Adaptive impedance control in master-slave robotic systems: Real-time estimation with update of reference impedance coefficients

Abstract

This research addresses the challenge of effective human-robot interaction in master-slave robotic systems, particularly for applications like manufacturing and healthcare. A method is proposed for transferring desired impedance from a human operator to a slave robot. A three-term model estimates the interactive force/torque between the human hand and the master robot, with adaptive rules for updating stiffness and damping coefficients in real-time to provide accurate and responsive haptic feedback. These updated coefficients dynamically adjust the reference impedance model used to control the slave robot. This architecture, incorporating robust control techniques and estimators, ensures stability and transparency, enabling the master-side user to perceive conditions faced by the slave robot (e.g., obstacles). The slave robot responds according to the user's desired impedance, providing a seamless and intuitive interaction. Input-to-state stability analysis demonstrates robustness to disturbances and uncertainties. The proposed approach in this paper allows replicating the user impedance of the master robot to the slave robot, with the input-to-state stability of the entire closed-loop system analyzed in the presence of the proposed three-term model. The comparison of the root mean square (RMS) error measure for the tracking position and the tracking force/torque when the slave robot encounters an obstacle shows the favorable performance of the proposed approach compared to the impedance reference model approaches with fixed stiffness and damping coefficients and traditional position control approaches. Numerical simulations and experimental implementation validate the efficiency and accuracy of the proposed approach.