Incremental on-line hierarchical clustering of whole body motion patterns

Proceedings - IEEE International Workshop on Robot and Human Interactive Communication

Volumn , Issue , 2007, Pages 1016-1021

  Kulić, Dana ^a   Takano, Wataru ^a   Nakamura, Yoshihiko ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ARSENIC COMPOUNDS; BOOLEAN FUNCTIONS; CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; FLOW OF SOLIDS; HIDDEN MARKOV MODELS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MAMMALS; MARKOV PROCESSES; METROPOLITAN AREA NETWORKS; REVERSE OSMOSIS; ROBOTICS;

HIER ARCHICAL CLUSTERING; HIERARCHICAL AGGLOMERATIVE CLUSTERING; HUMAN MOTIONS; INCREMENTAL LEARNING; INTERACTIVE COMMUNICATIONS; INTERNATIONAL CONFERENCES; MARKOV MODELLING; MOTION CAPTURE DATA; MOTION PATTERNS; MOTION PRIMITIVES; MOTION RECOGNITION; NOVEL ALGORITHMS; OBSERVATION OF HUMAN MOTION; RELATIVE DISTANCES; TRAINING DATA; TREE LEAVES; TREE STRUCTURES; WHOLE-BODY MOTION;

TREES (MATHEMATICS);

EID: 48749097061     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROMAN.2007.4415231     Document Type: Conference Paper

References (15)

1. D. C. Bentivegna, C. G. Atkeson, and G. Cheng. Learning similar tasks from observation and practice. In International Conference on Intelligent Robots and Systems, pages 2677-2683, 2006.
2. A. Billard, S. Calinon, and F. Guenter. Discriminative and adaptive imitation in uni-manual and bi-manual tasks. Robotics and Autonomous Systems, 54:370-384, 2006.
3. C. Breazeal and B. Scassellati. Robots that imitate humans. Trends in Cognitive Sciences, 6(11):481-487, 2002.
4. K. P. Burnham and D. R. Anderson. Multimodel inference: Understanding aic and bic in model selection. Sociological Methods and Research, 33(2):261-304, 2004.
5. T. Inamura, I. Toshima, H. Tanie, and Y. Nakamura. Embodied symbol emergence based on mimesis theory. The International Journal of Robotics Research, 23(4-5):363-377, 2004.
6. A. K. Jain, M. N. Murty, and P. J. Flynn. Data clustering: A review. ACM Computing Surveys, 31(3):264-323, 1999.
7. H. Kadone and Y. Nakamura. Symbolic memory for humanoid robots using hierarchical bifurcations of attractors in nonmonotonic neural networks. In International Conference on Intelligent Robots and Systems, pages 2900-2905, 2005.
8. H. Kadone and Y. Nakamura. Segmentation, memorization, recognition and abstraction of humanoid motions based on correlations and associative memory. In IEEE-RAS International Conference on Humanoid Robots, pages 1-6, 2006.
9. M. N. Nicolescu and M. J. Mataric. Task learning through imitation and human-robot interaction. In K. Dautenhahn and C. Nehaniv, editors, Imitation and social learning in robots, humans and animals: behavioral, social and communicative dimensions. Cambridge University Press, 2005.
10. T. Ogata, S. Sugano, and J. Tani. Open-end human-robot interaction from the dynamical systems perspective: mutual adaptation and incremental learning. Advanced Robotics, 19:651-670, 2005.
11. L. R. Rabiner. A tutorial on hidden markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2):257-286, 1989.
12. G. Rizzolatti, L. Fogassi, and V. Gallese. Neurophysical mechanisms underlying the understanding and imitation of action. Nature Reviews: Neuroscience, 2:661-670, 2001.
13. S. Schaal, A. Ijspeert, and A. Billard. Computational approaches to motor learning by imitation. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 358:537-547, 2003.
14. W. Takano. Stochastic segmentation, proto-symbol coding and clustering of motion patterns and their application to signifiant communication between man and humanoid robot. PhD thesis, University of Tokyo, 2006.
15. W. Takano and Y. Nakamura. Humanoid robot's autonomous acquisition of proto-symbols through motion segmentation. In IEEE-RAS International Conference on Humanoid Robots, pages 425-431, 2006.