Self-emerging Action Gestalts for Task Segmentation

摘要

Task segmentation from user demonstrations is an often neglected component of robot programming by demonstration (PbD) systems. This paper presents an approach to the segmentation problem motivated by psychological findings of gestalt theory. It assumes the existence of certain "action gestalts" that correspond to basic actions a human performs. Unlike other approaches, the set of elementary actions is not prespecified, but is learned in a self-organized way by the system.