PERFORMANCE-DERIVED BEHAVIOR VOCABULARIES: DATA-DRIVEN ACQUISITION OF SKILLS FROM MOTION

International Journal of Humanoid Robotics

Volumn 1, Issue 2, 2004, Pages 237-288

  JENKINS, ODEST CHADWICKE ^a   MATARIĆ, MAJA J ^a  

^a University of Southern California ^*  (United States)

Author keywords

humanoid robotics; motion clustering; Motion primitives; motion segmentation; spatio temporal dimension reduction

Indexed keywords

DEGREES OF FREEDOM (MECHANICS); HUMAN ROBOT INTERACTION; KINEMATICS; MOTION ANALYSIS; REDUCTION;

CLUSTERINGS; DIMENSION REDUCTION; HUMANOID ROBOT; HUMANOID ROBOTICS; MOTION CLUSTERING; MOTION PRIMITIVES; MOTION SEGMENTATION; SKILL LEVELS; SPATIO-TEMPORAL DIMENSION REDUCTION; SPATIO-TEMPORAL DIMENSIONS;

ANTHROPOMORPHIC ROBOTS;

EID: 17144391260     PISSN: 02198436     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219843604000186     Document Type: Article

References (56)

1. M. Huber and R. A. Grupen, A hybrid architecture for learning robot control tasks, Robotics Today, Robotics International/Society of Manufacturing Engineers 13(4), (2000).
2. R. A. Brooks, Intelligence without representation, Artif. Intell. J. 47, 139-159 (1991).
3. M. J. Mataríc, Behavior-based control: Examples from navigation, learning, and group behavior, J. Exp. Theoret. Artif. Intell. 9(2-3), 323-336 (1997).
4. O. C. Jenkins and M. J. Mataríc, A spatio-temporal extension to isomap nonlinear dimension reduction, in Procs. Int. Conf. Machine Learning (ICML 2004), Banff, Alberta, Canada, 2004.
5. C. Rose, M. F. Cohen and B. Bodenheimer, Verbs and adverbs: Multidimensional motion interpolation, IEEE Computer Graphics and Applications 18(5), 32-40 (1998).
6. A. Moore, C. G. Atkeson and S. A. Schaal, Memory-based learning for control, Technical Report CMU-RI-TR-95-18, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, April 1995.
7. M. J. Mataríc, Sensory-motor primitives as a basis for imitation: Linking perception to action and biology to robotics, in Imitation in Animals and Artifacts, eds. C. Nehaniv and K. Dautenhahn (MIT Press, 2002), pp. 392-422.
8. M. N. Nicolescu and M. J. Mataríc, Natural methods for robot task learning: Instructive demonstration, generalization and practice, in Autonomous Agents and Multi-Agent Systems (AAMAS 2003), Melbourne, Australia, July 2003, pp. 241-248.
9. D. C. Bentivegna and C. G. Atkeson, Learning from observation using primitives, in IEEE Int. Conf. Robotics and Automation, Seoul, Korea, May 2001, pp. 1988-1993.
10. A. D'Souza, S. Vijayakumar and S. Schaal, Learning inverse kinematics, in IEEE Intelligent Robots and Systems (IROS 2001), Maui, HI, USA, 2001, pp. 298-303.
11. M. I. Jordan, Computational aspects of motor control and motor learning, in Handbook of Perception and Action: Motor Skills, eds. H. Heuer and S. Keele (Academic Press, New York, 1996).
12. J. J. Craig, Introduction to Robotics: Mechanics and Control (Addison-Wesley, Reading, MA, USA, 1989).
13. L. E. Kavraki, P. Svestka, J.-C. Latombe and M. Overmars, Probabilistic roadmaps for path planning in high dimensional configuration spaces, in IEEE Trans. Robotics and Automation 12(4), 566-580 (1996).
14. L. Kovar, M. Gleicher and F. Pighin, Motion graphs, ACM Trans. Graphics 21(3), 473-482 (2002).
15. O. C. Jenkins and M. J. Mataríc, Automated derivation of behavior vocabularies for autonomous humanoid motion, in Autonomous Agents and Multiagent Systems (AAMAS 2003), Melbourne, Australia, July 2003, pp. 225-232.
16. Y. Li, T. Wang, and H.-Y. Shum, Motion texture: A two-level statistical model for character motion synthesis, ACM Trans. Graphics 21(3), 465-472 (2002).
17. J. Ijspeert, J. Nakanishi and S. Schaal, Learning rhythmic movements by demonstration using nonlinear oscillators, in IEEE Intelligent Robots and Systems (IROS 2002), Lausanne, Switzerland, October 2002, pp. 958-963.
18. M. Turk and A. Pentland, Eigenfaces for recognition, J. Cogn. Neurosci. 3(1), 71-86 (1991).
19. A. Fod, M. Mataríc and O. Jenkins, Automated derivation of primitives for movement classification, Autonomous Robots 12(1), 39-54 (2002).
20. H. Sidenbladh, M. J. Black and L. Sigal, Implicit probabilistic models of human motion for synthesis and tracking, in Eur. Conf. Computer Vision, Vol. 1, Copenhagen, Denmark, 2002, pp. 784-800.
21. M. G. Choi, J. Lee and S. Y. Shin, Planning biped locomotion using motion capture data and probabilistic roadmaps, ACM Trans. Graphics 22(2), 182-203 (2003).
22. L. G. Y. Song and P. Perona, Unsupervised learning of human motion, in IEEE Trans. Pattern Analysis and Machine Intelligence 25(7), 814-827 (2003).
23. J. Rittscher and A. Blake, Classification of human body motion, in IEEE Int. Conf. Computer Vision, Kerkyra, Corfu, Greece, September 1999, pp. 634-639.
24. C. Bregler, Learning and recognizing human dynamics in video sequences, in IEEE Computer Vision and Pattern Recoginition, San Juan, Puerto Rico, 1997, pp. 568-574.
25. M. Williamson, Postural primitives: Interactive behavior for a humanoid robot arm, in Int. Conf. Simulation of Adaptive Behavior, Cape Cod, MA, USA (MIT Press, 1996), pp. 124-131.
26. J. Ijspeert, J. Nakanishi and S. Schaal, Movement imitation with nonlinear dynamical systems in humanoid robots, in IEEE Int. Conf. Robotics and Automation (ICRA 2002), Washington, DC, USA, May 2002, pp. 1398-1403.
27. M. Williamson, Robot Arm Control Exploiting Natural Dynamics, Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, MA, 1999.
28. S. Schaal and D. Sternad, Programmable pattern generators, in Int. Conf. Computational Intelligence in Neuroscience, Research Triangle Park, NC, USA, October 1998, pp. 48-51.
29. D. Chi, M. Costa, L. Zhao and N. Badler, The emote model for effort and shape, in Conference on Computer Graphics and Interactive Techniques (ACM Press/ Addison-Wesley Publishing Co., 2000), pp. 173-182.
30. R. A. Grupen, M. Huber, J. A. C. Jr. and K. Souccar, A basis for distributed control of manipulation tasks, IEEE Expert 10(2), 9-14 (1995).
31. M. J. Mataríc, V. B. Zordan and M. Williamson, Making complex articulated agents dance: An analysis of control methods drawn from robotics, animation, and biology, Autonomous Agents and Multi-Agent Systems 2(1), 23-44 (1999).
32. O. C. Jenkins, M. Mataríc and S. Weber, Primitive-based movement classification for humanoid imitation, in IEEE Int. Conf. Humanoid Robots (Humanoids 2000), Cambridge, MA, USA, October 2000.
33. O. Arikan, D. A. Forsyth and J. F. O'Brien, Motion synthesis from annotations, ACM Trans. Graphics 22(3), 402-408 (2002).
34. A. Billard and M. J. Mataríc, Learning human arm movements by imitation: Evaluation of a biologically inspired connectionist architecture, Robotics and Autonomous Systems 37(2), 145-160 (2001).
35. L. Molina-Tanco and A. Hilton, Realistic synthesis of novel movements from a database of motion capture data, in IEEE Workshop on Human Motion (HUMO 00), Austin, Texas, USA, December 2000, pp. 137-142.
36. R. Bowden, Learning statistical models of human motion. in IEEE Workshop on Human Modelling, Analysis and Synthesis, Hilton Head Island, SC, USA, 2000.
37. M. Brand and A. Hertzmann, Style machines, in Proceedings of ACM SIGGRAPH 2000, Computer Graphics Proc., Annual Conf. Series (ACM Press, July 2000), pp. 183-192.
38. M. Okada and Y. Nakamura, Design of the continuous symbol space for the intelligent robots using the dynamics-based information processing, in IEEE Int. Conf. Robotics and Automation (ICRA 2004), 2004, pp. 3201-3206.
39. W. Iba, Learning to classify observed motor behavior, in Int. Joint Conf. Artificial Intelligence (IJCAI 1991), Sydney, New South Wales, Australia, 1991, pp. 732-738.
40. Y. Demiris and G. Hayes, Imitation as a dual-route process featuring predictive and learning components: A biologically-plausible computational model, in Imitation in Animals and Artifacts, eds. K. Dautenhahn and C. Nehaniv (MIT Press, 2002), Chap. 13, pp. 327-361.
41. D. M. Wolpert and M. Kawato, Multiple paired forward and inverse models for motor control, Neural Networks 11(7-8), 1317-1329 (1998).
42. W. Ilg, G. H. Bakir, J. Mezger and M. A. Giese, On the representation, learning and transfer of spatio-temporal movement characteristics, in IEEE Int. Conf. Humanoid Robotics (Humanoids 2003), Karlsruhe, Germany, October 2003.
43. L. Kovar and M. Gleicher, Automated extraction and parameterization of motions in large data sets, to appear in ACM Trans. Graphics 23(3), (2004).
44. L. R. Rabiner, A tutorial on hidden markov models and selected applications in speech recognition, Proc. IEEE 77(2), 257-285 (1989).
45. J. Cutting, D. Proffitt and L. Kozlowski, A biomechanical invariant for gait perception, J. Experiemental Psych. Human Perception and Performance 4(3), 357-372 (1978).
46. J. B. Tenenbaum, V. de Silva and J. C. Langford, A global geometric framework for nonlinear dimensionality reduction, Science 290(5500), 2319-2323 (2000).
47. A. Jain and R. Dubes, Algorithms for Clustering Data (Prentice Hall, Englewood Cliffs, 1988).
48. J. D. Cohen, M. C. Lin, D. Manocha and M. K. Ponamgi, I-COLLIDE: An interactive and exact collision detection system for large-scale environments, in Symp. Interactive 3D Graphics, Monterey, California, USA, 1995, pp. 189-196, 218.
49. D. Shepard, A two-dimensional interpolation function for irregularly-spaced data, in Proc. ACM National Conf. (ACM Press, 1968), pp. 517-524.
50. D. Erol, J. Park, E. Turkay, K. Kawamura, O. Jenkins and M. Mataríc, Motion generation for humanoid robots with automatically derived behaviors, in IEEESystems, Man, and Cybernetics (SMC 2003), Washington, DC, USA, 2003, pp. 1816-1822.
51. D. Baraff and A. Witkin, Physically-based modeling, principles and practice, Technical Report Course 34, SIGGRAPH 1997 Course Notes, ACM, August 1997.
52. D. Sternad and S. Schaal, Segmentation of endpoint trajectories does not imply segmented control, Experimental Brain Research 124(1), 118-136 (1999).
53. R. O. Ambrose, H. Aldridge, R. S. Askew, R. R. Burridge, W. Bluethmann, M. Diftler, C. Lovchik, D. Magruder and F. Rehnmark, Robonaut: Nasa's space humanoid, IEEE Intelligent Systems 15(4), 57-63 (2000).
54. N. Pollard, J. K. Hodgins, M. Riley and C. G. Atkeson, Adapting human motion for the control of a humanoid robot, in IEEE Int. Conf. Robotics and Automation (ICRA 2002), May 2002, pp. 1390-1397.
55. M. J. Mataríc, V. B. Zordan and Z. Mason, Movement control methods for complex, dynamically simulated agents: Adonis dances the macarena, in Autonomous Agents, Minneapolis, MN, USA (ACM Press, 1998), pp. 317-324.
56. R. Peters, C. Campbell, W. Bluethmann and E. Huber, Robonaut task learning through teleoperation, in IEEE Int. Conf. Robotics and Automation (ICRA 2003), 2003, pp. 2806-2811.