Dynamic control with a remote center-of-motion constraint for human–robot collaboration

Abstract

This paper presents a novel dynamics-based human–robot collaboration (HRC) control method with a remote center-of-motion (RCM) constraint. The existing works rely on prescribed main task trajectories and regard the RCM constraint as a secondary task, making them inapplicable in the fully interactive mode under HRC. Our work imposes a virtual RCM constraint on the interactive HRC process so that the robot’s motion conforms to human intentions while keeping the robot’s end-effector shaft always passing through a fixed (RCM) point. In our approach, the task coordinates of the RCM constraint and its Jacobian matrix are formulated, and a task control law with a computed torque controller is proposed to guarantee the convergence of the RCM error. In the null space of the RCM constraint, a mass-damping impedance control law is used to make the robot motion conform to human interactions. To address the uncertainties of both the dynamic model and external interactions of the robot, a nonlinear disturbance observer is employed to estimate the lumped disturbance projected to the task space of the RCM for steady error elimination. We also show that the robot RCM task approaches a singularity as the RCM error approaches zero. A least-squares damping inversion method is used to map the task-space motion to the joint space near the singularity. Experiments are performed to validate the effectiveness of our method, and the results show that the maximum RCM error is less than 0.85 mm during fast HRC interactions and converges to zero when the interactions cease.