Goal-Directed Imitation in a Humanoid Robot

Our work aims at developing a robust discriminant controller for robot programming by demonstration. It addresses two core issues of imitation learning, namely "what to imitate" and "how to imitate". This paper presents a method by which a robot extracts the goals of a demonstrated task and determines the imitation strategy that satisfies best these goals. The method is validated in a humanoid platform, taking inspiration of an influential experiment from developmental psychology.


Published in:
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 299--304
Presented at:
International Conference on Robotics and Automation, Barcelona, Spain, April 2005
Year:
2005
Keywords:
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 Record created 2005-11-16, last modified 2018-03-17

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