Learning the inverse map for a robot hitting task
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.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
Document Type: Research Article
Affiliations: Department of Mechanical Engineering, Faculty of Engineering Science, Osaka University, Toyonaka, Osaka 560, Japan
Publication date: 1995-01-01