Identifying contact formations from sensory patterns and its applicability to robot programming by demonstration

Abstract

This paper presents a pattern recognition approach to identifying contact formations from force sensor signals. The approach is sensor-based and does not use geometric models of the workpieces. The design of a fuzzy classifier is described, when membership functions are generated automatically from training data. The technique is demonstrated using supervised learning. Test results are included for experiments using both rigid and non-rigid workpieces. The technique is discussed in the context of robot programming by human demonstration.