Self-calibration of wearable upper limb Cable-driven exoskeleton

Cable-driven parallel robots (CDPRs) is an important branch of rehabilitation exoskeleton. Due to the non-rigid character of CDPRs, the geometric parameters of CDPRs are greatly deviated. Therefore, it is necessary to carry out geometric calibration of cable-driven rehabilitation exoskeleton. At present, there are still many difficulties in the geometric calibration of wearable upper limb cable-driven exoskeleton. This is because the body has the individual diversity and flexibility, and the motion system composed of the human body and the exoskeleton is more uncertain than the anthropomorphic robot arm. Aiming at this problem, an adaptive calibration method for upper limb cable-driven rehabilitation exoskeleton based on Newton-Raphson iteration was established, and the model of human-exoskeleton motion system were optimized in this paper. The adaptive calibration of human-exoskeleton motion system is realized for the first time. Experimental results show that this method can effectively improve the motion control accuracy and human-exoskeleton interaction experience.