USING JOINT TRAJECTORIES AND TIME-SCALING OPTIMIZATION FOR HUMANOID MOTION IMITATION OF HUMAN BEINGS

This paper presents a hybrid approach involving geometric and temporal evolution of joint motion for the imitation of human motion by a humanoid robot. We exploit the key advantages of modifying temporal evolution of joint motion like joint coordination and Cartesian trajectory tracking and combine it with geometric evolution of joint motion to ensure balance and obey the physical limits of the humanoid robot during motion imitation. In order to achieve this objective, we have framed a multi objective optimization problem with constraints on balance. A feasible set of joint motion was obtained, as close as possible to the human reference motion, to achieve a natural looking motion imitation with optimum time delay and joint angle error. This approach was tested with the NAO humanoid robot with a kick motion in a single-support phase.