Adaptive hybrid impedance control for dual-arm cooperative manipulation with object uncertainties

Abstract

In this paper, a novel adaptive hybrid impedance control for a dual-arm robot is proposed to cooperatively manipulate unknown objects. The proposed adaptive hybrid control scheme could be employed to improve the control performance of motion tracking and internal force regulation when dual-arm cooperative robot grasp an unknown object. Along with the analysis of human motion in the process of transferring, the controller has a master–slave structure in three levels: the first level is an absolute-relative motion controller satisfying the closed-chain constraints; the second level introduces an adaptive impedance control with variable stiffness to regulate the internal force; the motion and force control signals are fused in the third level with a select matrix. The controller uses the forces sensed at the end-effectors to compute the internal force with only kinematics, and the dynamics of the object is not required. To verify the effectiveness of the algorithm, a dual-arm robotic system is set up with two UR5 arms and the experimental results illustrate the performance and feasibility of the proposed control strategy.