Algorithmics of Motion: from Robotics, Through Structural Biology, Toward Atomic-Scale CAD Juan Cortés

Total Page:16

File Type:pdf, Size:1020Kb

Algorithmics of Motion: from Robotics, Through Structural Biology, Toward Atomic-Scale CAD Juan Cortés Algorithmics of motion: From robotics, through structural biology, toward atomic-scale CAD Juan Cortés To cite this version: Juan Cortés. Algorithmics of motion: From robotics, through structural biology, toward atomic-scale CAD. Robotics [cs.RO]. Universite Toulouse III Paul Sabatier, 2014. tel-01110545 HAL Id: tel-01110545 https://tel.archives-ouvertes.fr/tel-01110545 Submitted on 28 Jan 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Habilitation a Diriger des Recherches (HDR) delivr´eepar l'Universit´ede Toulouse pr´esent´eeau Laboratoire d'Analyse et d'Architecture des Syst`emes par : Juan Cort´es Charg´ede Recherche CNRS Algorithmics of Motion: From Robotics, Through Structural Biology, Toward Atomic-Scale CAD Soutenue le 18 Avril 2014 devant le Jury compos´ede : Michael Nilges Institut Pasteur, Paris Rapporteurs Fr´ed´ericCazals INRIA Sophia Antipolis-Mediterrane St´ephane Doncieux ISIR, UPMC-CNRS, Paris Oliver Brock Technische Universit¨atBerlin Examinateurs Jean-Pierre Jessel IRIT, UPS, Toulouse Jean-Paul Laumond LAAS-CNRS, Toulouse Pierre Monsan INSA, Toulouse Membre invit´e Thierry Sim´eon LAAS-CNRS, Toulouse Parrain Contents Curriculum Vitæ1 1 Research Activities5 1.1 Introduction...................................5 1.2 Methodological advances............................6 1.2.1 Algorithmic developments in a general framework...........6 1.2.2 Methods for molecular modeling and simulation............ 13 1.3 Applications in robotics............................ 17 1.3.1 Manipulation and Grasping....................... 17 1.3.2 Motion planning for aerial robots.................... 19 1.4 Applications in structural biology, biotechnology and materials science................................ 21 1.4.1 Modeling conformational transitions of proteins and peptides.... 21 1.4.2 Analyzing and predicting molecular interactions........... 24 1.4.3 Polymer modeling............................ 26 2 Other Activities 27 2.1 Teaching and Advising Activities....................... 27 2.1.1 Teaching................................. 27 2.1.2 Advising.................................. 28 2.2 Organizational and Editorial Activities.................... 29 2.2.1 Chairing activities, organization de conferences et workshops.... 29 2.2.2 Editorial activities............................ 30 2.2.3 Other organizational and evaluation duties.............. 30 2.3 Projects and collaborations.......................... 30 2.3.1 Contractual projects........................... 30 2.3.2 Other collaborations........................... 32 2.4 Mobility..................................... 34 2.4.1 Disciplinary mobility........................... 34 2.4.2 Geographic mobility........................... 34 2.5 Software development............................. 35 2.5.1 Move3D.................................. 35 2.5.2 MoMA................................... 35 2.6 Technology transfer, industrial relationships................. 36 3 Research Project 37 3.1 Overview.................................... 37 3.2 Methodological developments......................... 38 3.3 Robotics applications: motion planning and control of aerial robots................. 39 3.4 Towards integrative approaches in structural biology............ 40 3.5 Computational Protein Design........................ 41 ii Contents 3.6 Towards atomic-scale CAD.......................... 42 4 List of Publications 45 Annex 1: Selected Publications 51 Curriculum Vitæ Full name: Juan Cort´es-Mastral Date of birth: 15/08/1974 Place of birth: Zaragoza, Spain Marital status: Married, 1 child Professional address: LAAS-CNRS 7 Av. Colonel Roche, F-31400 Toulouse, France Phone: +33 5 61 33 63 45 Fax: +33 5 61 33 64 55 E-mail: [email protected] Web: http://homepages.laas.fr/jcortes/ Professional Experience CNRS Researcher at LAAS-CNRS (Toulouse) From Oct. 2004 • Area: Algorithmics of motion, with applications in robotics, structural biology, biotechnology and materials science Invited Professor at IRI (CSIC-UPC, Barcelona) Nov. 2008 - Nov. 2009 • Subject: New approaches to peptide and polymer modeling Post-doctoral Researcher at UFIP (Univ. Nantes-CNRS) Mar. 2004 - Sep. 2004 • Subject: Computational prediction and analysis of protein loop motions PhD thesis preparation at LAAS-CNRS (Toulouse) Oct. 2000 - Dec. 2003 • Subject: Motion planning algorithms for close-chain mechanisms Undergrad. Research Assistant at LAAS-CNRS (Toulouse) Aug. 1999 - Sep. 2000 • Subject: Participation to the development of Move3D: a generic path-planning software platform Education PhD - Computer science / Robotics December 2003 • Institut National Polytechnique de Toulouse (France) Dipl^omed'Etudes Approfondies (Master) - Control / Robotics July 2000 • Institut National Polytechnique de Toulouse (France) Engineering Degree - Specialization in Control and Robotics June 2000 • Centro Polit´ecnicoSuperior - Universidad de Zaragoza (Spain) Awards Prix Jean Lagasse : Award to the best PhD theses of the CNRS STIC department, 2004 • Prix L´eopold Escande : Award to the best PhD theses of the INP Toulouse, 2004 • 2 Curriculum Vitæ Summary of Research and Teaching Activities Research Topics Basic research, Robotics: Algorithmics of motion. Motion computation and analysis for • complex systems. Applications in robotics, mainly to motion planning and manipulation task planning. Interdisciplinary research: Development of computational methods to study protein flex- • ibility and interactions, for protein design, and polymer modeling. Applications in structural biology, biotechnology and materials science. Publications 20 articles in scientific journals on robotics (IEEE Trans. Robot., Int. J. Robot. Res.), • bioinformatics and theoretical physical chemistry (Bioinformatics, J. Comput. Chem., Proteins, Polymer, Nucl. Acids Res., among others). 4 book chapters. • 23 publications in proceedings of international conferences and workshops. • 5 invited talks, and 9 seminars in French and foreign universities. • Google Scholar h-index = 20 ; 1133 citations. • Advising activities Advisor or co-advisor of 8 PhD students and 6 post-docs. • Advisor of 12 undergraduate students. • Scientific advisor of 1 CNRS Research Engineer. • Teaching Co-organizer and teacher of the international, interdisciplinary school \Algorithms in • Structural Bioinformatics", 2012, 2013. ( http://algosb.sciencesconf.org/ ) Member of the teaching team of the master program \Ing´enieriede la Mati`ere: Mod´elisa- • tion des Processus Physiques", Universit´ede Toulouse, since 2008. Teacher in the \Master en Simulaci´onde Pol´ımerosy Biopol´ımeros", Universidad Poli- • t`ecnicade Catalunya (Barcelona, Spain), 2011. Teacher in the \Master en Syst`emesAutomatiques, Informatiques et D´ecisionnels", • Universit´ede Toulouse, 2008-2010. Teacher in the \Master de Rob´otica"of the Universidad Polit´ecnicade Valencia (Spain), • 2008. Teacher in the \Summer School on Image & Robotics", CIC Mexico, 2007. • 3 Organizational and editorial activities Co-chair of the IEEE RAS Technical Committee on Algorithms for Planning and Control • of Robot Motion, since 2009. Co-organizer of the AAAI Workshop on “Artificial Intelligence and Robotics Methods • in Computational Biology", 2013. Co-organizer of the ACM-BCB Tutorial \From Robot Motion Planning to Modeling • Structures and Motions of Biological Molecules", 2013. Co-organizer of the RSS Workshop \Motion Planning: From Theory to Practice", 2010. • Program Committee Member of the Computational Structural Bioinformatics Workshop • (CSBW), 2011-2013. Program Committee Member of the international conference ECAI 2008, 2010. • Associated Editor of the IEEE international conferences ICRA and IROS, 2009-2013. • Reviewer of : IEEE Journals and Conferences (T-RO, T-ASE, ICRA, IROS, ...), The • International Journal of Robotics Research, Workshop on the Algorithmic Foundations of Robotics, Journal of Computations Chemistry, Journal of Chemical Theory and Com- putation, Bioinformatics, Archives of Biochemistry and Biophysics, ... Software development Coordinator of the developments of MoMA, a software platform for molecular modeling. • Participation in the development of Move3D, a generic motion planning software. • Mobility Disciplinary mobility: Being robotics my basic research area, I am interested in the de- • velopment of methods in structural biology and materials science, as well as in applications to biotechnologies and nanotechnologies. Geographic mobility: One-year stay (Nov. 2008 - Nov. 2009) at the l'Universidad • Polit´ecnicade Catalunya (Barcelona, Spain), in the framework of international mobility pro- grams of the CNRS and the INPT. Participation in projets Robotics projects: 6 European projects (ARCAS, SAPHARI, DEXMART, PHRIENDS, • MOVIE, MOLOG), 1 French national project (IRASIS). Computational biology / Molecular modeling projects: 3 French national projects • (ProtiCAD, GlucoDesign, NanoBioMod), 1 regional project (AMYLO), 1 trans-regional project (AMOBIO), 3 local projects (ITAV-ALMA, OTIMASU, AMORO), 1 CNRS project (BioMove3D), 1 ADEME project.
Recommended publications
  • Mobile Robot Kinematics
    Mobile Robot Kinematics We're going to start talking about our mobile robots now. There robots differ from our arms in 2 ways: They have sensors, and they can move themselves around. Because their movement is so different from the arms, we will need to talk about a new style of kinematics: Differential Drive. 1. Differential Drive is how many mobile wheeled robots locomote. 2. Differential Drive robot typically have two powered wheels, one on each side of the robot. Sometimes there are other passive wheels that keep the robot from tipping over. 3. When both wheels turn at the same speed in the same direction, the robot moves straight in that direction. 4. When one wheel turns faster than the other, the robot turns in an arc toward the slower wheel. 5. When the wheels turn in opposite directions, the robot turns in place. 6. We can formally describe the robot behavior as follows: (a) If the robot is moving in a curve, there is a center of that curve at that moment, known as the Instantaneous Center of Curvature (or ICC). We talk about the instantaneous center, because we'll analyze this at each instant- the curve may, and probably will, change in the next moment. (b) If r is the radius of the curve (measured to the middle of the robot) and l is the distance between the wheels, then the rate of rotation (!) around the ICC is related to the velocity of the wheels by: l !(r + ) = v 2 r l !(r − ) = v 2 l Why? The angular velocity is defined as the positional velocity divided by the radius: dθ V = dt r 1 This should make some intuitive sense: the farther you are from the center of rotation, the faster you need to move to get the same angular velocity.
    [Show full text]
  • Abbreviations and Glossary
    Appendix A Abbreviations and Glossary Abbreviations are defined and the mathematical symbols and notations used in this book are specified. Furthermore, the random number generator used in this book is referenced. A.1 Abbreviations arccos arccosine BiRRT Bidirectional rapidly growing random tree C-space Configuration space DH Denavit-Hartenberg DLR German aerospace center DOF Degree of freedom FFT Fast fourier transformation IK Inverse kinematics HRI Human-Robot interface LWR Light weight robot MMI Institute of Man-Machine interaction PCA Principal component analysis PRM Probabilistic road map RRT Rapidly growing random tree rulaCapMap Rula-restricted capability map RULA Rapid upper limb assessment SFE Shape fit error TCP Tool center point OV workspace overlap 130 A Abbreviations and Glossary A.2 Mathematical Symbols C configuration space K(q) direct kinematics H set of all homogeneous matrices WR reachable workspace WD dexterous workspace WV versatile workspace F(R,x) function that maps to a homogeneous matrix VRobot voxel space for the robot arm VHuman voxel space for the human arm P set of points on the sphere Np set of point indices for the points on the sphere No set of orientation indices OS set of all homogeneous frames distributed on a sphere MS capability map A.3 Mathematical Notations a scalar value a vector aT vector transposed A matrix AT matrix transposed < a,b > inner product 3 SO(3) group of rotation matrices ∈ IR SO(3) := R ∈ IR 3×3| RRT = I,detR =+1 SE(3) IR 3 × SO(3) A TB reference frame B given in coordinates of reference frame A a ceiling function a floor function A.4 Random Sampling In this book, the drawing of random samples is often used.
    [Show full text]
  • Theoretical Computer Science Knowledge a Selection of Latest Research Visit Springer.Com for an Extensive Range of Books and Journals in the field
    ABCD springer.com Theoretical Computer Science Knowledge A Selection of Latest Research Visit springer.com for an extensive range of books and journals in the field Theory of Computation Classical and Contemporary Approaches Topics and features include: Organization into D. C. Kozen self-contained lectures of 3-7 pages 41 primary lectures and a handful of supplementary lectures Theory of Computation is a unique textbook that covering more specialized or advanced topics serves the dual purposes of covering core material in 12 homework sets and several miscellaneous the foundations of computing, as well as providing homework exercises of varying levels of difficulty, an introduction to some more advanced contempo- many with hints and complete solutions. rary topics. This innovative text focuses primarily, although by no means exclusively, on computational 2006. 335 p. 75 illus. (Texts in Computer Science) complexity theory. Hardcover ISBN 1-84628-297-7 $79.95 Theoretical Introduction to Programming B. Mills page, this book takes you from a rudimentary under- standing of programming into the world of deep Including well-digested information about funda- technical software development. mental techniques and concepts in software construction, this book is distinct in unifying pure 2006. XI, 358 p. 29 illus. Softcover theory with pragmatic details. Driven by generic ISBN 1-84628-021-4 $69.95 problems and concepts, with brief and complete illustrations from languages including C, Prolog, Java, Scheme, Haskell and HTML. This book is intended to be both a how-to handbook and easy reference guide. Discussions of principle, worked Combines theory examples and exercises are presented. with practice Densely packed with explicit techniques on each springer.com Theoretical Computer Science Knowledge Complexity Theory Exploring the Limits of Efficient Algorithms computer science.
    [Show full text]
  • Graph Visualization and Navigation in Information Visualization 1
    HERMAN ET AL.: GRAPH VISUALIZATION AND NAVIGATION IN INFORMATION VISUALIZATION 1 Graph Visualization and Navigation in Information Visualization: a Survey Ivan Herman, Member, IEEE CS Society, Guy Melançon, and M. Scott Marshall Abstract—This is a survey on graph visualization and navigation techniques, as used in information visualization. Graphs appear in numerous applications such as web browsing, state–transition diagrams, and data structures. The ability to visualize and to navigate in these potentially large, abstract graphs is often a crucial part of an application. Information visualization has specific requirements, which means that this survey approaches the results of traditional graph drawing from a different perspective. Index Terms—Information visualization, graph visualization, graph drawing, navigation, focus+context, fish–eye, clustering. involved in graph visualization: “Where am I?” “Where is the 1 Introduction file that I'm looking for?” Other familiar types of graphs lthough the visualization of graphs is the subject of this include the hierarchy illustrated in an organisational chart and Asurvey, it is not about graph drawing in general. taxonomies that portray the relations between species. Web Excellent bibliographic surveys[4],[34], books[5], or even site maps are another application of graphs as well as on–line tutorials[26] exist for graph drawing. Instead, the browsing history. In biology and chemistry, graphs are handling of graphs is considered with respect to information applied to evolutionary trees, phylogenetic trees, molecular visualization. maps, genetic maps, biochemical pathways, and protein Information visualization has become a large field and functions. Other areas of application include object–oriented “sub–fields” are beginning to emerge (see for example Card systems (class browsers), data structures (compiler data et al.[16] for a recent collection of papers from the last structures in particular), real–time systems (state–transition decade).
    [Show full text]
  • Experimental Algorithmics from Algorithm Desig
    Lecture Notes in Computer Science 2547 Edited by G. Goos, J. Hartmanis, and J. van Leeuwen 3 Berlin Heidelberg New York Barcelona Hong Kong London Milan Paris Tokyo Rudolf Fleischer Bernard Moret Erik Meineche Schmidt (Eds.) Experimental Algorithmics From Algorithm Design to Robust and Efficient Software 13 Volume Editors Rudolf Fleischer Hong Kong University of Science and Technology Department of Computer Science Clear Water Bay, Kowloon, Hong Kong E-mail: [email protected] Bernard Moret University of New Mexico, Department of Computer Science Farris Engineering Bldg, Albuquerque, NM 87131-1386, USA E-mail: [email protected] Erik Meineche Schmidt University of Aarhus, Department of Computer Science Bld. 540, Ny Munkegade, 8000 Aarhus C, Denmark E-mail: [email protected] Cataloging-in-Publication Data applied for A catalog record for this book is available from the Library of Congress. Bibliographic information published by Die Deutsche Bibliothek Die Deutsche Bibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data is available in the Internet at <http://dnb.ddb.de> CR Subject Classification (1998): F.2.1-2, E.1, G.1-2 ISSN 0302-9743 ISBN 3-540-00346-0 Springer-Verlag Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag.
    [Show full text]
  • Algorithmics and Modeling Aspects of Network Slicing in 5G and Beyonds Network: Survey
    Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000. Digital Object Identifier 10.1109/ACCESS.2017.DOI Algorithmics and Modeling Aspects of Network Slicing in 5G and Beyonds Network: Survey FADOUA DEBBABI1,2, RIHAB JMAL2, LAMIA CHAARI FOURATI2,AND ADLENE KSENTINI.3 1University of Sousse, ISITCom, 4011 Hammam Sousse,Tunisia (e-mail: [email protected]) 2Laboratory of Technologies for Smart Systems (LT2S) Digital Research Center of Sfax (CRNS), Sfax, Tunisia (e-mail: [email protected] [email protected] ) 3Eurecom, France (e-mail: [email protected] ) Corresponding author: Rihab JMAL (e-mail:[email protected]). ABSTRACT One of the key goals of future 5G networks is to incorporate many different services into a single physical network, where each service has its own logical network isolated from other networks. In this context, Network Slicing (NS)is considered as the key technology for meeting the service requirements of diverse application domains. Recently, NS faces several algorithmic challenges for 5G networks. This paper provides a review related to NS architecture with a focus on relevant management and orchestration architecture across multiple domains. In addition, this survey paper delivers a deep analysis and a taxonomy of NS algorithmic aspects. Finally, this paper highlights some of the open issues and future directions. INDEX TERMS Network Slicing, Next-generation networking, 5G mobile communication, QoS, Multi- domain, Management and Orchestration, Resource allocation. I. INTRODUCTION promising solutions to such network re-engineering [3]. A. CONTEXT AND MOTIVATION NS [9] allows the creation of several Fully-fledged virtual networks (core, access, and transport network) over the HE high volume of generated traffics from smart sys- same infrastructure, while maintaining the isolation among tems [1] and Internet of Everything applications [2] T slices.The FIGURE 1 shows the way different slices are complicates the network’s activities and management of cur- isolated.
    [Show full text]
  • Nyku: a Social Robot for Children with Autism Spectrum Disorders
    University of Denver Digital Commons @ DU Electronic Theses and Dissertations Graduate Studies 2020 Nyku: A Social Robot for Children With Autism Spectrum Disorders Dan Stephan Stoianovici University of Denver Follow this and additional works at: https://digitalcommons.du.edu/etd Part of the Disability Studies Commons, Electrical and Computer Engineering Commons, and the Robotics Commons Recommended Citation Stoianovici, Dan Stephan, "Nyku: A Social Robot for Children With Autism Spectrum Disorders" (2020). Electronic Theses and Dissertations. 1843. https://digitalcommons.du.edu/etd/1843 This Thesis is brought to you for free and open access by the Graduate Studies at Digital Commons @ DU. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of Digital Commons @ DU. For more information, please contact [email protected],[email protected]. Nyku : A Social Robot for Children with Autism Spectrum Disorders A Thesis Presented to the Faculty of the Daniel Felix Ritchie School of Engineering and Computer Science University of Denver In Partial Fulfillment of the Requirements for the Degree Master of Science by Dan Stoianovici August 2020 Advisor: Dr. Mohammad H. Mahoor c Copyright by Dan Stoianovici 2020 All Rights Reserved Author: Dan Stoianovici Title: Nyku: A Social Robot for Children with Autism Spectrum Disorders Advisor: Dr. Mohammad H. Mahoor Degree Date: August 2020 Abstract The continued growth of Autism Spectrum Disorders (ASD) around the world has spurred a growth in new therapeutic methods to increase the positive outcomes of an ASD diagnosis. It has been agreed that the early detection and intervention of ASD disorders leads to greatly increased positive outcomes for individuals living with the disorders.
    [Show full text]
  • A Review of Parallel Processing Approaches to Robot Kinematics and Jacobian
    Technical Report 10/97, University of Karlsruhe, Computer Science Department, ISSN 1432-7864 A Review of Parallel Processing Approaches to Robot Kinematics and Jacobian Dominik HENRICH, Joachim KARL und Heinz WÖRN Institute for Real-Time Computer Systems and Robotics University of Karlsruhe, D-76128 Karlsruhe, Germany e-mail: [email protected] Abstract Due to continuously increasing demands in the area of advanced robot control, it became necessary to speed up the computation. One way to reduce the computation time is to distribute the computation onto several processing units. In this survey we present different approaches to parallel computation of robot kinematics and Jacobian. Thereby, we discuss both the forward and the reverse problem. We introduce a classification scheme and classify the references by this scheme. Keywords: parallel processing, Jacobian, robot kinematics, robot control. 1 Introduction Due to continuously increasing demands in the area of advanced robot control, it became necessary to speed up the computation. Since it should be possible to control the motion of a robot manipulator in real-time, it is necessary to reduce the computation time to less than the cycle rate of the control loop. One way to reduce the computation time is to distribute the computation over several processing units. There are other overviews and reviews on parallel processing approaches to robotic problems. Earlier overviews include [Lee89] and [Graham89]. Lee takes a closer look at parallel approaches in [Lee91]. He tries to find common features in the different problems of kinematics, dynamics and Jacobian computation. The latest summary is from Zomaya et al. [Zomaya96].
    [Show full text]
  • Acknowledgements Acknowl
    2161 Acknowledgements Acknowl. B.21 Actuators for Soft Robotics F.58 Robotics in Hazardous Applications by Alin Albu-Schäffer, Antonio Bicchi by James Trevelyan, William Hamel, The authors of this chapter have used liberally of Sung-Chul Kang work done by a group of collaborators involved James Trevelyan acknowledges Surya Singh for de- in the EU projects PHRIENDS, VIACTORS, and tailed suggestions on the original draft, and would also SAPHARI. We want to particularly thank Etienne Bur- like to thank the many unnamed mine clearance experts det, Federico Carpi, Manuel Catalano, Manolo Gara- who have provided guidance and comments over many bini, Giorgio Grioli, Sami Haddadin, Dominic Lacatos, years, as well as Prof. S. Hirose, Scanjack, Way In- Can zparpucu, Florian Petit, Joshua Schultz, Nikos dustry, Japan Atomic Energy Agency, and Total Marine Tsagarakis, Bram Vanderborght, and Sebastian Wolf for Systems for providing photographs. their substantial contributions to this chapter and the William R. Hamel would like to acknowledge work behind it. the US Department of Energy’s Robotics Crosscut- ting Program and all of his colleagues at the na- C.29 Inertial Sensing, GPS and Odometry tional laboratories and universities for many years by Gregory Dudek, Michael Jenkin of dealing with remote hazardous operations, and all We would like to thank Sarah Jenkin for her help with of his collaborators at the Field Robotics Center at the figures. Carnegie Mellon University, particularly James Os- born, who were pivotal in developing ideas for future D.36 Motion for Manipulation Tasks telerobots. by James Kuffner, Jing Xiao Sungchul Kang acknowledges Changhyun Cho, We acknowledge the contribution that the authors of the Woosub Lee, Dongsuk Ryu at KIST (Korean Institute first edition made to this chapter revision, particularly for Science and Technology), Korea for their provid- Sect.
    [Show full text]
  • Forward and Inverse Kinematics Analysis of Denso Robot
    Proceedings of the International Symposium of Mechanism and Machine Science, 2017 AzC IFToMM – Azerbaijan Technical University 11-14 September 2017, Baku, Azerbaijan Forward and Inverse Kinematics Analysis of Denso Robot Mehmet Erkan KÜTÜK 1*, Memik Taylan DAŞ2, Lale Canan DÜLGER1 1*Mechanical Engineering Department, University of Gaziantep Gaziantep/ Turkey E-mail: [email protected] 2 Mechanical Engineering Department, University of Kırıkkale Abstract used Robotic Toolbox in forward kinematics analysis of A forward and inverse kinematic analysis of 6 axis an industrial robot [4]. DENSO robot with closed form solution is performed in This study includes kinematics of robot arm which is this paper. Robotics toolbox provides a great simplicity to available Gaziantep University, Mechanical Engineering us dealing with kinematics of robots with the ready Department, Mechatronics Lab. Forward and Inverse functions on it. However, making calculations in kinematics analysis are performed. Robotics Toolbox is traditional way is important to dominate the kinematics also applied to model Denso robot system. A GUI is built which is one of the main topics of robotics. Robotic for practical use of robotic system. toolbox in Matlab® is used to model Denso robot system. GUI studies including Robotic Toolbox are given with 2. Robot Arm Kinematics simulation examples. Keywords: Robot Kinematics, Simulation, Denso The robot kinematics can be categorized into two Robot, Robotic Toolbox, GUI main parts; forward and inverse kinematics. Forward kinematics problem is not difficult to perform and there is no complexity in deriving the equations in contrast to the 1. Introduction inverse kinematics. Especially nonlinear equations make the inverse kinematics problem complex.
    [Show full text]
  • A Generative Middleware Specialization Process for Distributed Real-Time and Embedded Systems
    A Generative Middleware Specialization Process for Distributed Real-time and Embedded Systems Akshay Dabholkar and Aniruddha Gokhale ∗Dept. of EECS, Vanderbilt University Nashville, TN 37235, USA Email: {aky,gokhale}@dre.vanderbilt.edu Abstract—General-purpose middleware must often be special- domain and product variant – a process we call middleware ized for resource-constrained, real-time and embedded systems specialization. to improve their response-times, reliability, memory footprint, and even power consumption. Software engineering techniques, Most prior efforts at specializing middleware (and other such as aspect-oriented programming (AOP), feature-oriented system artifacts) [1]–[6] often require manual efforts in iden- programming (FOP), and reflection make the specialization task tifying opportunities for specialization and realizing them on simpler, albeit still requiring the system developer to manually identify the system invariants, and sources of performance the software artifacts. At first glance it may appear that these and memory footprint bottlenecks that determine the required manual efforts are expended towards addressing problems that specializations. Specialization reuse is also hampered due to a are purely accidental in nature. A close scrutiny, however, lack of common taxonomy to document the recurring specializa- reveals that system developers face a number of inherent tions. This paper presents the GeMS (Generative Middleware complexities as well, which stem from the following reasons: Specialization) framework to address these challenges. We present results of applying GeMS to a Distributed Real-time 1. Spatial disparity between OO-based middleware design and Embedded (DRE) system case study that depict a 21-35% and domain-level concerns - Middleware is traditionally ˜ reduction in footprint, and a 36% improvement in performance designed using object-oriented (OO) principles, which enforce while simultaneously alleviating 97%˜ of the developer efforts in specializing middleware.
    [Show full text]
  • 1. Immersive Analytics: an Introduction
    1. Immersive Analytics: An Introduction Tim Dwyer1, Kim Marriott1, Tobias Isenberg2, Karsten Klein3, Nathalie Riche4, Falk Schreiber1,3, Wolfgang Stuerzlinger5, and Bruce H. Thomas6 1 Monash University, Australia [Tim.Dwyer, Kim.Marriott]@monash.edu 2 Inria and University Paris-Saclay [email protected] 3 ? University of Konstanz, Germany [Karsten.Klein, Falk Schreiber]@uni-konstanz.de 4 Microsoft, USA [email protected] 5 Simon Fraser University, Canada [email protected] 6 University of South Australia [email protected] Abstract. Immersive Analytics is a new research initiative that aims to remove barriers between people, their data and the tools they use for analysis and decision making. Here we clarify the aims of immersive analytics research, its opportunities and historical context, as well as providing a broad research agenda for the feld. In addition, we review how the term immersion has been used to refer to both technological and psychological immersion, both of which are central to immersive analytics research. Keywords: immersive analytics, multi-sensory, 2D and 3D, data analytics, decision making 1.1. What is Immersive Analytics? Immersive Analytics is the use of engaging, embodied analysis tools to support data understanding and decision making. Immersive analytics builds upon the felds of data visualisation, visual analytics, virtual reality, computer graphics, and human-computer interaction. Its goal is to remove barriers between people, their data, and the tools they use for analysis. It aims to support data understanding and decision making everywhere and by everyone, both working individually and collaboratively. While this may be achieved through the use of immersive virtual environment technologies, multisensory presentation, data physicalisation, natural interfaces, or responsive analytics, the feld of immersive analytics is not tied to the use of specifc techniques.
    [Show full text]