This paper develops a general policy for learning relevant features of an imitation task. We restrict our study to imitation of manipulative tasks or of gestures. The imitation process is modeled as a hierarchical optimization system, which minimizes the discrepancy between two multi-dimensional datasets. To classify across manipulation strategies, we apply a probabilistic analysis to data in Cartesian and joint spaces. We determine a general metric that optimizes the policy of task reproduction, following strategy determination. The model successfully discovers strategies in six different imitative tasks and controls task reproduction by a full body humanoid robot.
| Author(s): | Billard, A. and Epars, Y. and Calinon, S. and Cheng, G. and Schaal, S. |
| Book Title: | Robotics and Autonomous Systems |
| Volume: | 47 |
| Number (issue): | 2-3 |
| Pages: | 68-77 |
| Year: | 2004 |
| Bibtex Type: | Article (article) |
| Cross Ref: | p1959 |
| Electronic Archiving: | grant_archive |
| Note: | clmc |
BibTex
@article{Billard_RAS_2004,
title = {Discovering optimal imitation strategies},
booktitle = {Robotics and Autonomous Systems},
abstract = {This paper develops a general policy for learning relevant features of an imitation task. We restrict our study to imitation of manipulative tasks or of gestures. The imitation process is modeled as a hierarchical optimization system, which minimizes the discrepancy between two multi-dimensional datasets. To classify across manipulation strategies, we apply a probabilistic analysis to data in Cartesian and joint spaces. We determine a general metric that optimizes the policy of task reproduction, following strategy determination. The model successfully discovers strategies in six different imitative tasks and controls task reproduction by a full body humanoid robot.},
volume = {47},
number = {2-3},
pages = {68-77},
year = {2004},
note = {clmc},
slug = {billard_ras_2004},
author = {Billard, A. and Epars, Y. and Calinon, S. and Cheng, G. and Schaal, S.},
crossref = {p1959}
}