Visual perception and reproduction for imitative learning of a partner robot

Authors:
Naoyuki Kubota
Affiliations:
Dept. of System Design, Tokyo Metropolitan University, Hachioji, Tokyo, Japan and SORST, Japan Science and Technology Agency
Venue:
SIP'06 Proceedings of the 5th WSEAS international conference on Signal processing
Year:
2006

Citing 6
Cited 0

Relevance: communication and cognition

Relevance: communication and cognition
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Abstract

This paper proposes visual perception and model reproduction based on imitation of a partner robot interacting with a human. First of all, we discuss the role of imitation, and propose the method for imitative behavior generation. After the robot searches for a human by using a CCD camera, human hand positions are extracted from a series of images taken from the CCD camera. Next, the position sequence of the extracted human hand is used as inputs to a fuzzy spiking neural network to recognize the position sequence as a motion pattern. The trajectory for the robot behavior is generated and updated by a steady-state genetic algorithm based on the human motions pattern. Furthermore, a self-organizing map is used for clustering human hand motion patterns. Finally, we show experimental results of imitative behavior generation through interaction with a human.