Fast and Intuitive Kinematics Mapping for Human-Robot Motion Imitating: A Virtual-Joint-Based Approach

Abstract

It is quite difficult to imitate the motion of human arms using non-humanoid robots due to their dissimilar embodiments (degree-of-freedom, body morphology, and constraints). However, in most cases of the robotic imitation, the human operator and the robot would not share the same kinematic configuration. This paper addresses the motion imitation problem between the human arm and an industrial robot, where a commonly-used UR5 robot is considered. The motion of the human arm is obtained by an inertial motion capture system, and then the captured motion is reproduced using the UR5 embodiment. A virtual-joint-based approach is proposed to facilitate the fast and intuitive kinematics mapping between the human arm and the UR5 robot, leading to a robotic imitation system that can imitate the tip location and configuration of the human arm simultaneously. The proposed approach is verified experimentally on a real UR5 robot and compared with classic Cartesian-space-based mapping approach and joint-space-based approach.