A Variable Admittance Control Strategy for Stable and Compliant Human-Robot Physical Interaction

Admittance control is an important method for providing collaborative robots with precise manipulation and flexible contact behavior in industrial settings that often involve physical interaction. However, too rigid or high-frequency interactions by non-specialists will jeopardise the stability of the system. To address this issue, this research presents a novel admittance control framework for collaborative robots to detect oscillatory states and maintain stability by adjusting the controller parameters. In particular, a recursive haptic stability observer is designed to provide a quantitative assessment of the system stability, while a variable admittance controller based on model predictive control is constructed for optimal tuning of stability and flexibility to meet the requirements of a variable task. The effectiveness of the present algorithm is verified in experiments simulating two industrial tasks conducted on the AUBO I5 collaborative robot with 23 volunteers. In addition, the algorithm is tested for application in real collaborative tasks.