Human-robot cooperative manipulation with motion estimation

Abstract

A control method of robots for human-robot cooperative manipulation is investigated. We propose estimating human motion using the minimum jerk model for smooth cooperation. Using a nonlinear least-squares method, we identify two parameters of the minimum jerk model in real-time. The estimated position of the human hand is used to determine the desired position of the end-effector of the manipulator in virtual compliance control. The effectiveness of the proposed method is verified by experimentation with an industrial 6-degree-of-freedom manipulator. Energy transfer in cooperative manipulation is studied for quantitative evaluation of achieved cooperation from the viewpoint of adaptation theory.