データベースとオンラインプランニングを統合した高速応答可能なジェスチャ生成

抄録

Generating natural body gestures is one of the essential functions in human-robot interaction. Various approaches, such as motion database approach and on-line planning, have been developed. However, these approaches cannot adapt to user's interruption, which usually occurs. Therefore, we propose a novel method for generating motions flexibly and immediately. The proposed method integrates Motion Graph and Probabilistic Roadmap Method. The former helps generation of human-like motion, while the latter helps rapid reaction due to user-intended interruption. We conducted the experiments to verify that the proposed method can maintain naturalness of body gestures, which we define based on key-poses and velocity profiles of the original motion. In addition, we implemented the proposed method on the android robot Actroid-SIT as a human-robot interaction system. Through subject experiments, we confirmed that the proposed method can make human-robot interaction more smooth and durable.