LEARNING THE INVERSE MAP FOR A ROBOT HITTING TASK

We describe our approach to the robot's Hanetsuki task (Japanese badmi nton), i.e. to return the incoming ball to the human opponent with a r acket. A learning algorithm that consists of updating action commands and smoothing them based on a Gaussian kernel is proposed to compensat e for the insufficiency in a non-adaptive model-based approach. Experi mental results obtained by using the developed Hanetsuki robot are als o shown.