Research on Adaptive Fuzzy Impedance Control of Human-Massage Robot Interaction Based on Kelvin-Voigt Modeling

Due to the deformable surface and unknown biomechanical properties of human skin tissue, it brings a large impact on the contact position and force control of robotic massage. In this paper, an adaptive hybrid impedance control method is proposed. To adapt the massage robot to the environmental changes of muscle tissues in the human massage area, a human muscle tissue model was established, and a recursive least squares algorithm was optimized to identify the model parameters online. To determine the parameters of the impedance controller, a fuzzy system between the parameters of the skin tissue model and the robot contact dynamics model was developed. To keep the robot with proper end-effector orientation and stable contact force during the massage process, an adaptive force-position hybrid control strategy is proposed. On the one hand, a position controller for adaptive attitude adjustment is used to control the move position and the normal direction of the robot. On the other hand, a force controller based on impedance control is used to ensure a stable contact force during dynamic interaction with human. Furthermore, since massage is a human contact task, the adaptive impedance control strategy also improves the interaction safety performance and contact detection. The effectiveness and feasibility of the massage system using adaptive fuzzy impedance control adapted to the variation of human muscle tissue is verified through experiments on the robot massage movement.