Velocity-Free Neuro-Adaptive Cooperative Control for Dual-Arm Robots With Dynamically Adjustable Performance Constraints

This paper investigates tracking control for the cooperative manipulation of dual-arm robots without velocity measurement, where prescribed performance specifications are imposed on the motion of the grasped object. An integrated dynamic model within the task space is formulated by establishing the interrelations that link the position and force constraints of the robotic arms to the grasped object. Subsequently, a motion model of the dual-arm system is derived, which remains unaffected by internal forces. To quickly obtain the object’s velocities with high precision, a practical prescribed-time velocity observer is constructed by incorporating a time-dependent scaling function. A revised performance boundary function is utilized to integrate the tracking errors associated with the grasping system, unlike existing approaches that define it solely as a time-dependent function. The barrier function is employed to map the complex output error constraints to new error variables, thereby facilitating the simplification of the controller design. Finally, simulation results are presented to illustrate and evaluate the effectiveness of the proposed method.