Three-Layer Model for Generation and Recognition of Attention-Drawing Behavior

Abstract

This paper presents a three-layer model for generation and recognition of attention-drawing behavior. The model enables a robot to recognize people's attention-drawing behavior as well as to perform attention-drawing behavior to people. It consists of three layers: the PSM (pointing space model), the RTM (reference term model), and the OPM (object property model). The PSM associates the pointing gesture with a reference term, the RTM associates positional relationships with a reference term, and the OPM associates other supplemental verbal cues with a reference term. We implemented the model in a humanoid robot, Robovie, and verified its effectiveness through an experiment