Attractor design and prediction-based adaption for a robot waltz dancer in physical human-robot interaction

Abstract

Physical human-robot interaction between a human leader and a robot follower in waltz is studied in this paper. The dancers' body dynamics in single-support phase are modeled as inverted pendulums. On the robot side, an ankle torque control method is proposed and applied. The control law forms a time-dependent vector field, which makes the nominal orbit of the robot to be an attractor. To physically interact with human, the human leader's state is estimated from range image data by using an extended Kalman filter. Parameters of the robot's orbit are then adjusted according to the leader's estimated and predicted state. The proposed method is verified by simulation results.