Weighted Hybrid Admittance-Impedance Control with Human Intention Based Stiffness Estimation for Human-Robot Interaction

摘要

In a human-robot interaction (HRI) device that performs physical collaboration operations in constant contact with the user, admittance control and impedance control are generally used. Since the two controllers exhibit opposite performances depending on the stiffness condition, controllers capable of dealing with various magnitudes of stiffness are required. As such, this study proposes hybrid control that adjusts the control distribution ratios of admittance control and impedance control based on the operating frequency analysis to react to the user intention and various stiffness conditions in real time. The proposed controller algorithm exhibited lower overshoot than impedance control in the step input response simulation, faster response speed compared to admittance control in the response simulation for 0-5 Hz input frequencies, and the smallest vibration magnitude and number of vibrations in the case of a virtual wall collision, resulting in improved performance compared to existing control methods.