Adaptive Fuzzy Impedance Control of Human-Robot Interaction Modular Robot Manipulators Based on Human Motion Intention Estimation

For modular robot manipulators (MRMs) with physical human-robot interaction (pHRI) tasks, an adaptive fuzzy impedance control method based on the estimation of human motion intention is proposed in this paper. Dynamic subsystem of MRM is built based on joint torque feedback (JTF) technique. Processing unknown human limb models using fuzzy logic systems (FLSs), the obtained intention of the human is considered as the desired trajectory for impedance control, enabling the robot to actively follow a target impedance model. Adaptive fuzzy impedance control is utilized to compensate for model uncertainty and accomplish tracking goals. The uniformly ultimately bounded (UUB) of the tracking error is verified through Lyapunov theory. Eventually, the validity of the proposed adaptive fuzzy impedance control method is experimentally verified.