Compound Control Method for Human-powered Augmentation Upper Exoskeleton Based on Motion Intent Recognition

Aiming at the problem of response delay when the human-powered augmentation upper exoskeleton, a motion intent recognition algorithm based on data fusion of human-robot interaction force signal and pose signal is proposed. Classify, determine the wearer's movement intent, make adaptive adjustments to the control parameters, and change the response speed of the Human-robot collaboration system. The fruit fly optimization algorithm（FOA） is used to optimize the support vector machine to improve the classification accuracy; Finite state machine（FSM） is introduced to deal with unreasonable motion intents. In order to reduce the tracking error of the exoskeleton control system, a compound control method of exoskeleton combining fuzzy control and impedance control was designed to improve the update speed of control parameters and adjust the trajectory in real time. The motion intent recognition experiment was set up. The results show that the recognition accuracy can reach 97.93%, which can quickly detect unreasonable motion intents, compared to using EMG signals as motion data, reduce the difficulty of signal processing, and maintain a high accuracy. The exoskeleton boosting performance test experiment proved the feasibility of the control method.