A Study on Human Motor Learning through Force-Feedback Behavior Instruction Using High-speed Visual Sensing

Abstract

We have proposed a human-machine system in which a teleoperation robot realizes movements that transcend the athletic ability of the operator, based on a visual prediction that predicts the future a little ahead. In this paper, we investigate whether the system affects human motor learning through subject experiments. The results of the subject experiments suggest that motor learning can be enhanced by presenting motor sensations that greatly exceed the learning capacity of humans.