Adaptive Learning-Based Distributed Control of Cooperative Robot Arm Manipulation for Unknown Objects

This article proposes a distributed cooperative manipulation control scheme for multirobot systems to track reference trajectories with unknown payload dynamics, grasp positions, and external disturbances. An online learning module is established to estimate the payload dynamics. Then a wrench-synthetic trajectory tracking control protocol is thereby developed to manipulate an object under unknown external disturbances no matter where the grasping points are. Moreover, sufficient conditions are derived to guarantee the uniform boundedness of the tracking errors of the closed-loop cooperative manipulation system. Finally, numerical simulations are conducted to substantiate the effectiveness of the proposed cooperative manipulation control scheme.