Reading Group

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Administrative Stuff

Machine Learning:

  • We will be meeting in HRL every Friday at 3:00 PM.

Force Control of Manipulators:

  • We will meet on Mondays at 11:00.


Machine Learning/Perception:

  • 6/9/2010: Jan Peters, Sethu Vijayakumar, Stefan Schaal. Reinforcement Learning for Humanoid Robotics. International Conference on Humanoid Robots 2003. pdf
  • 6/11/2010, 6/16/2010 Kober, J.; Peters, J. (2009). Learning Motor Primitives for Robotics, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) pdf
  • 6/23/2010 Jens Kober, and Jan Peters. Policy Search for Motor Primitives in Robotics. NIPS 2008 pdf
  • 6/30/2010 Thomas Ruckstieb, Martin Felder, Jurgen Schmidhuber. State-Dependent Exploration for Policy Gradient Methods. Machine Learning and Knowledge Discovery in Database (2008) pdf
  • 7/13/2010 Jens Kober, Erhan Oztop, and Jan Peters. Reinforcement Learning to adjust Robot Movements to New Situations. RSS 2010. pdf
  • 8/11/2010. Brian D. Ziebart et al. Planning-based Prediction for Pedestrians. IROS 2009 pdf video
  • 8/18/2010. Kei Okada, Mitsuharu Kojima, Satoru Tokutsu, Yuto Mori, Toshiaki Maki, Masayuki Inaba : "Task Guided Attention Control and Visual Verification in Tea Serving by the Daily Assistive Humanoid HRP2JSK", In Proceedings of The 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2008), pp 1551-1557, 2008. (Best Robocup Award) pdf
  • B. Rasolzadeh, M. Björkman, K. Huebner, and D. Kragic. An Active Vision System for Detecting, Fixating and Manipulating Objects in the Real World. IJRR 2009. pdf
  • Roland Johansson and J. Flanagan. Coding and use of tactile signals from the fingertips in object manipulation tasks. Nature Reviews Neuroscience 2009. pdf

Force Control of Manipulators:

Notes from JK Salisbury paper. June 21
  • Jun 21, 2010: J.K. Salisbury, "Active stiffness control of a manipulator in Cartesian coordinates," Proc. 19th IEEE Conference on Decision and Control, 1980.
  • Jun 25, 2010:
    • Look at the thumbnail, Notes from JK Salisbury paper.
    • Stuart Glaser's (Stu's) controller: There's no paper. For citations, please cite the wiki page for the teleop_controllers package and the stack version (pr2_cockpit 0.1). The best reference for how it works is the code (attached). The controller is a riff off of "Simplified Acceleration Based Control Variation 1" from this paper (Comparative experiments on task space control with redundancy resolution by Nakanishi, Cory, Mistry, Peters and Schaal, IROS 2005)
  • July 1, 2010:
    • Read the PR1 paper (pdf)
    • Old paper that the PR1 paper cites for gravity compensation with springs. (pdf)(Not very helpful)
    • Continue discussion on Ken Salisbury paper and EPC.

Authors to Read

Machine Learning:

Force Control of Manipulators:

For initial background

Suggested Papers

  • Hsiao, Kaijen, Chitta Sachin, Ciocarlie Matei, and Jones Gil E. Contact-Reactive Grasping of Objects with Partial Shape Information. IROS 2010.


  • Satoru Ishigaki, Timothy White, Victor Zordan, and C. Karen Liu. Performance-Based Control Interface for Character Animation. SIGGRAPH 2009.
  • Reliable non-prehensile door opening through the combination of vision, tactile and force feedback. Mario Prats · Pedro J. Sanz · Angel P. del Pobil. Auton Robot 2010.
  • Roland S. Johansson, Göran Westling, Anders Bäckström, and J. Randall Flanagan. Eye-Hand Coordination in Object Manipulation. The Journal of Neuroscience, September 1, 2001, 21(17):6917-6932. pdf
  • Emanuel Todorov & Michael I. Jordan. Optimal feedback control as a theory of motor coordination. Nature Neuroscience 5, 1226 - 1235 (2002) pdf

Machine Learning:

  • Fernando De la Torre's component analysis paper.
  • Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smola, and Quoc V. Le. Bundle Methods for Regularized Risk Minimization. Journal of Machine Learning Research, 11:311–365, January 2010. pdf
  • Jan Peters, Stefan Schaal. Policy Gradient Methods for Robotics. IROS 2006. pdf
  • Jan Peters, Stefan Schall. Learning to Control in Operational Space. IJRR 08. download from library website
  • Jonas Buchli, Evangelos Theodorou, Freek Stulp, Stefan Schaal. Variable Impedance Control A Reinforcement Learning Approac. Robotic Systems Science. pdf
  • Detry,R.; Baseski, E.; Popovic, M.; Touati, Y.; Krueger, N.; Kroemer, O.; Peters, J.; Piater, J. (2010). Learning Continuous Grasp Affordances by Sensorimotor Exploration, From Motor Learning to Interaction Learning in Robots, Springer Verlag, 264. pdf
  • Brian D. Ziebart, Andrew Maas, J. Andrew Bagnell, Anind K. Dey. Human Behavior Modeling with Maximum Entropy Inverse Optimal Control. AAAI Spring Symposium on Human Behavior Modeling. 2009 pdf

Force Control of Manipulators:

  • Neville Hogan, Impedance control: an approach to manipulation: parts 1,2, 3

Multi-contact Manipulation

  • Compliant Control of Multicontact and Center-of-Mass Behaviors in Humanoid Robots, Sentis, L. Park, J. Khatib, O. Page(s): 483 - 501 link

Visual Servoing

  • Survey on visual servoing for manipulation. D Kragic, HI Christensen

Skin Sensing

  • Tactile Sensing—From Humans to Humanoids. Dahiya, R.S. Metta, G. Valle, M. Sandini, G., Feb 2010, Volume: 26 Issue: 1. On page(s): 1 - 20 link
  • Tactile Sensing and Control of Robotic Manipulation. Robert D. Howe. Journal of Advanced Robotics, 8(3):245-261, 1994. pdf


Healthcare Robotics

  • Phys Med Rehabil Clin N Am. 2010 Feb;21(1):59-77. Recent trends in the development and evaluation of assistive robotic manipulation devices. Allin S, Eckel E, Markham H, Brewer BR.

This review explores recent trends in the development and evaluation of assistive robotic arms, both prosthetic and externally mounted. Evaluations have been organized according to the CATOR taxonomy of assistive device outcomes, which takes into consideration device effectiveness, social significance, and impact on subjective well-being. Questions that have informed the review include: (1) Are robotic arms being comprehensively evaluated along axes of the CATOR taxonomy? (2) Are definitions of effectiveness in accordance with the priorities of users? (3) What gaps in robotic arm evaluation exist, and how might these best be addressed? (4) What further advances can be expected in the next 15 years? Results highlight the need for increased standardization of evaluation methods, increased emphasis on the social significance (i.e., social cost) of devices, and increased emphasis on device impact on quality of life. Several open areas for future research, in terms of both device evaluation and device development, are also discussed.

  • Applications of robots in rehabilitation. Stan A. Nappera and Ronald L. Seaman. Robotics and Autonomous Systems. Volume 5, Issue 3, November 1989, Pages 227-239. link
* Volume 5, Number 3, November 1989
   * T. Michael Knasel:
     Editorial. 201
     Electronic Edition CiteSeerX Google scholar BibTeX bibliographical record in XML
   * Kent G. Engelhardt:
     Robotics in health and human services. 203
     Electronic Edition CiteSeerX Google scholar BibTeX bibliographical record in XML
   * Kent G. Engelhardt:
     An overview of health and human service robotics. 205-226
     Electronic Edition CiteSeerX Google scholar BibTeX bibliographical record in XML
   * Stan A. Napper, Ronald L. Seaman:
     Applications of robots in rehabilitation. 227-239
     Electronic Edition CiteSeerX Google scholar BibTeX bibliographical record in XML
   * Roger Edwards:
     Diffusion of robotic innovations in health care environments using the interactive evaluation methodology. 241-250
     Electronic Edition CiteSeerX Google scholar BibTeX bibliographical record in XML
   * John Evans, Bala Krishnamurthy, Will Pong, Robert Croston, Carl F. R. Weiman, Gay Engelberger:
     HelpMateTM: A robotic materials transport system. 251-256
     Electronic Edition CiteSeerX Google scholar BibTeX bibliographical record in XML
   * James L. Crowley:
     Planning and execution of tasks for a domestic robot. 257-272
     Electronic Edition CiteSeerX Google scholar BibTeX bibliographical record in XML