Task model of lower body motion for a biped humanoid robot to imitate human dances

Abstract

The goal of this study is developing a biped humanoid robot that can observe a human dance performance and imitate it. To achieve this goal, we propose a task model of lower body motion, which consists of task primitives (what to do) and skill parameters (how to do it). Based on this model, a sequence of task primitives and their skill parameters are detected from human motion, and robot motion is regenerated from the detected result under constraints of a robot. This model can generate human-like lower body motion including various waist motions as well as various stepping motions of the legs. Generated motions can be performed stably on an actual robot supported by its own legs. We used improved robot hardware HRP-2, which has superior features in body weight, actuators, and DOF of the waist. By using the proposed method and HRP-2, we have realized a dance performance of Japanese folk dance by the robot, which is synchronized with a performance of a human grand master on the same stage.