Decentralized variable impedance control of modular robot manipulators with physical human–robot interaction using Gaussian process-based motion intention estimation

This paper proposes a decentralized variable impedance control method of modular robot manipulators (MRM) with physical human-robot interaction (pHRI) using Gaussian process-based motion intention estimation. The dynamic model of MRM subsystem is established by using joint torque feedback (JTF) technique. Human limb dynamic model is regarded as mechanical impedance model, and human motion intention is estimated online based on Gaussian process. A variable impedance control method is proposed to make the MRM comply with human motion intention in the process of pHRI. A decentralized sliding mode control strategy is designed to achieve high performance position tracking and compensate the uncertainty of the controller. Based on Lyapunov theory, the uniform ultimately bounded of tracking error of each joint is proved. Finally, the effectiveness of the proposed control method under pHRI is verified by experiments. The experimental results show that the proposed method reduces the position tracking error by ∼ 10