Bayesian motion intention estimation-based impedance control of modular robot manipulator: theory and experimental verification

This article proposes an impedance control method of modular robot manipulator (MRM) system for physical human-robot interaction (pHRI). Bayesian parameter estimation is employed to identify human motion intention, which is considered as the desired trajectory in impedance control that allows the MRM easily to track the target impedance model. The uniformly ultimately bounded (UUB) of the tracking error is proved based on Lyapunov theory, and the experimental results demonstrate the effectiveness of the proposed control method in pHRI.