Seminal works in Robotic Manipulation
compiled for
IROS’2014 Workshop on Robot Manipulation:
What has been achieved and what remains to be done?
Organizers: Erol S¸ahin and Siddhartha Srinivasa
Sept. 14, 2014
Title: What has been achieved and what remains to be done: Much and much.
Speaker: Matt Mason, Carnegie Mellon University
Seminals:
Goertz, teleoperation.
Goertz, R.C. “Manipulators used for handling radioactive materials” Chap. 27 in Human Factors
in Technology, edited by Edward Bennett, James Degan, and Joseph Spiegel, 425–443. New York:
McGraw-Hill, 1963.
STRIPS.
Fikes, R. E., and N. J. Nilsson. “STRIPS: A New Approach to the Applications of Theorem Proving
to Problem Solving.” Artificial Intelligence 2, no. 3 (1971): 189–208.
Sampling based motion planning.
Kavraki, L.E., P. Svestka, J.C. Latombe, and M.H. Overmars. “Probabilistic roadmaps for path plan-
ning in high-dimensional configuration spaces.” Robotics and Automation, IEEE Transactions on 12,
no. 4 (1996): 566–580.
LaValle, Steven M., and James J. Kuffner. “Randomized kinodynamic planning.” The International
Journal of Robotics Research 20.5 (2001): 378–400.
Hirochika Inoue, force control.
Inoue, H. “Computer controlled bilateral manipulator.” Bulletin of JSME 14, no. 69 (1971): 199?207.
issn: 0021–3764.
CSpace for path planning
Lozano-P
´
erez, T. and Wesley, M.A. “An algorithm for planning collision-free paths among polyhe-
dral obstacles.” Communications of the ACM 22, no. 10 (1979): 560–570.
Robodoc.
Kazanzides, P., Zuhars, J., Mittelstadt, B., and Taylor, R. H. (1992, May). “Force sensing and con-
trol for a surgical robot.” In Robotics and Automation, 1992. Proceedings., 1992 IEEE International
Conference on (pp. 612–617). IEEE.
1
Title: Minimalist Design, where Hardware gets Hard
Speaker: William T. Townsend, Barrett Tech.
Seminal events:
1987 WAM-arm beginnings at MIT. Pre-haptics, mechanical bandwidth, and 2nd-Law thermodynamics. Robots
that work with people.
ftp://publications.ai.mit.edu/ai-publications/pdf/AITR-1054.pdf
US Patent 4,903,536 Cable differential.
US Patent 5,046,375 High-speed cable drives
US Patent 5,207,114 Whole-arm manipulation
US Patent 5,193,963 Force-reflecting teleop master
1988 Barrett founded offering high-end robotic-manipulation alternatives for researchers pushing the limits of
manipulation.
http://en.wikipedia.org/wiki/Barrett_Technology
US Patent 5,388,480 Cable-drive pretensioner
US Patent D352,050 Robotic wrist
US Patent D351,849 Robotic shoulder
1989-2001 Impossibly tough going(!)
1995 Introduction of the Barrett Hand, a minimalist design.
US Patent 4,957,320 Hand clutch break-away mechanism
US Patent 5,501,498 Hand spread action
US Patent 7,168,748 Eye-In-Hand
2004 The Puck brushless motor controller and birth of the modern WAM. Major breakthrough.
US Patent 7,854,631 Puck – Primary patent very broad claim
US Patent 7,511,443 Puck – Secondary patent narrower claims
US Patent 7,893,644 Puck – Secondary patent on heat-transfer
2014 Puck (P3) finished at 2.5 grams and diameter of a penny.
http://web.barrett.com/temp/P3-PreliminaryDataSheet.pdf
2015 New applications – Proficio – human-scale haptics for stroke rehabilitation.
http://www.barrettmedical.com
2
Title: How to think about robot hands and grasping.
Speaker: Robert D. Howe, Harvard U.
Seminals:
Mason, M. T., & Salisbury Jr, J. K. (1985). “Robot hands and the mechanics of manipulation.” MIT press.
Jacobsen, S. C., E. K. Iversen, D. Knutti, R. Johnson, & K. Biggers. ”Design of the Utah/MIT dextrous
hand.” In Proc. of ICRA’1986.
Fearing, Ronald S. ”Tactile sensing mechanisms.” The International Journal of Robotics Research 9(3):3-23,
1990.
Howe, Robert D., and Mark R. Cutkosky. “Sensing skin acceleration for slip and texture perception.” In
Proc. of ICRA’1989.
Dollar, Aaron M., and Robert D. Howe. “A robust compliant grasper via shape deposition manufactur-
ing,” IEEE/ASME Transactions on Mechatronics 11(2):154-161, 2006.
Odhner, L.U., Jentoft, L.P., Claffee, M.R., Corson, N., Tenzer, Y., Ma, R.R., Buehler, M, Kohout, R., Howe,
R.D., & Dollar, A.M.. ”A compliant, underactuated hand for robust manipulation.” The International
Journal of Robotics Research 33(5): 736-752, 2014.
Yaroslav, T., Jentoft, L.P., & Howe, R.D. ”Inexpensive and easily customized tactile array sensors using
MEMS barometers chips.” IEEE Robotics and Automation Magazine, in press (Sept. 2014).
DARPA’s ARM-S program, reported in the Special issue on autonomous grasping and manipulation,
Autonomous Robots 36(1-2), January 2014.
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Title: Manipulation planning: past, present and future.
Speaker: Tom´as Lozano-P´erez, MIT.
Seminals:
Motion planning + Grasp Planning
Lozano-P
´
erez, T., Jones, J., Mazer, E., O’Donnell, P., Grimson, W., Tournassoud, P., and Lanusse, A.
”Handey: A robot system that recognizes, plans, and manipulates.” In Proc. of ICRA’1987.
Sim
´
eon, T., Laumond, J. P., Cort
´
es, J., and Sahbani, A., ”Manipulation planning with probabilistic
roadmaps”, The International Journal of Robotics Research, 23(7-8), 729-746 (2004).
Hauser, K., and Latombe, J. C. ”Multi-modal motion planning in non-expansive spaces.” The Inter-
national Journal of Robotics Research, (2009).
Symbolic Action Planning + Manipulation Planning
Nilsson, Nils J., ”Shakey the robot” SRI INTERNATIONAL MENLO PARK CA, 1984.
Cambon, S., Alami, R., & Gravot, F. ”A hybrid approach to intricate motion, manipulation and task
planning”, The International Journal of Robotics Research, 28(1), 104-126, 2009.
Kaelbling, L. P., & Lozano-P
´
erez, T., ”Hierarchical planning in the now”, In Workshops at the Twenty-
Fourth AAAI Conference on Artificial Intelligence (2010).
Robot Planning with Uncertainty
Lozano-P
´
erez, T., Mason, M.T., & Taylor, R.H., ”Automatic synthesis of fine-motion strategies for
robots”, The International Journal of Robotics Research, 3(1), 3-24 (1984).
Kaelbling, L. P., Littman, M.L., & Cassandra, A.R., ”Planning and acting in partially observable
stochastic domains”, Artificial intelligence, 101(1), 99-134, (1998).
Platt, R., Tedrake, R., Lozano-P
´
erez, T. & Kaelbling, L., ”Belief space planning assuming maximum
likelihood observations”, Proc. of RSS’2010.
Manipulation and Task Planning in Belief Space
Kaelbling, L. P., & Lozano-P
´
erez, T. ”Integrated task and motion planning in belief space”, The Inter-
national Journal of Robotics Research, (2013).
4
Title: Learning and Optimization in Robotic Manipulation
Speaker: Pieter Abbeel, UC Berkeley.
Seminals:
Optimization-based Motion Planning
Khatib, O. ”Real-time obstacle avoidance for manipulators and mobile robots”, The international
journal of robotics research, 5(1), 90-98, (1986).
Ratliff, N., Zucker, M., Bagnell, J. A., & Srinivasa, S., ”CHOMP: Gradient optimization techniques for
efficient motion planning”, In Proc. of ICRA’2009.
Schulman, J., Ho, J., Lee, A., Awwal, I., Bradlow, H., & Abbeel, P., ”Finding Locally Optimal, Collision-
Free Trajectories with Sequential Convex Optimization”, In Proc. of RSS’2013.
Belief space planning
van den Berg, J., Abbeel, P., & Goldberg, K., ”LQG-MP: Optimized Path Planning for Robots with
Motion Uncertainty and Imperfect State Information”, Proc. of RSS’2010.
Platt, R., Tedrake, R., Lozano-P
´
erez, T. & Kaelbling, L., ”Belief space planning assuming maximum
likelihood observations”, Proc. of RSS’2010.
Patil, S., Kahn, G., Laskey, M., Schulman, J., Goldberg, K., & Abbeel, P., ”Scaling up Gaussian Belief
Space Planning through Covariance-Free Trajectory Optimization and Automatic Differentiation”,
Proc. of WAFR’2014.
Learning from demonstrations
Abbeel, P., Coates, A., & Ng, A. Y., ”Autonomous helicopter aerobatics through apprenticeship learn-
ing”, The International Journal of Robotics Research, (2010).
Schulman, J., Ho, J., Lee, C., & Abbeel, P., ”Learning from Demonstrations Through the Use of Non-
Rigid Registration”, In Proc. of. ISRR’2013
Reinforcement learning
Peters, J., & Schaal, S., ”Natural actor-critic”, Neurocomputing, 71(7), 1180-1190, (2008).
Tang, J., & Abbeel, P., ”On a connection between importance sampling and the likelihood ratio policy
gradient”, In Proc. of NIPS’2010.
Levine S., Koltun, V., ”Learning Complex Neural Network Policies with Trajectory Optimization”,
Proc. of ICML’2014.
Levine, S., Abbeel, P., ”Trajectory Optimization under Unknown Dynamics for Policy Search”, Proc.
of NIPS’2014.
Hierarchical planning
Kaelbling, L.P., & Lozano-P
´
erez, T., ”Hierarchical planning in the now”, In Workshops at the AAAI’2010.
Srivastava, S., Fang, E., Riano, L., Chitnis, R., Russell, S. & Abbeel, P., ”Combined Task and Motion
Planning through an Extensible Planner-Independent Interface Layer”, Proc. of ICRA’2014
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