A methodological approach relating the classification of gesture to identification of human intent in the context of human-robot interaction

Abstract

In order to infer intent from gesture, a broad classification of types of gestures into five main classes is introduced. The classification is intended as a generally applicable basis for incorporating the understanding of gesture into human-robot interaction (HRI). Examples from human-robot interaction show the need to take into account not only the kinematics of gesture, but also the interactional context. Requirements for the operational classification of gesture by a robot interacting with humans are suggested and initial steps in its deployment are discussed.