Transactions of the Japanese Society for Artificial Intelligence
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
Technical Papers
Acquisition of Motion Primitives of Robot in Human-Navigation Task
Towards Human-Robot Interaction based on ``Quasi-Symbols''
Tetsuya OgataShigeki SuganoJun Tani
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2005 Volume 20 Issue 3 Pages 188-196


A novel approach to human-robot collaboration based on quasi-symbolic expressions is proposed. The target task is navigation in which a person with his or her eyes covered and a humanoid robot collaborate in a context-dependent manner. The robot uses a recurrent neural net with parametric bias (RNNPB) model to acquire the behavioral primitives, which are sensory-motor units, composing the whole task. The robot expresses the PB dynamics as primitives using symbolic sounds, and the person influences these dynamics through tactile sensors attached to the robot. Experiments with six participants demonstrated that the level of influence the person has on the PB dynamics is strongly related to task performance, the person's subjective impressions, and the prediction error of the RNNPB model (task stability). Simulation experiments demonstrated that the subjective impressions of the correspondence between the utterance sounds (the PB values) and the motions were well reproduced by the rehearsal of the RNNPB model.

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© 2005 JSAI (The Japanese Society for Artificial Intelligence)
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