Safety and Performance of Industrial Collaborative Robots: Bounded Compensation in Precision Motion Control

The safety and control performance of industrial collaborative robots must be ensured while they are executing repetitive and precise tasks alongside human workers. This study proposes a new motion control structure to enhance the safety by demonstrating full-body compliance while achieving control performance as accurate as that of conventional industrial controllers. For precise motion, the proposed approach introduces a nominal model and compensates for disturbances caused by model uncertainty while bounding the compensation input for the safe interaction. Furthermore, to reduce the interaction forces without compromising the control performances, a method for designing the compensation bound based on the Gaussian Process (GP) is proposed. The proposed approach can achieve a uniformly ultimately boundedness (UUB) in the tracking scenario and asymptotic stability in the regulation scenario. The effectiveness of the proposed approach is validated under various conditions through experiments conducted using a 6-DOF industrial collaborative robot.