Humanoid robots learning to walk faster: From the real world to simulation and back

12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013

Volumn 1, Issue , 2013, Pages 39-46

  Farchy, Alon ^a   Barrett, Samuel ^a   MacAlpine, Patrick ^a   Stone, Peter ^a  

^a University of Texas at Austin   (United States)

Author keywords

Bipedal Robotics; Simulation Machine Learning

Indexed keywords

ANTHROPOMORPHIC ROBOTS; AUTONOMOUS AGENTS; INDUSTRIAL RESEARCH; LEARNING ALGORITHMS; LEARNING SYSTEMS; MULTI AGENT SYSTEMS; SIMULATORS;

BI-PEDAL ROBOTICS; HUMANOID ROBOT; ITERATIVE OPTIMIZATION; MACHINE-LEARNING; OPTIMIZATION LOOP; REAL MODELS; SIMULATION MACHINE; WALKING SPEED;

OPTIMIZATION;

EID: 84899413569     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (34)

1. Open dynamics engine faq. http://ode-wiki.org/wiki/index.php?title=FAQ.
2. SimSpark generic physical multiagent simulator system, http://simspark.sourceforge.net/.
3. P. Abbeel, M. Quigley, and A. Y. Ng. Using inaccurate models in reinforcement learning. In International Conference on Machine Learning (ICML) Pittsburgh, pages 1-8. ACM Press, 2006.
4. J. A. Bagnell and J. Schneider. Autonomous helicopter control using reinforcement learning policy search methods. In International Conference on Robotics and Automation, pages 1615-1620. IEEE Press, 2001.
5. S. Behnke. Online trajectory generation for omnidirectional biped walking. In Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on, pages 1597-1603, May 2006.
6. E. Gat. On the role of simulation in the study of autonomous mobile robots. In AAAI-95 Spring Symposium on Lessons Learned from Implemented Software Architectures for Physical Agents., Stanford, CA, March 1995.
7. C. Graf and T. Röfer. A closed-loop 3D-LIPM gait for the RoboCup Standard Platform League humanoid. In E. Pagello, C. Zhou, S. Behnke, E. Menegatti, T. Röfer, and P. Stone, editors, Proceedings of the Fifth Workshop on Humanoid Soccer Robots in conjunction with the 2010 IEEE-RAS International Conference on Humanoid Robots, Nashville, TN, USA, 2010.
8. J. Grefenstette, C. L. Ramsey, and A. C. Schultz. Learning sequential decision rules using simulation models and competition. In Machine Learning, pages 355-381, 1990.
9. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten. The WEKA data mining software: an update. SIGKDD Explor. Newsl., 11: 10-18, November 2009.
10. N. Hansen. The CMA evolution strategy: A tutorial, 2005.
11. T. Hester, M. Quinlan, and P. Stone. Generalized model learning for reinforcement learning on a humanoid robot. In IEEE International Conference on Robotics and Automation (ICRA), May 2010.
12. L. Iocchi, F. D. Libera, and E. Menegatti. Learning humanoid soccer actions interleaving simulated and real data. In Second Workshop on Humanoid Soccer Robots, November 2007.
13. S. Kajita, F. Kanehiro, K. Kaneko, K. Fujiwara, K. Harada, K. Yokoi, and H. Hirukawa. Biped walking pattern generation by using preview control of zero-moment point. In ICRA'03, pages 1620-1626, 2003.
14. M. Kim and W. Uther. Automatic gait optimisation for quadruped robots. Australasian Conference on Robotics and Automation, pages 1-3, 2003.
15. N. Kohl and P. Stone. Machine learning for fast quadrupedal locomotion. In The Nineteenth National Conference on Artificial Intelligence, pages 611-616, July 2004.
16. S. Koos, J.-B. Mouret, and S. Doncieux. Crossing the reality gap in evolutionary robotics by promoting transferable controllers. In Proceedings of the 12th annual conference on Genetic and evolutionary computation, GECCO'10, pages 119-126, New York, NY, USA, 2010. ACM.
17. P. MacAlpine, S. Barrett, D. Urieli, V. Vu, and P. Stone. Design and optimization of an omnidirectional humanoid walk: A winning approach at the RoboCup 2011 3D simulation competition. In Twenty-Sixth Conference on Artificial Intelligence (AAAI-12), July 2012.
18. Ç. Meriçli and M. Veloso. Biped walk learning through playback and corrective demonstration. In AAAI 2010: Twenty-Fourth Conference on Artificial Intelligence, 2010.
19. Ç. Meriçli and M. Veloso. Improving biped walk stability using real-time corrective human feedback. In RoboCup Symposium 2010: Robot Soccer World Cup XIV, 2010.
20. A. Y. Ng, H. J. Kim, M. I. Jordan, and S. Sastry. Autonomous helicopter flight via reinforcement learning. In Advances in Neural Information Processing Systems 17. MIT Press, 2004.
21. J. M. Porta and E. Celaya. Reinforcement learning for agents with many sensors and actuators acting in categorizable environments. Journal of Artificial Intelligence Research, 23: 79-122.
22. R. J. Quinlan. Learning with continuous classes. In 5th Australian Joint Conference on Artificial Intelligence, pages 343-348, Singapore, 1992. World Scientific.
23. S. Ramamoorthy and B. Kuipers. Trajectory generation for dynamic bipedal walking through qualitative model based manifold learning. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-08), 2008.
24. M. Saggar, T. D'Silva, N. Kohl, and P. Stone. Autonomous learning of stable quadruped locomotion. In G. Lakemeyer, E. Sklar, D. Sorenti, and T. Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Volume 4434 of Lecture Notes in Artificial Intelligence, pages 98-109. Springer Verlag, Berlin, 2007.
25. S. Schaal. Learning from demonstration. In Advances in Neural Information Processing Systems 9. MIT Press, 1997.
26. A. Setapen. Exploiting human motor skills for training bipedal robots. HR 09-02, The University of Texas at Austin, May 2009. ftp://ftp.cs.utexas.edu/ pub/techreports/hr09-02.pdf.
27. J. H. Strom, G. Slavov, and E. Chown. Omnidirectional walking using zmp and preview control for the nao humanoid robot. In J. Baltes, M. G. Lagoudakis, T. Naruse, and S. S. Ghidary, editors, RoboCup, Volume 5949 of Lecture Notes in Computer Science, pages 378-389. Springer, 2009.
28. D. Thain, T. Tannenbaum, and M. Livny. Distributed computing in practice: the Condor experience. Concurrency - Practice and Experience, 17(2-4): 323-356, 2005.
29. S. H. Thomke. Simulation, learning and R&D performance: Evidence from automotive development. Research Policy, 27(1): 55-74, May 1998.
30. R. Tilgner, T. Reinhardt, D. Borkmann, T. Kalbitz, S. Seering, R. Fritzsche, C. Vitz, S. Unger, S. Eckermann, H. Müller, M. Bellersen, M. Engel, and M. Wünsch. Team research report 2011. Technical report, Leipzig University of Applied Sciences.
31. D. Urieli, P. MacAlpine, S. Kalyanakrishnan, Y. Bentor, and P. Stone. On optimizing interdependent skills: A case study in simulated 3D humanoid robot soccer. In K. Turner, P. Yolum, L. Sonenberg, and P. Stone, editors, Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2011), Volume 2, pages 769-776. IFAAMAS, May 2011.
32. E. R. Westervelt, J. Grizzle, and D. E. Koditschek. Hybrid zero dynamics of planar biped walkers. IEEE Transactions on Automatic Control, 48: 42-56, 2001.
33. S. X. Yang and M. Meng. Real-time collision-free path planning of robot manipulators using neural network approaches. Auton. Robots, 9(1): 27-39, Aug. 2000.
34. J. C. Zagal, J. Delpiano, and J. Ruizdel Solar. Self-modeling in humanoid soccer robots. Robot. Auton. Syst., 57(8): 819-827, July 2009.