Learning to predict humanoid fall

International Journal of Humanoid Robotics

Volumn 8, Issue 2, 2011, Pages 245-273

  Kalyanakrishnan, Shivaram ^a   Goswami, Ambarish ^b  

^a University of Texas at Austin   (United States)

^b HONDA RESEARCH INSTITUTE   (United States)

Author keywords

fall prediction; Humanoid robots; machine learning; supervised learning

Indexed keywords

ANALYTICAL TECHNIQUES; COMPLEX DYNAMICS; CONTROL MODES; DECISION LISTS; FALSE ALARMS; FALSE POSITIVE RATES; FEATURE SPACE; HUMAN ENVIRONMENT; HUMANOID ROBOT; HUMANOID ROBOTS; LEADTIME; MACHINE-LEARNING; SUPERVISED LEARNING METHODS;

ANTHROPOMORPHIC ROBOTS; SUPERVISED LEARNING;

FORECASTING;

EID: 82155164626     PISSN: 02198436     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219843611002496     Document Type: Article

References (43)

1. S. Kagami, F. Kanehiro, Y. Tamiya, M. Inaba and H. Inoue, Autobalancer: An online dynamic balance compensation scheme for humanoid robots, in B. R. Donald, K. M. Lynch and D. Rus (Eds.), Algorithmic and Computational Robotics: New Directions: The Fourth Workshop on the Algorithmic Foundations of Robotics (AK Peters, Ltd., 2001), pp. 329-339.
2. A. Nishio, K. Takahashi and D. N. Nenchev, Balance control of a humanoid robot based on the reaction null space method, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2006) (IEEE, 2006), pp. 1996-2001. (Pubitemid 46928188)
3. Napoleon, S. Nakaura and M. Sampei, Balance control analysis of humanoid robot based on ZMP feedback control, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2002) (IEEE, 2002), Vol. 3, pp. 2437-2442. (Pubitemid 35438174)
4. K. Ogata, K. Terada and Y. Kuniyoshi, Real-time selection and generation of fall damage reduction actions for humanoid robots, in Proceedings of the 8th IEEERAS International Conference on Humanoid Robots (Humanoids 2007) (IEEE, 2008), pp. 233-238.
5. Q. Huang and Y. Nakamura, Sensory reflex control for humanoid walking, IEEE Transactions on Robotics 21(5) (2005) 977-984. (Pubitemid 41489347)
6. S. Kudoh, T. Komura and K. Ikeuchi, Stepping motion for a human-like character to maintain balance against large perturbations, in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2006) (IEEE, 2006), pp. 2661-2666. (Pubitemid 44940466)
7. J. Pratt, J. Carff, S. Drakunov and A. Goswami, Capture point: A step toward humanoid push recovery, in Proceedings of the Sixth IEEE-RAS International Conference on Humanoid Robots (Humanoids 2006) (IEEE, 2006), pp. 200-207.
8. R. Zaier and S. Kanda, Piecewise-linear pattern generator and reflex system for humanoid robots, in Proceedings of the 2007 IEEE International Conference on Robotics and Automation (ICRA 2007) (IEEE, 2007), pp. 2188-2195. (Pubitemid 350140503)
9. T.Wilken, M. Missura and S. Behnke, Designing falling motions for a humanoid soccer goalie, in The 4th Workshop on Humanoid Soccer Robots at the 9th International Conference on Humanoid Robots (Humanoids 2009) (2009).
10. K. Fujiwara, F. Kanehiro, S. Kajita, K. Kaneko, K. Yokoi and H. Hirukawa, UKEMI: Falling motion control to minimize damage to biped humanoid robot, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2002) (IEEE, 2002), Vol. 3, pp. 2521-2526. (Pubitemid 35438188)
11. K. Fujiwara, S. Kajita, K. Harada, K. Kaneko, M. Morisawa, F. Kanehiro, S. Nakaoka and H. Hirukawa, Towards an optimal falling motion for a humanoid robot, in Proceedings of the 6th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2006) (IEEE, 2006), pp. 524-529.
12. K. Fujiwara, S. Kajita, K. Harada, K. Kaneko, M. Morisawa, F. Kanehiro, S. Nakaoka and H. Hirukawa, An optimal planning of falling motions of a humanoid robot, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2007) (IEEE, 2007), pp. 456-462.
13. J. Ruiz-del-Solar, R. Palma-Amestoy, R. Marchant, I. Parra-Tsunekawa and P. Zegers, Learning to fall: Designing low damage fall sequences for humanoid soccer robots, Robotics and Autonomous Systems 57(8) (2009) 796-807.
14. S.-K. Yun, A. Goswami and Y. Sakagami, Safe fall: Humanoid robot fall direction change through intelligent stepping and inertia shaping, in Proceedings of the 2009 IEEE International Conference on Robotics and Automation (ICRA 2009) (IEEE, 2009), pp. 781-787.
15. U. Nagarajan and A. Goswami, Generalized direction changing fall control of humanoid robots among multiple objects, in Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA 2010) (IEEE, May 2010), To appear.
16. Y. Sakagami, R. Watanabe, C. Aoyama, S. Matsunaga, N. Higaki and K. Fujimura, The intelligent ASIMO: System overview and integration, in Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2002) (IEEE, 2002), Vol. 3, pp. 2478-2483. (Pubitemid 35438181)
17. P.-B. Wieber, On the stability of walking systems, in The Third IARP International Workshop on Humanoid and Human Friendly Robotics (2002).
18. J.-P. Aubin, Viability Theory (Birkhäuser, Boston, 1991).
19. P.-B.Wieber, Viability and predictive control for safe locomotion, in Proceedings of the 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems (IEEE, 2008), pp. 1103-1108.
20. R. Renner and S. Behnke, Instability detection and fall avoidance for a humanoid using attitude sensors and reflexes, in Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2006) (IEEE, 2006), pp. 2967-2973. (Pubitemid 46928354)
21. J. G. Daniël Karssen and M. Wisse, Fall detection of two-legged walking robots using multi-way principal components analysis, International Journal of Humanoid Robots 7(1) (2010) 73-93.
22. O. Höhn and W. Gerth, Probabilistic balance monitoring for bipedal robots, International Journal of Robotics Research 28(2) (2009) 245-256.
23. K. Ogata, K. Terada and Y. Kuniyoshi, Falling motion control for humanoid robots while walking, in Proceedings of the 7th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2007) (IEEE, 2007), pp. 306-311.
24. P. Langley and H. A. Simon, Applications of machine learning and rule induction, Communications of the ACM 38(11) (1995) 54-64.
25. M. Chen, A. X. Zheng, J. Lloyd, M. I. Jordan and E. Brewer, Failure diagnosis using decision trees, in Proceedings of the 1st International Conference on Autonomic Computing (ICAC 2004) (IEEE, 2004), pp. 36-43.
26. D. L. Olson and D. Delen, Advanced Data Mining Techniques (Springer-Verlag, 2008).
27. T. Degen, H. Jaeckel, M. Rufer and S. Wyss, SPEEDY: A fall detector in a wrist watch, in Proceedings of the 7th IEEE International Symposium on Wearable Computers (ISWC 2003) (IEEE, 2003), pp. 184-187.
28. A. K. Bourke, K. J. O'Donovan and G. M. O'Laighin, Distinguishing falls from normal ADL using vertical velocity profiles, in Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007) (IEEE, 2007), pp. 3176-3179.
29. N. Noury, A. Fleury, P. Rumeau, A. K. Bourke, G. O'Laighin, V. Rialle and J. E. Lundy, Fall detection - principles and methods, in Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007) (IEEE, 2007), pp. 1663-1666.
30. J. J. Gertler, Survey of model-based failure detection and isolation in complex plants, IEEE Control Systems Magazine 8(6) (1988) 3-11.
31. R. Mattone and A. De Luca, Relaxed fault detection and isolation: An application to a nonlinear case study, Automatica 42(1) (2006) 109-116. (Pubitemid 41660567)
32. C. C. Zou, L. Gao,W. Gong and D. Towsley, Monitoring and early warning for internet worms, in Proceedings of the 10th ACM Conference on Computer and Communications Security (CCS 2003) (ACM, 2003), pp. 190-199. (Pubitemid 40673801)
33. R. Parasuraman, P. A. Hancock and O. Olofinboba, Alarm effectiveness in drivercentred collision-warning systems, Ergonomics 40(3) (1997) 390-399. (Pubitemid 27182299)
34. N. Kohl, K. Stanley, R. Miikkulainen, M. Samples and R. Sherony, Evolving a realworld vehicle warning system, in M. Cattolico (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2006) (ACM, 2006), pp. 1681-1688.
35. J. Talandier and E. A. Okal, An algorithm for automated tsunami warning in French Polynesia based on mantle magnitudes, Bulletin of the Seismological Society of America 79(4) (1989) 1177-1193.
36. W. L. Tung, C. Quek and P. Cheng, GenSo-EWS: A novel neural-fuzzy based early warning system for predicting bank failures, Neural Networks 17(4) (2004) 567-587. (Pubitemid 38510340)
37. O. Michel, WebotsTM: Professional mobile robot simulation, Journal of Advanced Robotics Systems 1(1) (2004) 39-42.
38. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann and I. H. Witten, The WEKA data mining software: An update, SIGKDD Explorations 11(1) (2009) 10-18.
39. N. Kohl and P. Stone, Machine learning for fast quadrupedal locomotion, in D. L. McGuinness and G. Ferguson (Eds.), The Nineteenth National Conference on Artificial Intelligence (AAAI Press, 2004), pp. 611-616.
40. C. Plagemann, D. Fox and W. Burgard, Efficient failure detection on mobile robots using particle filters with Gaussian process proposals, in M. M. Veloso (Ed.), Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007) (IJCAI, 2007), pp. 2185-2190.
41. D. Katić and M. Vukobratović, Survey of intelligent control techniques for humanoid robots, Journal of Intelligent Robotic Systems 37(2) (2003) 117-141.
42. K. Hitomi, T. Shibata, Y. Nakamura and S. Ishii, Reinforcement learning for quasipassive dynamic walking of an unstable biped robot, Robotics and Autonomous Systems 54(12) (2006) 982-988. (Pubitemid 46053753)
43. J. Peters and S. Schaal, Reinforcement learning of motor skills with policy gradients, Neural Networks 21(4) (2008) 682-697.