Combining motion planning and optimization for flexible robot manipulation

2010 10th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2010

Volumn , Issue , 2010, Pages 80-85

  Scholz, Jonathan ^a   Stilman, Mike ^a  

^a Georgia Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FLEXIBLE ROBOTS; HIGH-DIMENSIONAL PROBLEMS; HUMAN ENVIRONMENT; MANIPULATION TASK; MULTIPLE OBJECTS; OBJECT MOTION; OPTIMIZATION CRITERIA; REINFORCEMENT LEARNING METHOD; ROBOT ARMS; ROBOT MOTION PLANNING; SEARCH METHOD; UNCERTAIN DYNAMICS;

ALGORITHMS; ANTHROPOMORPHIC ROBOTS; MOTION PLANNING; OPTIMIZATION; PLANNING;

ROBOT PROGRAMMING;

EID: 79851474083     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICHR.2010.5686849     Document Type: Conference Paper

References (24)

1. B.D. Argall, S. Chernova, M. Veloso, and B. Browning. A survey of robot learning from demonstration. Robotics and Autonomous Systems, 57(5):469-483, 2009.
2. C.G. Atkeson and S. Schaal. Robot learning from demonstration. In Machine Learning-International Workshop then conference, pages 12-20. Citeseer, 1997.
3. D.C. Bentivegna and C.G. Atkeson. Learning from observation using primitives. In IEEE International Conference on Robotics and Automation, volume 2, pages 1988-1993. Citeseer, 2001.
4. S. Brown and C. Sammut. An architecture for tool use and learning in robots. In Australian Conference on Robotics and Automation. Citeseer, 2007.
5. P. Cheng, J. Fink, and V. Kumar. Abstractions and Algorithms for Cooperative Multiple Robot Planar Manipulation. Robotics: Science and Systems IV, page 143, 2009.
6. T. Dean, L.P. Kaelbling, J. Kirman, and A. Nicholson. Planning with deadlines in stochastic domains. In Proceedings of the Eleventh National Conference on Artificial Intelligence, pages 574-579. Citeseer, 1993.
7. B. Dillman and P. Steinhaus. ARMAR II-a learning and cooperative multimodal humanoid robot system. International Journal of Humanoid Robotics, 1(1):143-155, 2004.
8. E. Frazzoli, M.A. Dahleh, and E. Feron. Robust hybrid control for autonomous vehicle motion planning. In Proceedings of the 39th IEEE Conference on Decision and Control, 2000, volume 1, 2000.
9. SF Giszter, FA Mussa-Ivaldi, and E. Bizzi. Convergent force fields organized in the frog's spinal cord. Journal of Neuroscience, 13(2):467-491, 1993. (Pubitemid 23045133)
10. H. Imamizu, S. Miyauchi, T. Tamada, Y. Sasaki, R. Takino, B. Putz, T. Yoshioka, and M. Kawato. Human cerebellar activity reflecting an acquired internal model of a new tool. Nature, 403(6766):192-195, 2000. (Pubitemid 30050961)
11. L.P. Kaelbling, M.L. Littman, and A.W. Moore. Reinforcement learning: A survey. Journal of Artificial Intelligence, 4(1):237-285, 1996. (Pubitemid 126646155)
12. D. Katz, Y. Pyuro, and O. Brock. Learning to manipulate articulated objects in unstructured environments using a grounded relational representation. In Robotics: Science and Systems. Citeseer, 2008.
13. L.E. Kavraki and J.C. Latombe. Probabilistic roadmaps for robot path planning. Practical Motion Planning in Robotics: Current Approaches and Future Directions, 53, 1998.
14. JJ Kuffner Jr and SM LaValle. RRT-connect: An efficient approach to single-query path planning. In IEEE International Conference on Robotics and Automation, 2000. Proceedings. ICRA'00, volume 2, 2000.
15. S. LaValle and J. Kuffner. Rapidly-exploring random trees: Progress and prospects. In Algorithmic and computational robotics: new directions: the fourth Workshop on the Algorithmic Foundations of Robotics, page 293. AK Peters, Ltd., 2001.
16. Frank C. Park and Jaeyoung Haan. srlib - snu robot dynamics library. http://r-station.co.kr/srlib/.
17. J. Peters, S. Vijayakumar, and S. Schaal. Reinforcement learning for humanoid robotics. In Proc. 3rd IEEE-RAS Intl Conf. on Humanoid Robots, pages 29-30. Citeseer, 2003.
18. A. Safonova, N.S. Pollard, and J.K. Hodgins. Optimizing human motion for the control of a humanoid robot. In 2nd International Symposium on Adaptive Motion of Animals and Machines (AMAM2003). Citeseer, 2003.
19. A. Shkolnik, M. Levashov, S. Itani, and R. Tedrake. Motion planning for bounding on rough terrain with the littledog robot. In Submitted to the International Conference on Robotics and Automation, Anchorage, Alaska. IEEE/RAS, 2010.
20. M. Stilman and J.J. Kuffner. Navigation among movable obstacles: Real-time reasoning in complex environments. In Proc. IEEE Int. Conf. on Humanoid Robotics (Humanoids'04), 2004.
21. R.S. Sutton and A.G. Barto. Reinforcement Learning: An Introduction. MIT Press, 2004.
22. A.L. Thomaz and C. Breazeal. Reinforcement learning with human teachers: Evidence of feedback and guidance with implications for learning performance. In Proceedings of the National Conference on Artificial Intelligence, volume 21, page 1000. Menlo Park, CA; Cambridge, MA; London; AAAI Press; MIT Press; 1999, 2006.
23. E. Todorov. Optimality principles in sensorimotor control. Nature Neuroscience, 7(9):907-915, 2004. (Pubitemid 39129496)
24. D.M. Wolpert and Z. Ghahramani. Computational principles of movement neuroscience. nature neuroscience, 3:1212-1217, 2000.