ranasinghe and Gamini Dissanyake Edward Adelson, and Russ Tedrake University of Technology Sydney, Australia CSAIL, Massachusetts Institute of Technology, USA Xiaoyang Li and Yong Liu Zhejiang University, China • The proposed RGB-D features, RISAS, consists a keypoint detector and a feature descriptor by utilizing geometry and appearance information in both phases; • This paper highlights the importance • The GelSight sensor allows dense, tactile geometric sensing of designing hand-crafted detector • We combine tactile geometry with RGB-D camera data by treating and descriptor coherently in principle; • RISAS shows superior each as a point cloud • A dataset is built for RGB-D feature performance compared with • We accurately track small objects in real-time during manipulation evaluation under rotation, illumination existing RGB-D feature under and significant occlusion and scale variations; different variations;

15:00–15:05 WeC6.7 15:05–15:10 WeC6.8

An Analytical Lidar Sensor Model Learning Depth-aware Deep Representations for Based on Ray Path Information Robotic Perception Lorenzo Porzi1,2, Samuel Rota Bulò2, Adrian Penate-Sanchez3, Alexander Schaefer, Lukas Luft, Wolfram Burgard Elisa Ricci1,2, Francesc Moreno Noguer4 Department of Computer Science, University of Freiburg, Germany 1University of Perugia, 2Fondazione Bruno Kessler, 3University College, 4IRI CSIC-UPC

• State-of-the-art grid mapping algorithms • We introduce DaConv, a general-purpose neglect the distances that a Lidar beam travels CNN block which exploits depth to learn scale- within each map cell. aware feature representations. • We present a more general approach that • Main idea: similar objects at different leverages the whole ray path information. distances should activate the same neurons. • It models the interaction between laser and • We achieve this by locally tying the scale of environment in a probabilistic way as Our off-road robot in the convolutional kernels to the measured depth. exponential decay process. forest. • We demonstrate DaConv on affordance • This is particularly advantageous in cluttered detection, object coordinate regression and environments. contour detection in RGB-D images.

2017 IEEE International Conference on Robotics and Automation Session WeC7 Rm. 4711/4712 Wednesday, May 31, 2017, 14:30–15:45 Manipulation Planning 1 Chair Florent Lamiraux, CNRS Co-Chair Kevin Lynch, Northwestern University

14:30–14:35 WeC7.1 14:35–14:40 WeC7.2

Manipulation planning: Noninteracting Constrained Motion Planning Addressing the crossed foliation issue and Control for Robot Manipulators Manuel Bonilla and Antonio Bicchi Joseph Mirabel and Florent Lamiraux Istituto Italiano di Tecnologia LAAS-CNRS, Univ. de Toulouse, France Lucia Pallotino Università di Pisa

• Constraint Graph: the most general • In constrained compliant robot manipulators formulation of manipulation planning problems. there exist a description for the complementary spaces describing rigid body • Crossed foliation issue: although manipulation motions and interaction forces planning has been extensively studied for the • Geometric control approaches enables the past 20 years, we highlight some unexplored design of a completely decoupled control theoretical issues and propose practical scheme for the aforementioned spaces solutions. Compliant robot • It in turn allows us to plan motion using state- manipulators under of-the-art methods using relaxed constraints environment interactions

14:40–14:45 WeC7.3 14:45–14:50 WeC7.4

Multi-Bound Tree Search for Logic-Geometric Programming in Cooperative Manipulation Open World Grasping with Laser Selection Domains Marc Toussaint Abraham Shultz, James Kuczynski, Holly Yanco Machine Learning & Robotics Lab, University of Stuttgart, Germany Department of Computer Science, UMass Lowell, USA Manuel Lopes Marcus Gualtieri, Andreas ten Pas, Robert Platt Instituto Superior Técnico, Universide de Lisboa, Portugal College of Computer and Information Science, Northeastern University, USA

• An optimization-based formulation of • Our system grasps objects that the user concurrent, multi-agent cooperative indicates with a laser pointer. manipulation (task and motion planning) • 88% object selection success and 90% grasp • Jointly (locally) optimal paths and action success in stationary tests. parameters for all agents over the full • 89% object selection success and 72% grasp manipulation sequence success driving the scooter between tests. • Multiple levels of bounds to better direct tree • Average time to grasp and return objects of search over symbolic decisions 128s (minimum 44s, max 374s). • Efficient path optimization across kinematic switches, where configuration space dimensionality varies over time

14:50–14:55 WeC7.5 14:55–15:00 WeC7.6

C-LEARN: Learning Geometric Constraints from Planning and Control for Dynamic, Demonstrations for Multi-Step Manipulation Nonprehensile, and Hybrid Manipulation Tasks in Shared Autonomy Claudia Pérez-D’Arpino and Julie A. Shah J. Zachary Woodruff and Kevin M. Lynch Massachusetts Institute of Technology Mechanical Engineering, Northwestern University, USA

• C-LEARN: a method of learning from demonstrations that supports the use of hard • We propose a method for motion geometric constraints for planning multi-step planning and feedback control of functional manipulation tasks with multiple hybrid manipulation tasks end effectors in quasi-static settings. • We apply the framework to plan • C-LEARN supports multi-step tasks with a sequence of motions for multiple end effectors; manipulating a block with a • reasons about SE(3) volumetric and CAD planar 3R manipulator constraints, and, Optimus robot executes • We demonstrate experimental • offers a principled way to transfer skills tasks with learned results for a block resting on a between robots with different kinematics. geometric constraints manipulator moving through different contact modes

15:00–15:05 WeC7.7 15:05–15:10 WeC7.8

Parts Assembly Planning under Uncertainty with Feasibility Evaluation of Object Manipulation by a Humanoid Robot Simulation-Aided Physical Reasoning Based on Recursive Estimation of the Object’s Physical Properties

Sung-Kyun Kim, Maxim Likhachev Masaki Murooka, Shunichi Nozawa, Yohei Kakiuchi, Kei Okada and Masayuki Inaba The Robotics Institute, Carnegie Mellon University, USA (The University of Tokyo, Japan)

•Search-based motion planning in foliated • Improve the autonomy of whole- belief space with uncertainty coordinates body manipulation by humanoid •Physics-based simulator for more • Calculate the likelihood of object’s reasonable state transition model properties from sensor information • Update physical properties •Informative but inadmissible heuristics: estimation by Bayesian method Contact between objects to reduce relative • Evaluate feasibility probability of pose uncertainty object operation • Robot selects proper operation •MHA* (Multi-Heuristic A*) search that depending on object’s properties accepts inadmissible heuristics with theoretic guarantee on sub-optimality bound

2017 IEEE International Conference on Robotics and Automation Session WeC8 Rm. 4613/4713 Wednesday, May 31, 2017, 14:30–15:45 Humanoid Robots 2 Chair Katja Mombaur, Heidelberg University Co-Chair Tomomichi Sugihara, Graduate School of Engineering, Osaka University

14:30–14:35 WeC8.1 14:35–14:40 WeC8.2

Real-Time Pursuit-Evasion Passivity-based Control of Underactuated Biped with Humanoid Robots Robots within Hybrid Zero Dynamics Approach Hamid Sadeghian1, Christian Ott2, Gianluca Garofalo2, and Gordon Cheng3 1Engineering Department, University of Isfahan, Isfahan, Iran M. Cognetti, D. De Simone, F. Patota, N. Scianca, L. Lanari, G. Oriolo 2Institute of Robotics and Mechatronics, DLR, Germany Sapienza University of Rome, Italy 3Institute for Cognitive Systems, Faculty of Electrical Engineering and Information Technology, Technical University of Munich, Munich, Germany

•A pursuer heads for collision with an evader that tries to escape • A passivity-based controller for a planar biped with one degree of underactuation is designed •Both robots are controlled by a fast within HZD approach. replanning scheme based on vision • It is aimed to preserve the natural dynamics of •Trajectory generation uses a the system in the transverse dynamics in feedback-controlled unicycle as contrast to input-output linearization method template model which cancels these dynamics. •Simulations and experiments with A 7-link planar underactuated • The asymptotic stability of the periodic orbit in system with zero ankle torque NAOs reveal a limit cycle behavior lower dimensional state space is extended to in stance foot. the full dimensional space by a Lyapunov stability analysis of the full-order system.

14:40–14:45 WeC8.3 14:45–14:50 WeC8.4

Control of Humanoid Robot Motions with Dynamic Multi-contact Transitions for Humanoid Impacts: Numerical Experiments with Reference Robots using Divergent Component of Motion Spreading Control M Rijnen, E de Mooij, N v/d Wouw, A Saccon, H Nijmeijer George Mesesan Johannes Englsberger Dept. of Mechanical Engineering, TU/e, The Netherlands Bernd Henze Christian Ott S Traversaro and F Nori German Aerospace Center (DLR), Germany iCub facility, IIT Genova, Italy • The motion planner computes feasible step • Reference spreading stabilizes desired robot durations and timing of contact transitions motions with impacts • The Center of Mass trajectory has an • The reference motion is extended about analytical form impact times to create multiple segments • A feasible solution is found within seconds by • Switching between segments occurs when a using a simplified robot model contact transition is detected • The controller combines a passivity-based • Validation: balancing on one foot while approach with Divergent Component of Motion impacting a wall with a hand control.

14:50–14:55 WeC8.5 14:55–15:00 WeC8.6

Smooth-Path-Tracking Control of a Biped Robot Experimental Evaluation of Deadbeat Running at Variable Speed Based on Dynamics Morphing on the ATRIAS Biped

Hiroshi Atsuta1, Haruki Nozaki2 and Tomomichi Sugihara1 William Martin, Albert Wu, and Hartmut Geyer The Robotics Institute, Carnegie Mellon University, USA 1 Grad. School of Enginerring, Osaka University, Japan

2 Yamazaki Mazak Corporation, Japan • We investigate how well control strategies developed for the theoretical spring mass • A biped control to follow an arbitrary smooth curved path is proposed model transfer to real-world bipedal robots. • The controller is designed with respect to a moving frame fixed to the • Our controller regulates running using model- robot based force control during the stance phase • Advantageous features include: and deadbeat foot placement during flight. (i) The referential path can be given as an arbitrary smooth curve • We find that our controller produces one-step, deadbeat tracking of velocity changes up to (ii) The motion references can be given from the first-person viewpoint ±0.2 m/s at speeds up to 1.0 m/s. of the robot ATRIAS, a human-scale • The control tolerates larger velocity changes, bipedal robot with no (iii) The states can be observed from the egocentric frame of reference higher speeds, and ground height changes up external sensing for the robot to ±15 cm, but requires more steps.

15:00–15:05 WeC8.7 15:05–15:10 WeC8.8

Influence of compliance modulation Singularity-tolerant inverse kinematics for on human locomotion bipedal robots

Yue Hu, Katja Mombaur Salman Faraji and Auke Jan Ijspeert Optimization in Robotics and Biomechanics (ORB), Biorobotics Lab, EPFL, Switzerland Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Germany • Extensive analysis of singularity in: • A floating-based humanoid • Motion capture data mapped on a 2D • For balancing tasks human model with variable stiffness • Inverse kinematics proposed: springs in the leg joints. • Nonlinear optimization • Three walking environments: level ground, • Joint position/velocity limits slope and stairs.

• Punishing stiffness with minimization of • Approaching singularities stiffness derivatives and stiffness jumps Motion capture data are mapped as objective functions. to the human model considering • No vibration, instability Example: In-place rotation whole-body dynamics and • Fitting errors computed for different • Escaping from singularities and lateral shift, feasibility constraints Asymmetric weighting factors on the objective function. • No delays stretch of the legs

2017 IEEE International Conference on Robotics and Automation Session WeC9 Rm. 4811/4812 Wednesday, May 31, 2017, 14:30–15:45 Biologically-Inspired Robots 2 Chair Joonbum Bae, UNIST Co-Chair jinhua zhang, Xi'an jiaotong university

14:30–14:35 WeC9.1 14:35–14:40 WeC9.2

CPG-based Control of Smooth Transition for Body Design and Control of an Inchworm-Inspired Shape and Locomotion Speed of a Snake-like Robot Soft Robot with Omega-Arching Locomotion Zhenshan Bing, Long Cheng, Mingchuan Zhou, and Alois Knoll Huaxia Guo, Jinhua Zhang, Tao Wang, Department of Informatics, Technical University of Munich, Germany Yuanjie Li, Jun Hong, Yue Li Kai Huang State Key Laboratory for manufacturing systems Engineering, School of Data and Computer Science, Sun Yat-sen University, China Xi’an Jiaotong University, China

• A light-weight CPG model is designed for • An inchworm soft robot with one single locomotion control of snake-like robot. The online execution time and converge speed are silicone square tube being the body. compared with other well-known CPG models. • Achieving the Omega-Arching locomotion with • The body shape and locomotion speed transitions in rolling gait are simulated based only one pressure. on the proposed CPG model. • Both the design and control are very simple The inchworm soft robot • Compared with the sinusoid-based method, a Snake-like robot is smooth transition process can be achieved, slithering forward • The work illustrate some potential value of without generating undesired movement or using soft materials. abnormal torque.

14:40–14:45 WeC9.3 14:45–14:50 WeC9.4

Guidelines for the Design and Control of Implementing Caterpillar Inspired Roll Control of Bio-inspired Hovering Robots a Spherical Robot Abhra Roy Chowdhury, A. Vibhute, G. S. Soh, S. H. Foong Hamid Vejdani and David Boerma and Sharon Swartz and K. L. Wood and Kenneth Breuer Temasek Laboratories, Engineering Product Development Pillar School of Engineering, Brown University, USA Singapore University of Technology and Design Singapore 487372

• Caterpillars (Pleuruptya ruralis) use ballistic • Hummingbirds and insects (small dynamical rolling gaits to curl rapidly backward into a systems) hover with constant wingspan wheel to escape while birds and bats (larger systems) hover with varying wingspan. • Rolling gait is generated by a CPG (Central Pattern generator). Processed signal output is • The preferred mode of hovering is studied desired roll angle, directly drives segment joint for systems with different dynamical (dc motors in robot). characteristics. • A robust Nonlinear Feedback Controller • The relations between wing kinematics, corrects the produced rolling gait angle in the actuator limitation and energy consumption Rolling gait in a caterpillar Two hovering mechanisms presence of uncertainties and disturbances are presented. mimicked by a spherical for different dynamical (surface friction and actuator noise) robot characteristics

14:50–14:55 WeC9.5 14:55–15:00 WeC9.6

Design of Hair-like Appendages and their Development and Validation of Modeling Coordination Inspired by Water Beetles for Framework for Interconnected Tendon Networks Steady Swimming on the Water Surface Taylor D. Niehues and Ashish D. Deshpande Bokeon Kwak1, and Joonbum Bae1 Dept. of Mechanical Engineering, The University of Texas at Austin, USA 1Department of Mechanical Engineering, UNIST, Republic of Korea Raymond J. King and Sean Keller V 2 Oculus & Facebook, USA 2,F • Inspired by the locomotion of water beetles, two t1 types of robots (one-pair-leg, two-pair-leg) with  2,H • A generalized model of tension novel hair-like appendages were built. transmission through a network of t t • The hair-like appendages could passively adjust 2 3 branching tendons is developed the frontal projected area of the robot to achieve • Simulations of the human finger extensor drag-powered swimming. mechanism capture realistic dynamic • The coordination between the two pairs of legs tension variations and passive joint was investigated for steady swimming, and its coupling effects locomotion was compared with the robot with • Experiments with a robotic finger illustrate one pair of legs. that the model is able to accurately predict • By properly coordinating the legs, the velocity force transformation between the muscles fluctuation was fairly attenuated, and more and fingertip energy-efficient swimming was achieved. t1 t2 t3

15:00–15:05 WeC9.7 15:05–15:10 WeC9.8

VAM: hypocycloid mechanism for Mechanical Specialization of Robotic Limbs efficient bio-inspired robotic gaits

Espen Knoop1,2,3, Andrew Conn2,3, Jonathan Rossiter2,3 Nathan Cahill, Yi Ren, and Thomas Sugar 1Disney Research, Zurich, Switzerland Mechanical Engineering, Arizona State University, United States of America 2University of Bristol, UK 3Bristol Robotics Laboratory, UK

• A constrained optimization problem is • VAM module produces reciprocating presented which tunes the kinematics of a output of continuously-variable multiactuator robotic limb amplitude, using a drive input and a • Power consumption is minimized locally, and control input several design families are presented. • Modular building-block for • Manipulability is constrained along the task biomimetic robotic gaits trajectory via the condition number of the Kinematically Tuned • Demonstrated with VAMOS: Two- Jacobian. Hybrid-Serial Robot Limb motor hexapod that walks and turns • A gear ratio optimization routine with realistic with arbitrary curvature constraints is also presented.

2017 IEEE International Conference on Robotics and Automation Session WeC10 Rm. 4911/4912 Wednesday, May 31, 2017, 14:30–15:45 Surgical Robotics 1 Chair Jorge Solis, Karlstad University / Waseda University Co-Chair Leonardo Mattos, Istituto Italiano di Tecnologia

14:30–14:35 WeC10.1 14:35–14:40 WeC10.2

Pose optimization of a C-arm imaging device to Preoperative Planning for the Multi-arm reduce intraoperative radiation exposure of staff and Surgical Robot using PSO-GP-based patient during interventional procedures Performance Optimization Nicolas Loy Rodas*, Julien Bert**, Dimitris Visvikis**, Michel de Fan Zhang1, Zhiyuan Yan2 and Zhijiang Du2 Mathelin* and Nicolas Padoy* 1Imperial College London, United Kingdom *ICube, University of Strasbourg, CNRS, IHU Strasbourg, France 2Harbin Institute of Technology, China ** LaTIM, INSERM, CHRU Brest, France • X-ray guided interventions expose • The surgical workspace is divided patient and clinicians to harmful ionizing and the subspaces are assigned with radiation. different weights. • Method for active radiation exposure • Three metrics are proposed to reduction by exploiting the robotic evaluate the performance of the capabilities of imaging devices. multi-arm surgical robot. • Reduction of patient and staff exposure • A combination of Particle Swarm while maintaining target visibility. Optimization (PSO) and Gaussian • Optimization in quasi real-time thanks to Process (GP) is proposed to locate a novel and fast radiation simulation the port placement and robot method. positioning.

14:40–14:45 WeC10.3 14:45–14:50 WeC10.4

Magnetic Laser Scanner MagNex – Expendable robotic surgical tooltip for Endoscopic Microsurgery

Alperen Acemoglu and Leonardo S. Mattos Karthik Chandrasekaran, Akhil Sathuluri and Asokan Thondiyath Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy Department of Engineering Design, Indian Institute of Technology Madras, India

• Proposed design has 3 degrees of freedom – • Enables laser scanning in narrow workspaces pitch, yaw and grasp • High-speed laser scanning • Proposed tooltip design is magnetically coupled to an actuator through a sealed shaft • Magnetic interaction between coils and the to mitigate biofouling permanent magnet attached to an optical fiber. • Monolithic tooltip has a modified serpentine • For precise micromanipulation the optical fiber flexure for increased buckling strength and off Prototype of the complete tool to perform surgical tissue ablations. axis stiffness Endoscopic Laser Scanner • The laser spot can be controlled with 35µm • The single use tool tip is pluggable to tool precision. shaft assembly and provides modularity

14:50–14:55 WeC10.5 14:55–15:00 WeC10.6

Modeling and Analysis of a Laparoscopic Implicit Gaze-Assisted Adaptive Motion Scaling Camera's Interaction with Abdomen Tissue for Highly Articulated Instrument Manipulation Gauthier Gras, Konrad Leibrandt, Piyamate Wisanuvej, Reza Yazdanpanah A. and Xiaaolong Liu and Jindong Tan Petros Giataganas, Carlo A. Seneci, Menglong Ye, Mechanical Aerospace Biomedical Eng., University of Tennessee, USA Jianzhong Shang, Guang-Zhong Yang The Hamlyn Centre for Robotic Surgery, Imperial College London, UK

• Mechanical modeling of abdomen bulk tissue • By fusing eye tracking data with hand motion (skin, fat, muscle, connective tissues) and instrument information, user intention to • Camera-tissue interaction mathematical model reach distant targets can be recognized. • Interaction finite element study for various • Motion scaling is modulated accordingly, linear and rotational speeds without compromising safety or precision. • Damage prevention, fall prevention and online • Custom-designed instruments mounted on tissue properties measurement system Online force estimation robotic arms are used to test the system. and damage prevention • The control scheme aims to maximize the system dexterity of the system even when the external arms cannot provide sufficient triangulation.

15:00–15:05 WeC10.7 15:05–15:10 WeC10.8

A Continuum Robot and Control Interface for Utilizing Elasticity of Cable Driven Surgical Surgical Assist in Fetoscopic Interventions Robot to Estimate Cable Tension and Ext. Force G Dwyer 1, F Chadebecq 1, M Tella Amo 1, C Bergeles 1, E Maneas 1, V Pawar 1, E Vander Poorten 2, J Deprest 2, Mohammad Haghighipanah, Muneaki Miyasaka, and Blake S Ourselin 1, P De Coppi 1, T Vercauteren 1 and D Stoyanov 1 Hannaford 1 UCL, UK 2 KU Leuven, Belgium Electrical Engineering, University of Washington, USA

• Fetoscopic interventions are delicate procedures involving the introduction of a small • This paper presents a method to estimate endoscope for visualisation cable pre-tension and external forces acting on the robot • Concentric tube manipulator to enhance • Cable pre-tension was estimated based on dexterity at the tip of the endoscope dynamical methods

• Eternal forces acting on the robot in all the four • 7 DOF robotic arm constrained to remote quadrants was estimated based on UKF and centre of motion to improve stability cable elasticity • 3D reconstruction and mosaicing of the placenta is demonstrated

2017 IEEE International Conference on Robotics and Automation Session WeC11 Rm. 4813/4913 Wednesday, May 31, 2017, 14:30–15:45 Service Robotics 2 Chair Peter Luh, University of Connecticut Co-Chair Claudio Melchiorri, University of Bologna

14:30–14:35 WeC11.1 14:35–14:40 WeC11.2

Improving the Reliability of Service Robots in Deploying Social Robots as Teaching Aid in Pre- the Presence of External Faults by Learning school K2 Classes: A Proof-of-Concept Study Action Execution Models Alex Mitrevski, Anastassia Kuestenmacher, Albert Causo, Zin Win Phyo, Peng Sheng Guo, I-Ming Chen School of Mechanical & Aerospace Engineering, Santosh Thoduka, and Paul G. Plöger Nanyang Technological University, Singapore Department of Computer Science, Hochschule Bonn-Rhein-Sieg, Germany

• 16 student each from 2 pre-schools tested • We present a learning-based method for Pepper and Nao. avoiding the occurrence of external faults • 6 lessons were developed for each robot and • For generalising over various environment delivered over span of 3 months configurations and objects, the representation • Students and teachers were observed for of the model includes both symbolic and behaviors like critical thinking, imagination, geometric components creativity, and social interaction and creativity, • Our experiments show that the learned From faulty to successful classroom atmosphere, classroom models can represent execution knowledge execution management, and class behavior. fairly reliably • Study shows the challenges and potential benefits.

14:40–14:45 WeC11.3 14:45–14:50 WeC11.4

Instruction Completion through Instance-based What No Robot Has Seen Before – Learning and Semantic Analogical Reasoning Probabilistic Interpretation of Natural-language Object Daniel Nyga, Mareike Picklum, Sebastian Koralewski, Michael Beetz Descriptions Institute for Artificial Intelligence, University of Bremen Daniel Nyga, Mareike Picklum and Michael Beetz Institute for Artificial Intelligence, University of Bremen

 Natural-language instructions are vague and lack critical  recognize objects based on natural-language descriptions information  a novel probabilistic knowledge- driven approach to attribute-  Inference of missing information based object recognition pieces in natural-language instructions required  transform NL description into formal semantic representation wrt. perceptual attributes

 Novel Instance-based learner  use semantic representation to combining probabilistic with find corresponding object in analogical reasoning for deep scene knowledge transfer

14:50–14:55 WeC11.5 14:55–15:00 WeC11.6

Control of Liquid Handling Robotic Systems: Informative Planning and Online Learning with a Feed-Forward Approach to Suppress Sloshing Sparse Gaussian Processes L. Moriello*, L. Biagiotti♦, C. Melchiorri*, A. Paoli§ * Department of Electrical, Electronic and Information Engineering, Kai-Chieh Ma, Lantao Liu, Gaurav S. Sukhatme University of Bologna, Italy. Department of Computer Science, University of Southern California, USA ♦ Department of Engineering, University of Modena and Reggio Emilia, Italy. § School of Engineering, University of Lincoln, UK. • We are motivated by persistent sensing and estimation of an unknown environmental model • Sloshing of liquid into a moving container is with spatiotemporal variation. modelled as a spherical pendulum. • We propose a framework that combines an • Liquid handling is approached as a typical informative planning component and an online vibration suppression problem. learning component. • Mechanical model is used to design an • The planning component aims at collecting data Exponential Filter, which can be implemented in with maximal information for model prediction. cascade configuration to a generic trajectory • The learning component is based on a sparse generator. variant of Gaussian Process; the environment • Experimental tests on an industrial manipulator Set-point generation model and hyperparameters are learned online prove significant sloshing reduction and great algorithm for the by using only a subset of data. Informative path with industrial robot. sparse samples robustness to parametrical uncertainties.

15:00–15:05 WeC11.7 15:05–15:10 WeC11.8

Design and Analysis of 6-DOF Triple Scissor Extender Robots Sean Gunn, Peter Luh, Xuesong Lu Electrical & Computer Engineering, University of Connecticut, U.S.A. with Applications in Aircraft Assembly Brock Hotaling Daniel J. Gonzalez and H. Harry Asada Verbi, Inc Department of Mechanical Engineering Massachusetts Institute of Technology (MIT), USA • Optimizing Guidance during active shooter events to safely guide evacuees out of the building • We derive general case inverse kinematics for • Active shooter events are volatile, each incident average about 6.5 different designs of Triple Scissor Extender causalities with a fatal shooting every 15 seconds (TSE) Robots. • We analyze sensitivity of motion to changing • Guidance is optimized by geometric design parameters for the TSE. utilizing Lagrangian • We present a case study where these relaxation framework to analyses are utilized for the design of our minimize the risk to evacuees prototype.

Frequency of Active Shooter Events

2017 IEEE International Conference on Robotics and Automation Session WeD1 Rm. 4011 Wednesday, May 31, 2017, 16:05–17:20 Soft Robotics 1 Chair Shigeki Sugano, Waseda University Co-Chair Barthélemy Cagneau, Université de Versailles Saint-Quentin en Yvelines

16:05–16:10 WeD1.1 16:10–16:15 WeD1.2

A Versatile Conducting Interpenetrating Polymer Network 3D-Printed Ionic Polymer-Metal Composite for Sensing and Actuation Soft Crawling Robot Chia-Ju Peng1,2 , Tien Anh Nguyen1, Kätlin Rohtlaid3 , Cédric Plesse3, Shih-Jui Chen2, Luc Chassagne1 and Barthélemy Cagneau1 James D. Carrico and Kam K. Leang* 1 Université de Versailles St-Quentin en Yvelines / LISV, France. 2 National central University, Department of Mechanical Engineering, Taoyuan, Taiwan Dept. of Mechanical Engineering, Univ. of Utah Robotics Center, U.S.A. 3 Université de Cergy, LPPI / I-MAT, Cergy-Pontoise, France Kwang J. Kim Dept. of Mechanical Engineering, Univ. Of Nevada, Las Vegas, U.S.A. This work deals with conducting interpenetrating polymers (C-IPN).

• New 3D printing technique developed to The main characteristic of C-IPN is that they can create ionic polymer-metal composite (IPMC) be used as sensors and actuators. They require low based soft crawling robot voltage (under 2.5V) to be actuated.

• Crawling robot consists of modular gripper A model is proposed to actuate the C-IPN in open and body units, for caterpillar-like locomotion loop. Moreover, another model is presented for the sensor output. • Developed a dynamics model for performance prediction and gait optimization Future work will include developments at micro- and nanoscale. • Experimental results demonstrate caterpillar- The polymer used in top figure is actuated with a low voltage. While moving, It can detect like locomotion periodic disturbances shown in bottom figure.

16:15–16:20 WeD1.3 16:20–16:25 WeD1.4

Asymmetric Stable Deformations in Inflated Dielectric Elastomer Actuators Lindsey Hines1, Kirsten Petersen2, and Metin Sitti1 1 Max Planck Institute for Intelligent Systems, Germany 2 Cornell University, USA Networked Soft Actuators with Large Deformations Stable State 1 • We demonstrate fluidically connected Area ɛ > 100% dielectric elastomer actuators (DEAs) with Feifei Chen, Jiawei Cao, Lei Zhang, Hongying stable asymmetric deformations. Zhang, Jian Zhu and Y.F. Zhang

• Achieved membrane area strain can be both significant as well as significantly different. Stable State 2 Area ɛ > 550% Department of Mechanical Engineering • The inflated system is sealed, producing National University of Singapore motion without pumps or compressors.

contact: [email protected]

• Use cases may include compliant robotic Stable states of fluidically grippers and joints. connected DEA membranes, maintained without applied voltage

16:25–16:30 WeD1.5 16:30–16:35 WeD1.6

Design, Modeling and Control of a SMA- A High Speed Soft Robot Based On Dielectric Actuated Biomimetic Robot with Functional Skin Elastomer Actuators Mihai Duduta, David Clarke, and Robert Wood School of Engineering and Applied Sciences, Harvard University, USA Joan Ortega Alcaide, Levi Pearson, Mark E. Rentschler Department of Mechanical Engineering, University of Colorado, USA

• A novel manufacturing method has been • Novel functional robotic skin optimized to adapted to create inchworm and multi-legged maximize traction while providing sufficient crawling robots. recovery force to the SMA-actuators • The actuators are multilayered dielectric • SMA-Actuated peristaltic motion using forced elastomers unimorphs that allow some robots convection to increase robot speed to crawl at 1 body length / second. • Closed-loop non-linear control used to control • Future work will be directed at lowering the the three degrees of freedom of each of the actuation voltage to make untethered robots three robotic sections for exploration.

16:35–16:40 WeD1.7 16:40–16:45 WeD1.8

Tunable Friction through Constrained Inflation Printed Paper Robot of an Elastomeric Membrane Driven by Electrostatic Actuator

Hiroki Shigemune, Yoshitaka Iwata, Eiji Iwase Kaitlyn P. Becker, Nicholas W. Bartlett, Shuji Hashimoto and Shigeki Sugano Melinda J. D. Malley, Peter M. Kjeer, Robert J. Wood Waseda University, Japan School of Engineering and Applied Sciences, Harvard University, USA Shingo Maeda Vito Cacucciolo Shibaura Institute of Technology, Japan Scuola Superiore Sant’Anna, Italy

• A soft robotic device for tunable friction. • We propose a method to fabricate a 3D wiring • Pressure controls extension of high-friction board with inkjet printing. elastomeric membrane through holes in low- • The paper gets electronic function by silver ink friction restraining layer. and mechanic function with self-folding along • Achieves an order of magnitude differentiation the printed ink. of friction force between high and low pressure • We developed a printed paper robot driven by states. Tunable friction pads electrostatic actuator using the technique. • This mechanism enhanced performance in attached to the fingertips • The proposed method may also apply for both a crawling robot and a soft robotic of a soft robotic gripper. wearable devices or flexible devices. gripper. Driving of the printed paper robot

2017 IEEE International Conference on Robotics and Automation Session WeD2 Rm. 4111 Wednesday, May 31, 2017, 16:05–17:20 Motion and Path Planning 2 Chair Nicola Wolpert, HFT Stuttgart Co-Chair Haoyong Yu, National University of Singapore

16:05–16:10 WeD2.1 16:10–16:15 WeD2.2

Collision Detection for 3D Rigid Body Motion Automated Tuning and Configuration of Planning with Narrow Passages Path Planning Algorithms Ruben Burger, Mukunda Bharatheesha and Robert Babuska Daniel Schneider, Nicola Wolpert and Faculty of Mechanical Maritime and Materials Engineering, University of Applied Science Stuttgart, Germany Delft Univerity of Technology, The Netherlands Elmar Schömer Marc van Eert Johannes Gutenberg - University Mainz, Germany Applied Scientist, Technolution B. V, The Netherlands

• Contribution: Acceleration data structure • Software implementations of path planners to speed up collision detection. involve numerical and categorical • Application: Random sampling in configuration parameters. a motion planner. • These parameters influence the performance • Idea: Shooting random rays to find an of the planners. exact witness for collision at high speed. • Manual tuning is hard: Many parameters • Result: Speedup of up to 5.0 compared to interacting in unpredictable ways. Runtime, Solving well-established collision detection libraries. • Automated tuning with Sequential Model- Percentage and Path Based Algorithm Configuration (SMAC) Length comparison of significantly improves planner performance. OMPL planners with SMAC tuning.

16:15–16:20 WeD2.3 16:20–16:25 WeD2.4

Perfect Tracking Control Using a Phase Plane for a Maximizing Mutual Information for Multipass Wheeled Inverted Pendulum Under Hardware Constraints Target Search in Changing Environments

Ryosuke Nakamura and Azusa Amino M. Kuhlman1, M. Otte2, D. Sofge2 and S. Gupta3 Center for Technology Innovation, Hitachi, Ltd., Japan 1Dept. of Mech. Eng., Univ. of Maryland, College Park, USA 2Naval Research Laboratory, Washington, DC, USA 3Aero. and Mech. Eng. Dept, Univ. of Southern California, USA

• A motion-planning method for a wheeled • Consider target search tasks in changing inverted pendulum under hardware constraints environments for disaster scenarios • All state values are represented by a linear • Algorithms must plan over a long time horizon sum of differential values of one parameter. maximizing mutual information • The motion-plan can be designed on phase • Proposed algorithm generates plans that planes of body angle and angular velocity. cover the space multiple times as time Phase plane of motion constraints permit. Motion model for graph simulation • Use of ε-admissible heuristics speed up the search for disaster search recovery scenario

16:25–16:30 WeD2.5 16:30–16:35 WeD2.6

Efficient Multi-Agent Global Navigation Using Accelerating Energy-Aware Spatiotemporal Path Interpolating Bridges Planning for the Lunar Poles

Liang He1, Jia Pan2 and Dinesh Manocha1 Chris Cunningham, Joseph Amato, Heather L. Jones, 1 The University of North Carolina at Chapel Hill William L. Whittaker 2 City University of Hong Kong The Robotics Institute, Carnegie Mellon University, United States

• A novel approach for collision-free global • Planning missions for rovers on the lunar navigation for continuous time multi-agent poles requires consideration of dynamic systems with general linear dynamics. hazards including lighting and • Compute multiple bridges for environments communication shadows. with narrow passages and crowded regions • This paper accelerates energy-aware • Agents leverage bridges for efficient planning using a novel set of optimizations and constraints. navigation planning Planned path on lunar Collision-free results • Results show an average 80% runtime terrain showing slope, computed using bridges reduction over naïve planning with greater communication, and improvements in longer, more demanding lighting hazards as well as test cases. the reachable area.

16:35–16:40 WeD2.7 16:40–16:45 WeD2.8

Adaptive trajectory control of off-road mobile Smooth Extensions of Feedback Motion Planners robots: A multi-model observer approach via Reference Governors Mathieu Deremetz and Roland Lenain Omur Arslan and Daniel E. Koditschek TSCF, IRSTEA, France Electrical & Systems Engineering, University of Pennsylvania, US Benoit Thuilot Institut Pascal, Clermont-Ferrand University, France • A novel application of reference governors to Vincent Rousseau motion planning for separating the issues of TSCF, IRSTEA, France stability and collision avoidance is presented.

• An approach gathering extended kinematic • A provable correct computationally efficient and dynamic models into a single framework framework for extending low-order motion • A unique observer regardless of the velocity planners to high-order systems is proposed. allowing an accurate and reactive estimation • A new bidirectionally coupled robot-governor of sliding system is introduced. • An accurate path tracking, even in harsh • Smooth extensions of navigation paths to conditions and when facing significant Fig. Picture of the robot velocity- and force-controlled robot models dynamic effects during trials are presented. • Full-scale experiments

2017 IEEE International Conference on Robotics and Automation Session WeD3 Rm. 4311/4312 Wednesday, May 31, 2017, 16:05–17:20 Visual Tracking Chair Junaed Sattar, University of Minnesota Co-Chair Homayoun Najjaran, University of British Columbia

16:05–16:10 WeD3.1 16:10–16:15 WeD3.2

Illumination Insensitive Efficient Second-order Set space visual servoing of a 6-DOF manipulator Minimization for Planar Object Tracking Chicheng Liu1, Rui Chen1, Jing Xu1, Jianguo Zhao2, 1 1 2 1 2,3 Heping Chen3, Ning Xi4, Ken Chen1 Lin Chen , Fan Zhou , Yu Shen , Xiang Tian , Haibin Ling , 1 1 Department of Mechanical Engineering, Tsinghua University, China and Yaowu Chen 2 Department of Mechanical Engineering, Colorado State University, USA ADTI, Zhejiang University, China 3 Ingram School of Engineering, Texas State University, USA Meitu HiScene Lab, HiScene IT, China 4 Emerging Technologies Institute, The University of Hong Kong, China Computer and Information Sciences Dept, Temple University, USA • The visual tracking method is robust to severe • Define image error in set space for control illumination changes and general challenges. scheme input • The planar object tracking with templates is • Deduce image interaction matrix to control based on image registration and the ESM robot method. • Verify the proposed method by 6-DOF • First to introduce the gradient orientations manipulation feature into ESM method, instead of the Schematic diagram of the Set space visual servoing intensity values. illumination insensitive for 6-DOF manipulator • The Perona-Malik method and mask images planar object tracking are used for handling image noise and low texture.

16:15–16:20 WeD3.3 16:20–16:25 WeD3.4

Correlation Filter-Based Self-paced Object Real-time visual tracking via robust Tracking Kernelized Correlation Filter

Wenhui Huang1, Jason Gu2, Xin Ma1 and Yibin Li1 Xiaoliang Wang, Changle Xiang, Bin Xu 1School of Control Science and Engineering, Shandong University, China Beijing Institute of Technology, China 2Department of Electrical and Computer Engineering, Dalhousie University, Marie O’Brien and Homayoun Najjaran* Canada The University of British Columbia, Canada Precision plots of OPE 1 • Increase tracking accuracy for fast 0.9 • Object tracking is an important capability for moving targets by search window 0.8 robots tasked with interacting with humans 0.7 alignment based on motion estimation 0.6 and the environment. 0.5 Our tracker [0.861] • Accelerate tracking speed by reducing Precision 0.4 • A new object tracking method with the learning KCF [0.804] 0.3 Struck [0.691] the padding value TLD [0.561] 0.2 paradigm of self-paced learning. SCM [0.466] • Enhance robustness by combined 0.1 • A real-valued error-tolerant self-paced function 0 confidence measurement including 0 10 20 30 40 50 with a constraint vector to take the Location error threshold occlusion information characteristics of object tracking into account. Comparison of the precision • Under the framework of kernelized correlation The precision plots for the of the proposed tracker with filter to accelerate and advance the tracker. top 10 trackers on the OTB the state of the art 2013 data set.

16:25–16:30 WeD3.5 16:30–16:35 WeD3.6

Multi-robot control and tracking framework for Mixed-domain Biological Motion Tracking for bio-hybrid systems with closed-loop interaction Underwater Human-Robot Interaction Frank Bonnet, Alexey Gribovskiy and Francesco Mondada Robotic Systems Laboratory, Polytechnic School of Lausanne, Switzerland Md Jahidul Islam and Junaed Sattar Leo Cazenille and José Halloy Dept. of Computer Science, University of Minnesota Laboratory of Tomorrow’s Energies, University Paris Diderot VII, France

 Tracking spatial- and frequency-domain • We present a novel framework for features pertaining to human swimming pattern

experimentation on bio-hybrid systems  Frequency-domain signatures capture periodic consisting of fish and robots flipping along diver's swimming direction • The designed software is highly modular,  Hidden Markov Model (HMM)-based search- flexible and efficient to perform closed-loop space pruning using spatial-domain features control of the robots according to the fish  Robust detection of diver swimming in arbitrary behavior motion directions at reasonable computation Modeling arbitrary motion • We could show that a group composed of Three robots and three direction of diver in spatio- three robots can behave as the group of three zebrafish moving in the temporal volume zebrafish in terms of trajectory, speed and same environment inter-individual distances

16:35–16:40 WeD3.7 16:40–16:45 WeD3.8

Event-based Feature Tracking Co-Fusion: Real-time Segmentation, with Probabilistic Data Association Tracking and Fusion of Multiple Objects http://visual.cs.ucl.ac.uk/pubs/cofusion/index.html Alex Zihao Zhu1, Nikolay Atanasov2 and Kostas Daniilidis1 Martin Rünz and Lourdes Agapito 1Computer and Information Science, University of Pennsylvania, USA Department of Computer Science, University College London, 2Mechanical Engineering and Applied Mechanics, University of Pennsylvania, United Kingdom USA

• Events are grouped into features based the length of the optical flow. • Co-Fusion is a dense, multi-object SLAM system for RGBD-sequences. • Assignment of events to features is soft and computed as a probability based on • It tracks camera and objects simultaneously flow. and maintains a surfel-based map per model. • Flow is computed as a maximization of • Co-Fusion segments the scene into different the expectation over all data objects in image space, exploiting object associations. motion or semantic cues. Co-Fusion allows simultaneous segmentation • The feature deformation is modeled as Semi truck driving 3m in front • New synthetic and real evaluation-datasets tracking, and fusion of of the camera at 60 miles/hr were created and will be publicly available. affine and the residual serves as a multiple objects in RGB-D termination criterion sequences

2017 IEEE International Conference on Robotics and Automation Session WeD4 Rm. 4411/4412 Wednesday, May 31, 2017, 16:05–17:20 SLAM 2 Chair Vadim Indelman, Technion - Israel Institute of Technology Co-Chair Cyrill Stachniss, University of Bonn

16:05–16:10 WeD4.1 16:10–16:15 WeD4.2

Towards Efficient Inference Update through Nonmyopic Data Association aware Belief Space Planning via JIP – Joint inference and Belief Planning for Robust Active Perception Space Planning Elad I. Farhi Technion Autonomous Systems Program (TASP), Technion, Israel Shashank Pathak, Antony Thomas, Vadim Indelman Vadim Indelman Department of Aerospace Engineering Department of Aerospace Engineering, Technion, Israel Technion – Israel Institute of Technology

• Coalesce inference and planning using JIP – • We relax the typical assumption of state-of- Joint Inference and Belief Space Planning the-art Belief Space Planning – that the data paradigm. association is given and perfect • Utilizing Belief Space Planning calculations to • We consider uncertain data association within efficiently update inference. the belief in the context of nonmyopic planning • Four inference update methods are offered, • Our framework is mathematically sound assuming consistent Data Association between resulting in beliefs that are GMMs. inference and precursory planning. GMM beliefs with Simulation results for • Components of GMM can increase as well as appropriate weight • Our methods were compared to iSAM Inference Update running- decrease thereby modeling the problem better updates methodology and the standard batch paradigm. time comparison. as shown by experiments on real robot and simulations

16:15–16:20 WeD4.3 16:20–16:25 WeD4.4

MonoRGBD-SLAM: Simultaneous Localization and Real-Time Monocular Visual SLAM Mapping Using Both Monocular and RGBD Cameras with Points and Lines Khalid Yousif Albert Pumarola1, Alexander Vakhitov2, Antonio Agudo1, School of Engineering, RMIT University, Australia Alberto Sanfeliu1, Francesc Moreno-Noguer1 Yuichi Taguchi and Srikumar Ramalingam 1Institut de Robòtica i Informàtica Industrial, (UPC-CSIC), Spain Mitsubishi Electric Research Labs (MERL), USA 2Mathematics and Mechanics, St. Petersburg University, Russia Problem Statement: Given a monocular video, • We present a SLAM system that uses our problem is to simultaneously recover the full both an RGBD camera and a wide-angle camera trajectory and the rigid structure. monocular camera However, existing approaches are prone to fail • Our system enables larger-scale 3D when dealing with poorly textured scenes. reconstruction with less failure cases Our approach: Most real-world scenarios are than using only an RGBD camera human-made with low-textured environments. In such settings edges are predominant and one • We propose to generate multiple virtual can still reliably estimate line-based geometric images from each monocular image, primitives. which improves feature matching and 3D reconstruction results Results: We obtain state-of-the-art solutions loop closure detection between images using the proposed method while combining point and line correspondences captured by the different cameras even on challenging scenarios.

16:25–16:30 WeD4.5 16:30–16:35 WeD4.6

ICRA 2017 Digest Template ROS2D: Image Feature Detector Using Rank Paper Title in One or Two Lines Order Statistics

Luis Contreras and Walterio Mayol-Cuevas Khalid Yousif and Alireza Bab-Hadiashar School of Engineering, RMIT University, Australia Department of Computer Science, University of Bristol, United Kingdom Yuichi Taguchi and Srikumar Ramalingam

Mitsubishi Electric Research Labs (MERL), USA

• We present O-POCO, a visual odometry and • We present a new image feature detection SLAM system that makes online decisions method regarding what to map and what to ignore. • The detector selects features based on • We propose and evaluate different information segmenting points with high local intensity layers such as the descriptor information's variations across different scales relative entropy, map-feature occupancy grid, • A robust rank order statistics approach is and the point cloud's geometry error. utilized for segmentation • This system outperform several baselines as • Our method produces a large number of SfM an ORB SLAM even for conditions using repeatable features that are invariant to four times less information. several image transformations 3D reconstruction results using the proposed features

16:35–16:40 WeD4.7 16:40–16:45 WeD4.8

Illumination Change Robustness Cyrillic Manual Alphabet Recognition in (RGB)-D Data in Direct Visual SLAM for Sign Language Interpreting Robotic System Nazgul Tazhigaliyeva, Nazerke Kalidolda, Alfarabi Imashev, Seonwook Park Thomas Schöps Marc Pollefeys Shynggys Islam, Kairat Aitpayev, Anara Sandygulova Department of Computer Science, ETH Zurich, Switzerland Nazarbayev University, Astana, Kazakhstan German I. Parisi University of Hamburg, Germany • Standard direct image alignment used in direct

SLAM/VO based on Lukas-Kanade assumes • Aim: to develop an interpreting robotic system

brightness constancy. for hearing-impaired individuals. • We evaluate 10 illumination change robust • We collected four fully annotated RGB and variants of this alignment for accuracy and RGB-D datasets, two static and two motion robustness. datasets, of 33 signs of Cyrillic manual alphabet. • Gradient and Census based formulations • Applied datasets to standard ML tools and to our neural network-based learning architecture. perform well in our tests. Frames from our synthetic Fingerspelling in process. • We release our test dataset of synthetic and datasets with severe local • Our motion-based results outperform static real RGB-D videos with strong illumination illumination changes results. RGB-D results outperform RGB results. changes. (based on ICL-NUIM) • Average accuracy for 33 gestures is 93%.

2017 IEEE International Conference on Robotics and Automation Session WeD5 Rm. 4511/4512 Wednesday, May 31, 2017, 16:05–17:20 Aerial Robot 4 Chair Kostas Alexis, University of Nevada, Reno Co-Chair Shaojie Shen, Hong Kong University of Science and Technology

16:05–16:10 WeD5.1 16:10–16:15 WeD5.2

Orientation Filter and Angular Rates Estimation in Monocopter using Accelerometers and High Altitude Monocular Visual-Inertial State Magnetometer with the Extended Kalman Filter Estimation: Initialization and Sensor Fusion

Teguh Santoso Lembono, Jun En Low, Luke Soe Thura Win, Tianbo Liu and Shaojie Shen Shaohui Foong, Member, IEEE, and U-Xuan Tan, Member, IEEE Dept. of ECE, The Hong Kong University of Science and Technology, Singapore University of Technology and Design, Singapore Hong Kong S.A.R.

• Two important parameters in monocopter • Monocular visual-inertial systems are difficult to be flights: angular rates and orientation (heading initialized at high altitude. direction) • A spline-based high altitude estimator initialization • We propose to use three accelerometers to method is proposed in this paper. replace gyroscope for angular rates • Spline fitting and visual-inertial alignment are estimation, especially at high speed optimized to recovery quantities required by initialization. • We propose to use Extended Kalman Filter to  A complete closed-loop system is constructed, and estimate the heading direction. The experiments are conducted to validate our monocopter’s angular rates direction is used approach. as the vertical direction reference.

16:15–16:20 WeD5.3 16:20–16:25 WeD5.4

Real-time Monocular Dense Mapping on Aerial Robots Real-Time Local 3D Reconstruction for Aerial Using Visual-Inertial Fusion Inspection using Superpixel Expansion Zhenfei Yang, Fei Gao, and Shaojie Shen Lucas Teixeira and Margarita Chli Robotics Institute, Hong Kong University of Science and Technology, China Vision for Robotics Lab, ETH Zurich, Switzerland

• A dense mapping system that runs • Pipeline for real-time onboard 3D real-time on Nvidia Jetson TX1 reconstruction from a small aircraft.  Visual-inertial localization • Denser depth estimation builds on top  Motion stereo of feature-based monocular-inertial EXTERNAL VIEW  Global map fusion SLAM. • Close the perception-action loop: • Strict filtering of depth estimates is navigate a quadrotor autonomously applied to remove outliers, after CAMERA VIEW with collision-free guarantee superpixel-based dilation & temporal fusion are used to create a dense, • Open Source local map of the aircraft’s workspace. Real-time dense reconstruction of a local scene for aerial inspection

16:25–16:30 WeD5.5 16:30–16:35 WeD5.6

Uncertainty-aware Receding Horizon Exploration Autonomous Swing-Angle Estimation for Stable and Mapping using Aerial Robots Slung-Load Flight of Multi-Rotor UAVs

Christos Papachristos, Shehryar Khattak and Kostas Alexis Seung Jae Lee and H. Jin Kim Department of Computer Science and Engineering, Department of Mechanical and Aerospace Engineering, University of Nenada, Reno, USA Seoul National University, Republic of Korea

• Two-step Random Sampling-based • Presents a disturbance observer Probabilistic Exploration and Mapping: (DOB) based autonomous swing • Exploration based on Volumetric gain angle estimator for multirotor UAV and Mapping Probability improvement. • Only built-in IMU and single load cell • Localization and Mapping consistency mounted between tether is used for by Propagating Uncertainty of pose swing-angle estimation and landmarks through simulated • Autonomous thrust force estimation Autonomous Exploration of an inertial measurements for randomly method without additional sensors is sampled trajectories. unknown environment with Uncertainty-aware Path-planning for presented • Open-source code and datasets: Probabilistic Volumetric Mapping https://github.com/unr-arl/rhem_planner

16:35–16:40 WeD5.7 16:40–16:45 WeD5.8

Active Estimation of Mass Properties for Safe Model-based Global Localization for Aerial Robots Cooperative Lifting Using Edge Alignment

Kejie Qiu, Tianbo Liu, and Shaojie Shen Micah Corah and Nathan Michael Robotics Institute, Carnegie Mellon University, USA

• Reliable and safe aerial manipulation requires mass parameter estimation and feasible lifting configurations • Non-parametric Bayesian filtering and minimal interactions provide estimates • Measurements selected via information- theoretic active sensing • Simultaneous estimation and formation of lifting configurations via chance- Coordinated aerial manipulation is constrained deployment strategy achieved via: (1) approach, (2-4) deployment and interaction, and (4) object lifting

2017 IEEE International Conference on Robotics and Automation Session WeD6 Rm. 4611/4612 Wednesday, May 31, 2017, 16:05–17:20 Semantic Understanding Chair Fabio Morbidi, Université de Picardie Jules Verne Co-Chair James J. Little, UBC

16:05–16:10 WeD6.1 16:10–16:15 WeD6.2

What Can I Do Around Here? Deep Functional MF3D: Model-Free 3D Semantic Scene Parsing Scene Understanding for Cognitive Robots Chengxi Ye1, Yezhou Yang2, Ren Mao1 Frederick Tung and James J. Little Cornelia Fermüller1, Yiannis Aloimonos1 Department of Computer Science, University of British Columbia, Canada 1 University of Maryland, USA 2CIDSE, Arizona State University, USA

• We present a novel model-free method • We address the problem of localizing and for online 3D semantic scene parsing recognition of functional areas from an indoor from video sequences scene. • Voxel labelling is approached via • We designed a scene functional area ontology for search-based label transfer instead of indoor domain. discriminative classification • Deep network based recognition approach is • MF3D is easily extensible to new developed and presented for scene functional examples or categories as no model Figure caption is optional, understanding. use Arial 18pt re-training is required • The first scene functionality dataset is compiled and made publicly available (with >100,000 annotated training samples).

16:15–16:20 WeD6.3 16:20–16:25 WeD6.4

Semantic Analysis of Manipulation Actions Analyzing Modular CNN Architectures for Joint using Spatial Relations Depth Prediction and Semantic Segmentation Fatemeh Ziaeetabar1, Eren Erdal Aksoy2, Florentin Wörgötter1 Omid Hosseini Jafari1, Oliver Groth1, Alexander Kirillov1 and Minija Tamosiunaite1,3 Michael Ying Yang2 and Carsten Rother1 1 Institute for Physics 3- Biophysics, Georg August University, Göttingen, 1Computer Vision Lab, TU Dresden, Germany Germany 2Scene Understanding Group, University of Twente, Netherlands 2 Institute for Anthropomatics and Robotic, Karlsruher Institute for Technologies (KIT), Karlsruhe, Germany 3 Faculty of Informatics, Vytautas Magnus University, Kaunas, Lithuania • Propose Joint refinement network to predict and to refine depth estimation and semantic • A new framework for representation and RGB-D Segmentation Extraction of labeling jointly given a single image image and tracking spatial relations recognition of manipulation actions. sequences • Propose an experimental set-up to measure Enriched Similarity • Extraction of symbolic relations based on Action Semantic Event measureme cross-modality influence classification AABB object models and using sequences of Chain nt • Analyzing different network design to show the spatial relations between manipulated objects Steps of our spatial relationship between cross-modality influence for an accurate classification. reasoning approach and performance of tasks • This relational framework is able to differentiate and classify manipulation actions on a big dataset and obtains 97% accuracy.

16:25–16:30 WeD6.5 16:30–16:35 WeD6.6

SemanticFusion: Dense 3D Semantic Online Learning for Scene Segmentation With Mapping with Convolutional Neural Networks Laser-Constrained CRFs

John McCormac, Ankur Handa, Charika Alvis, Lionel Ott and Fabio Ramos School of IT, University of Sydney, Australia Andrew Davison and Stefan Leutenegger Dyson Robotics Lab, Imperial College London, UK • A model to learn CRF parameters which eliminates the need • Combine CNNs with a state-of-the- for ground truth labels art real time dense SLAM system • Reference labels obtained by processing multimodal sensor • Produce globally consistent data. semantically annotated 3D map • Fusing multiple 2D predictions in • Stochastic method to update the parameters in online settings 3D improves accuracy on NYUv2 • The system is fast enough to • Adaptive parameter learning for non-stationary data enables interactive use at 25FPS encountered in long-term autonomy settings

16:35–16:40 WeD6.7 16:40–16:45 WeD6.8

AdapNet: Adaptive Semantic Segmentation in Phase Correlation for Dense Visual Compass Adverse Environmental Conditions from Omnidirectional Camera-Robot Images Fabio Morbidi and Guillaume Caron Abhinav Valada, Johan Vertens, MIS laboratory, University of Picardie Jules Verne, Amiens, France Ankit Dhall, and Wolfram Burgard University of Freiburg, Germany • New dense omnidirectional visual

Modality 1 1 Modality compass based on the phase

• Convolutional neural network based semantic RGB correlation method in the segmentation architecture built upon the 2-D Fourier domain residual learning framework • Accurate, robust to image noise,

• Scale invariant and fast inference (~59 ms) 2 Modality and computationally inexpensive Depth • Adaptive fusion framework for learning • Suitable for use with weakly-calibrated cameras complementary features from multiple modalities • Experimental validation with a hypercatadioptric Segmented Segmented

• Robust to lighting changes, seasonal Output camera mounted on the end-effector of a appearance changes, motion-blur and glare Staubli manipulator and on a Pioneer robot • Demo: http://deepscene.cs.uni-freiburg.de/ • OVMIS dataset: http://mis.u-picardie.fr/~g-caron/en

2017 IEEE International Conference on Robotics and Automation Session WeD7 Rm. 4711/4712 Wednesday, May 31, 2017, 16:05–17:20 Manipulation Planning 2 Chair Jurgen Leitner, Australian Centre for Robotic Vision / Queensland University of Technology Co-Chair Hai-Jun Su, The Ohio State University

16:05–16:10 WeD7.1 16:10–16:15 WeD7.2

A Robust Control Scheme for 3D Manipulation of Toward Improving Path Following Motion: a Microparticle with Electromagnetic Coil System Hybrid Continuum Robot Design Weicheng Ma, Junyang Li, Fuzhou Niu, Bo Ouyang and Dong Sun Department of Mechanical and Biomedical Engineering, City University of Hong Ernar Amanov, Josephine Granna and Jessica Burgner-Kahrs Kong, Hong Kong, China Laboratory for Continuum Robotics, Haibo Ji Leibniz Universität Hannover, Germany Department of Automation, University of Science and Technology of China, China

•A robust feedback control approach for • Hybrid continuum robot design: concentric precise 3D manipulation of a microparticle tube and tendon-driven design combination actuated by a self-constructed electromagnetic • Path following capabilities investigation of coil system is proposed tendon-driven continuum robots • Model uncertainties, environmental • Hybrid design prototype introduction disturbances, as well as actuator energy • Experimental evaluation of path following with loss problem are all taken into account in the the hybrid design prototype controller design An overview of the • The proposed control scheme can enable the prototype electromagnetic entire system to maintain the input-to-state coil system stability in presence of various perturbations

16:15–16:20 WeD7.3 16:20–16:25 WeD7.4

Unobservable Monte Carlo Planning for The Manifold Particle Filter for State Estimation Nonprehensile Rearrangement Tasks on High-dimensional Implicit Manifolds Jennifer King, Vinitha Ranganeni, Siddhartha Srinivasa Robotics Institute, Carnegie Mellon University, USA Michael C. Koval, Matthew Klingensmith, • An anytime planner for creating open- Siddhartha S. Srinivasa, Nancy S. Pollard, and Michael Kaess loop trajectories that solve Robotics Institute, Carnegie Mellon University, USA rearrangement problems

• Extend Monte Carlo Tree Search to the • Use contact sensors to estimate the configuration unobservable domain of a robot with noisy proprioception

• Implicitly represent the contact manifold of • Evaluate three default policies: states consistent with an observation as the • Random policy – generate iso-contour of the signed distance function random action sequences • Use constraint projection to draw samples • Learned policy – use human from the contact manifold to implement the demonstrations to build a mapping implicit manifold particle filter that is queried for action sequences Policies trade-off computational • Demonstrate the proposed technique on a real • Planned policy – heuristically plan in subspace of the full problem complexity for better informed robotic arm and under-actuated robotic hand decision making

16:25–16:30 WeD7.5 16:30–16:35 WeD7.6

A Comparison of Autoregressive Hidden Markov Essential Properties of Numerical Integration for Models for Modeling Mass-Dependent Mode Time-optimal Path-constrained Trajectory Planning Switches in Manipulation Tasks Oliver Kroemer Peiyao Shen, Xuebo Zhang and Yongchun Fang RESL, University of Southern California (USC), USA Institute of Robotics and Automatic Information System, Nankai University, China

Tianjin Key Laboratory of Intelligent Robotics, Nankai University, China Jan Peters IAS, Technische Universitaet Darmstadt, Germany

1.4 MVC(s)

• This paper presents several new properties of 1.2 inadmissible •Mode switches, such as making or breaking region the Numerical Integration (NI) method. 1 V(s) contact, often depend on an object’s mass

p 0.8 3  •We evaluated four types of ARHMMs for 2 p 4 _s[m=s] 0.6  #  2 2 modeling mode switches in manipulation tasks • Rigorous mathematical proofs of these new p 3 1  0.4  3 1 p properties are presented. # p 5 •The robot uses the models to predict the 1 2 0.2  0  admissible o 1  masses and trajectories of manipulated objects 1 region e 0 0 1 2 3 4 5 6 • Some simulation results on a unicycle are s[m] •We successfully evaluated the different models provided to verify those presented properties. The NI method outputs on both pushing and lifting tasks the time-optimal trajectory.

16:35–16:40 WeD7.7 16:40–16:45 WeD7.8

Feature Selection for Learning The ACRV Picking Benchmark: Versatile Manipulation Skills based on A Robotic Shelf Picking Benchmark to Foster Observed and Desired Trajectories Reproducible Research Jürgen Leitner et al. Oliver Kroemer and Gaurav S. Sukhatme Australian Centre for Robotic Vision (ACRV) RESL, University of Southern California (USC), USA

The proposed benchmark consists of: •Robots need to adapt manipulation skills using (A)a commonly available shelf a small subset of the objects’ features (B)objects • Evaluated selecting relevant features based on observed trajectories versus desired trajectories

• Explored including a meta prior to predict the We also presents a baseline system relevance of features based on previous skills (C) performing the benchmark tasks •The methods were successfully evaluated using (D) describe its deployment during the placing, tilting, and wiping skills Amazon Picking Challenge 2016

http://Juxi.net/dataset/acrv-picking-benchmark/

2017 IEEE International Conference on Robotics and Automation Session WeD8 Rm. 4613/4713 Wednesday, May 31, 2017, 16:05–17:20 Humanoid Robots 3 Chair Christian Ott, German Aerospace Center (DLR) Co-Chair Abderrahmane Kheddar, CNRS-AIST JRL (Joint Robotics Laboratory), UMI3218/CRT

16:05–16:10 WeD8.1 16:10–16:15 WeD8.2

Control Walking Speed by Approximate-kinetic- Overlap-based ICP Tuning for Robust model-based Self-adaptive Control on Localization of a Humanoid Robot Underactuated Compass-like Bipedal Walker Simona Nobili, Raluca Scona, Xuan Xiao and Ou Ma Marco Caravagna and Maurice Fallon School of Aerospace Engineering, Tsinghua University, China School of Informatics, University of Edinburgh, UK Fumihiko Asano School of Information Science, JAIST, Japan • AICP: a strategy for non-incremental 3D scene registration and localization in challenging • The model of underactuated compass-like environments. bipedal walker is built and the gait properties • Point clouds registration based on careful are analyzed based on an open-loop control pre-filtering and automatic adjustment to law. overlap variations. • The approximate-kinetic model-based self- • Motivation: avoid incremental error and recover adaptive (AKS) control system is proposed from failures. through updating trajectory and control parameters. A planar underactuated • Accurate localization of the NASA Valkyrie and compass-like bipedal walker the Boston Dynamics Atlas humanoid robot • The capability of disturbance rejection and during the DARPA Robotics Challenge Finals. adjusting walking speed of AKS system are tested through numerical simulations.

16:15–16:20 WeD8.3 16:20–16:25 WeD8.4

Stability Regions for Standing Balance of Biped Humanoid Robots Humanoid Whole-Body Planning for Loco-Manipulation Tasks Jung Hoon Kim, Jongwoo Lee, Yonghwan Oh Center for Robotics Research, KIST, Republic of Korea Paolo Ferrari, Marco Cognetti, Giuseppe Oriolo • An analytical method for computing stability regions Sapienza University of Rome, Italy relevant to standing balance of biped humanoid robots is developed based on their LIPM. • ZMP should be located in the supporting region for stable standing balance of biped humanoid robots. • Generation of natural whole-body motions • Set 1: The initial values of the CoM position & velocity for humanoids in loco-manipulation tasks • Set 2: Maximum admissible impulse force disturbance. • Set 3: Maximum admissible external force disturbance • Definition of three operational zones: of finite energy locomotion, loco-manipulation, manipulation • A synchronization mechanism between the

(a) Standing biped humanoid robot two tasks allows fluid, smooth transitions • Implemented in V- REP for the NAO and successfully tested in various scenarios

Figure. Stability region. case i) The initial value of the CoM position & velocity inside the stability region. case ii) The initial value of the CoM position & velocity (b) Supporting region outside the stability region Figure. Standing biped humanoid robot with its supporting region

16:25–16:30 WeD8.5 16:30–16:35 WeD8.6

Footstep and Motion Planning in Semi-unstructured Collision Detection, Isolation and Identification Environments Using Randomized Possibility Graphs for Humanoids Jonathan Vorndamme, Moritz Schappler and Sami Haddadin Michael X. Grey and C. Karen Liu Insitute of Automatic Control, Leibniz Universität Hannover, Germany School of Interactive Computing, Georgia Tech, USA Aaron D. Ames Mech. and Civil Eng. & Control and Dyn. Sys., CalTech, USA • Unified collision detection, isolation and identification for • Quickly evaluate the possibilities of routes humanoid robots though the environment • Solution for single and multi • Use fast and efficient gait generators to contact without tactile skins traverse “easy” routes • Suitable for any combination of • Focus low-level whole body motion planners joint torque and distributed on challenging routes force/torque sensors • Parallelizable to avoid unnecessary • Acceleration observer based load bottlenecks compensation for distributed force/torque sensors

16:35–16:40 WeD8.7 16:40–16:45 WeD8.8

Angular Momentum Compensation in Yaw Direction QP-based Adaptive-Gains Compliance Control in using Upper Body based on Human Running Humanoid Falls T. Otani1, K. Hashimoto1, S. Miyamae1, H. Ueta1, Vincent Samy and Abderrahmane Kheddar 2 1 3 1 CNRS - University of Montpellier LIRMM, 34000 Montpellier France M. Sakaguchi , Y. Kawakami , H. O. Lim and A. Takanishi 1 2 3 Karim Bouyarmane Waseda University, Japan University of Calgary, Canada Kanagawa University of Lorraine - INRIA - CNRS LORIA, 54600 Villers-lès-Nancy, France University, Japan • We developed an angular momentum control • Handle falls in any direction in a cluttered method using a humanoid upper body based environment on human motion. In this method, the angular • Search of impact points and shape the robot to be compliant to the impact. momentum generated by the movement of • Adaptive gains compliance computation to the humanoid lower body is calculated, and absorb the impact reaction forces. the torso and arm motions are calculated to • A QP is used in both pre-impact and post- Falling strategy compensate for the angular momentum of impact phases. the lower body.

(a) 全体像 (b) 自由度配置図図 5 開発した機体の全体像

2017 IEEE International Conference on Robotics and Automation Session WeD9 Rm. 4811/4812 Wednesday, May 31, 2017, 16:05–17:20 Biologically-Inspired Robots 3 Chair Stefano Mintchev, École polytechnique fédérale de Lausanne Co-Chair Kamilo Melo, EPFL

16:05–16:10 WeD9.1 16:10–16:15 WeD9.2

Blade-type Crawler Vehicle with Gyro Wheel A Lobster-inspired Robotic Glove for Hand for Stably Traversing Uneven Terrain at High Speed Rehabilitation Yasuyuki Yamada1, Hirotaka Sawada2, Yaohui Chen, Sing Le, Qiao Chu Tan, Oscar Lau, Takashi Kubota2 and Taro Nakamura1 Chaoyang Song*

1Chuo University, Japan. 2Japan Aerospace Exploration Agency (JAXA). Faculty of Engineering, Monash University, Australia Fang Wan Independent Researcher, China

• A lobster-inspired actuator with both soft and rigid components to address repeatability and vulnerability issues; • Investigations including design, fabrication and characterization; • An open-palm glove design integrated with the hybrid actuators to assist hand rehabilitation at home; • A learning system for hand rehabilitation with EMG control strategy and game interface.

16:15–16:20 WeD9.3 16:20–16:25 WeD9.4

Quadrupedal Locomotion using Trajectory Biological Undulation Inspired Swimming Robot Optimization and Hierarchical Whole Body Control

1 2 3 4 Christian Gehring, C. Dario Bellicoso, Péter Fankhauser, Marco Hutter Xinghua Jia , Zongyao Chen , JM Petrosino , William R Hamel , Robotics Systems Lab, ETH Zurich, Switzerland and Mingjun Zhang5 Stelian Coros The Ohio State University1,3,5, The University of Tennessee2,4 Carnegie Mellon University, USA • Three aquatic species including alligator, eel • Fast motion planning with trajectory optimization and trout were investigated to uncover the and a simple model of the dynamics propulsion mechanism and applied for • Robust motion tracking with online plan swimming robot design. alignment, corrective stepping and whole body • Both simulation and experimental results control based on state feedback showed and explained the variation trend as • Walking, trotting and transition between the two the undulation changed from the anguilliform to the carangiform. gaits with the quadruped robot Undulation Inspired • Experimental results with the fully torque- Swimming Robot controllable 30kg quadruped ANYmal ANYmal

16:25–16:30 WeD9.5 16:30–16:35 WeD9.6

Introducing Rotary Force to a Template Model Autonomous Locomotion of a Miniature, can Explain Human Compliant Slope Walking Untethered Origami Robot Using Hall Effect Sensor-Based Magnetic Localization Xiaochen Wang AgileBody, Beijing, China Steven Guitron, Anubhav Guha, Shuguang Li, Daniela Rus Tao Geng Massachusetts Institute of Technology, USA School of Science and Technology, Middlesex University London, UK

• Humans preserve compliant legged behavior • Closed-loop, autonomous position during slope walking feedback control is enabled utilizing • Introducing rotary force to a template model the robot’s integrated magnet can explain such human compliant behavior • 33 Hall effect sensors arranged in • Letting rotary force collaborate with radial repeated triangles enables position compliant mechanism can improve energy- detection (average error of 0.995 ± efficiency of legged robots 0.520 mm). • The robot’s speed response to applied magnetic field was characterized for Position Feedback controller development System

16:35–16:40 WeD9.7 16:40–16:45 WeD9.8

Insect-inspired Mechanical Resilience for Spine Controller for a Sprawling Posture Robot Multicopters S. Mintchev, S. de Rivaz and D. Floreano Laboratory of Intelligent Systems, EPFL Tomislav Horvat1, Kamilo Melo1 and Auke J. Ijspeert1 1Biorob, EPFL, Switzerland

• Some insects has dual-stiffness wings that rigidly withstand loads during flight, but soften • Effective locomotion controller for a during collision to avoid damages. robot with the segmented spine • Based on this findings, the quadcopter has a • Importance of spine-limb dual-stiffness frame that reversibly transition coordination between a rigid and a soft state. • Active usage of the spine for both • Stiffness under low loads ensures a stable straight walking and turning and efficient flight while mechanical • Robot’s maneuverability compliance under high loads prevents demonstrated in a simulation and on damages during collisions. a real robot

2017 IEEE International Conference on Robotics and Automation Session WeD10 Rm. 4911/4912 Wednesday, May 31, 2017, 16:05–17:20 Surgical Robotics 2 Chair Sarthak Misra, University of Twente Co-Chair Robert James Webster III, Vanderbilt University

16:05–16:10 WeD10.1 16:10–16:15 WeD10.2

Predictive Filtering in Motion Compensation with The Tethered Magnet: Force Steerable Cardiac Catheters and 5-DOF Pose Control for Cardiac Ablation

Paul M Loschak, Alperen Degirmenci, and Robert D Howe Christophe Chautems and Bradeley J. Nelson Paulson School of Engineering and Applied Sciences, Harvard University, USA Multi-Scale Robotics Lab , ETH Zurich, Switzerland

• Robotic navigation of cardiac ultrasound (US) • Magnet connected to a tether control with imaging catheters provides real time imaging magnetic field and magnetic gradient from within the heart • Stable magnet position by means of tether • Accurate navigation is challenging due to lenght constraint physiological disturbances such as respiration • Position and orientation control demonstrate • We use an Extended Kalman Filter (EKF) to inside a magnetic manipulation system predict target motion Predictive filtering applied • Catheter tip contact force dependent on Tethered Magnet floating • Predictions are used towards automatically towards ultrasound (US) magnetic gradient magnitude inside magnetic field steering the US catheter in benchtop tracking a target experiments

16:15–16:20 WeD10.3 16:20–16:25 WeD10.4

Shared Control of a Magnetic Microcatheter for Towards MRI-guided Flexible Needle Steering Vitreoretinal Targeted Drug Delivery Using Fiber Bragg Grating-Based Tip Tracking

Pedro Moreira1, Klaas Jelmer Boskma2 and Sarthak Misra1,2 Samuel L. Charreyron, Burak Zeydan and Bradley J. Nelson 1Department of Biomechanical Engineering, University of Twente, Netherlands Multi Scale Robotics Lab, ETH Zurich, Switzerland 2Department of Biomedical Engineering, University Medical Center Groningen and Univerisity of Groningen, Netherlands

• Age Related Macular Degeneration (AMD) • Magnetic Resonance Imaging and Diabetic Retinopathy (DR) are retinal (MRI)-guided interventions using pathologies and leading causes of blindness Fiber Bragg Grating (FBG) sensor • A magnetic microcatheter could be used for to track the needle delivery of therapeutics to precise retinal • Combining MRI-compatible robot targets with FBG-based needle tracking • We demonstrate a control strategy shared • Closed-loop flexible needle steering between a human operator and automated • Average targeting error of 1.74 mm magnetic positioning of the microcatheter in a in gelation and biological phantoms vitreoretinal phantom

16:25–16:30 WeD10.5 16:30–16:35 WeD10.6

Highly articulated robotic needle achieves distributed ablation of liver tissue Design of a Compact Actuation and Control System for Flexible Medical Robots Giada Gerboni1, Joseph D. Greer1, Paul F. Laeseke2, Gloria L. Hwang3 and Allison M. Okamura1 Tania K. Morimoto1, Elliot W. Hawkes1,2, and Allison M. Okamura1 1 Mechanical Engineering Department, Stanford University, USA 1Mechanical Engineering Department, Stanford University, USA 2 Radiology Department, University of Wisconsin, USA 2Department of Mechanical Engineering, University of California, 3 Radiology Department, Stanford University, USA Santa Barbara, USA

• Robotic needle steering enables • Compact, lightweight, modular percutaneous radiofrequency ablation (RFA) actuation system of irregular shaped and multifocal liver tumors. • Each module drives two degrees • The active needle tip design increases needle of freedom (insertion and rotation) curvature while meeting clinical constraints. • Enabled by roller gears with teeth • Needle configuration and curvature in both in both axial and radial directions artificial and ex-vivo liver tissue is determined • Suitable for use in patient- and via 3D ultrasound data. procedure-specific design process • Distributed RFA of liver tissue under Modular actuation and control system ultrasound imaging was successfully shown holding three concentric tubes performed in ex-vivo porcine model. and as a single unit

16:35–16:40 WeD10.7 16:40–16:45 WeD10.8

Continuum Reconfigurable Parallel Robots: A Contact-Aided Asymmetric Steerable Catheter Shape Sensing and State Estimation for Atrial Fibrillation Ablation Patrick Anderson, Art Mahoney, and Robert Webster III Anzhu Gao, Hao Liu, Yun Zou, Zhidong Wang Department of Mechanical Engineering, Vanderbilt University, USA State Key Laborotary of Robotics Shenyang Institute of Automation, Chinese Academy of Sciences, China • Continuum reconfigurable incisionless Ming Liang, Zulu Wang General Hospital of Shenyang Command of Chinese PLA, Shenyang, China surgical parallel (CRISP) robots give 6- DOF control to needle instruments • Propose to use the asymmetric catheter to • Sensors such as magnetic trackers are improve the tip orientation capability for the integrated into the needle instruments asymmetric lesions at the pulmonary veins; • A Kalman filter estimation framework • Design a 2D steerable catheter with contact enables shape estimation even under aided compliant mechanism to achieve the applied forces of unknown magnitude asymmetric bends; • Experiments using magnetic trackers • Kinematics and lesion exploration algorithm confirm better tip pose estimates (a) CRISP robots combine the benefits of are presented to show its reachability; despite unknown tip loads parallel, continuum, and reconfigurable robots and (b) they can be sensorized for • Phantom study shows that the proposed Cardiac catheter ablation shape estimation despite uncertainty catheter with CCMs can improve the tip using the asymmetric orientation and achieve the full exploration. catheter with CCMs

2017 IEEE International Conference on Robotics and Automation Session WeD11 Rm. 4813/4913 Wednesday, May 31, 2017, 16:05–17:20 Marine Robotics Chair Gregory Dudek, McGill University Co-Chair Brendan Englot, Stevens Institute of Technology

16:05–16:10 WeD11.1 16:10–16:15 WeD11.2

Experimental Evaluation of Various Machine Assisted Painting of 3D Structures Using Learning Methods for Model Identification of Shared Control with Under-actuated Robots Autonomous Underwater Vehicles Joshua Elsdon and Yiannis Demiris Bilal Wehbe, Marc Hildebrandt, and Frank Kirchner Electronic and Electrical Engineering, Imperial College London, UK DFKI – Robotic Innovation Center, Bremen, Germany

• Identification of motion model of an AUV by • Development and implementation of a applying machine learning regression. planning algorithm for shared control of a • Data is collected from the vehicle's on board handheld painting robot sensors. • A single autonomously controlled DOF • Four regression algorithms are used: neural positions the paint spraying head nets, kernel ridge, suppor vector machines, • Planner is run in a receding-horizon fashion and Gaussian processes. AUV Leng during and generates paths in real time • Results show that learning methods experimentation • Planner finds solution that will apply paint to outperforms classical least squares method for most needed areas efficiently model estimation.

16:15–16:20 WeD11.3 16:20–16:25 WeD11.4

Underwater Localization and 3D Mapping of Submerged Structures with a Single-Beam Phytoplankton Hotspot Prediction With an Scanning Sonar Unsupervised Spatial Community Model Jinkun Wang, Shi Bai and Brendan Englot Arnold Kalmbach and Gregory Dudek Stevens Institute of Technology, USA School of Computer Science, McGill University, Montreal, Canada Yogesh Girdhar and Heidi M. Sosik • A novel perceptual pipeline is presented that applies Woods Hole Oceanographic Institution, Woods Hole, MA, USA SLAM to scanning sonar data, in the absence of inertial/odometry sensing, and accounts for vehicle • We model the spatial co-occurrence between motion that occurs while scanning sparse, discrete natural phenomena with a Bayesian nonparametric topic model. • Clustered sonar range returns are adaptively • Estimating topics from partial observations thresholded, and re-clustered to extract high-quality enables point features – each corresponds to a distinct pose robust estimation of unobserved target hotspots. • Joint compatibility branch-and-bound is iteratively • We apply this approach to data from a unique employed in concert with iSAM2 to achieve accurate marine robotic instrument, learning a data association phytoplankton community model and • Gaussian process occupancy mapping is applied to predicting the hotspots of specific missing the resulting point clouds to produce accurate, taxa. descriptive 3D maps of submerged structures

16:25–16:30 WeD11.5 16:30–16:35 WeD11.6

An Artificial Fish Lateral Line Sensory System One-Way Travel-Time Inverted Ultra-Short Composed of Modular Pressure Sensor Blocks Baseline Localization for Low-Cost AUVs

Kevin Nelson 1 2 2 Electrical & Computer Engineering, University of Florida, USA Nicholas R. Rypkema , Erin M. Fischell and Henrik Schmidt 1Electrical Engineering and Computer Science Kamran Mohseni 2Mechanical Engineering Mechanical & Aerospace Engineering; Electrical & Computer Engineering, MIT, USA University of Florida, USA • Motivation: Accurate localization for low-cost • A bioinspired artificial fish lateral line sensory AUVs enables multi-AUV research system was developed for use on an underwater vehicle • Problem: Size, power and cost constraints prevent the use of high-grade INS, DVL or • The system is composed of modular sensor active acoustics blocks each containing two differential pressure sensors • Solution: Fixed acoustic beacon periodically transmits wideband up-chirp; AUV CSAC- • An algorithm is developed and tested to Modular, Artificial Lateral triggered array passively receives signal estimate the total hydrodynamic force acting Line Sensory System on the cylinder • Array processing and particle filter calculates AUV payload and acoustic range, azimuth and inclination to beacon processing + filtering

16:35–16:40 WeD11.7 16:40–16:45 WeD11.8

Robots going round the bend—a comparative Acoustic-Inertial Underwater Navigation study of estimators for anticipating river meanders Kai Qin and Dylan Shell Yulin Yang and Guoquan Huang NXP Semiconductors, U.S.A and Department of Computer Science and Mechanical Engineering, University of Delaware, USA Engineering, Texas A&M University, U.S.A

• Acoustic-inertial odometry with online extrinsic calibration by optimally fusing • River meanders are structured. acoustic and inertial measurements • Adopted geological model, sine-generated without keeping features in the state. curve, to parameterize state-space to predict • Acoustic feature triangulation with unseen portion of the river. bearing and range constraints of sonar • Collected GPS positions from a boat measurements. navigating an extended stretch of river. • Observability analysis to understand the • Compared the performance of three Gaussian effects of sensor motion on acoustic filters: EKF, UKF and CIUKF. feature triangulation Fig. Effects of sonar motion on feature triangulation

2017 IEEE International Conference on Robotics and Automation