Action acquisition framework for humanoid robots based on kinematics and dynamics adaptation

Abstract

It is not simple for humanoid to acquire its actions automatically because: 1) it has very wide search space due to many DOF and is not fixed on the ground; 2) complex actions are difficult to describe using indirect evaluation functions; and 3) a humanoid is required to behave naturally like a human does. Kinematics adaptation generates an action outline which is a rough action description from teacher's action (motion capture data) by absorbing a difference of structures between the human and robot. Then a target action is acquired through dynamics adaptation by searching an action which is executable dynamically. Advantages of this framework are that: 1) the target action is described in an intuitive representation, 2) the search space is reduced in the neighborhood space, and 3) the acquired action will be a natural motion.