Force/Position Learning Control of Multiple Robot Manipulators

Abstract

Multiple robot manipulators are used in a coordinated way for carrying out tasks which cannot be performed by a single robot. When two or more robots handle a large object in free space, it is necessary to control the internal force applied on the object as well as the positions of the robot end effectors. In this paper, a learning control algorithm is proposed for the iterative-type position and force control of multiple manipulators carrying an object in free space. The learning control algorithm is of the D-type, and uses acceleration errors and internal force errors for learning. A proof of the convergence of the position and internal force trajectories to the desired trajectories is given. Simulation and experimental results are presented for two-robot manipulator systems to illustrate the effectiveness of the proposed learning controller.