Smooth human-robot interaction by interruptible gesture planning

Abstract

Generating natural body gestures is one of the essential functions in human-robot interaction. Thus various approaches, such as online-planning and the motion database method, have been developed. However, these approaches cannot adapt to user interruption, that 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 generate human-like motion, while the latter helps unexpected deviation of the reaction due to human interruption. We implemented the proposed method on the android robot Actroid-SIT as a human-robot interaction system and conducted evaluation experiments. We confirmed our proposed method can smooth human-robot interaction.