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Learning the inverse map for a robot hitting task

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We describe our approach to the robot's Hanetsuki task (Japanese badminton), i.e. to return the incoming ball to the human opponent with a racket. A learning algorithm that consists of updating action commands and smoothing them based on a Gaussian kernel is proposed to compensate for the insufficiency in a non-adaptive model-based approach. Experimental results obtained by using the developed Hanetsuki robot are also shown.
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Document Type: Research Article

Affiliations: Department of Mechanical Engineering, Faculty of Engineering Science, Osaka University, Toyonaka, Osaka 560, Japan

Publication date: 1995-01-01

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