Abstract
The existing exoskeleton rehabilitation equipment still has great obstacles to the compliance tracking of normal gait. Therefore, the anthropomorphic compliance control of the rehabilitation exoskeleton robot is still a hot research topic. One of the ways to improve this problem is to import the gait characteristics of human normal motion to achieve human-like tracking and control of the robot. This paper collected normal human gait data and obtained smooth gait data after preprocessing such as filtering and interpolation. Then, combine the collected data with OpenSim to build a musculoskeletal model that matches the subject and analyze the high-fidelity model’s joint angle and joint moment. Finally, the joint moment signal with the characteristics of human gait is used as the controller input of the exoskeleton robot, and the exoskeleton robot is simulated, analyzed, and verified. The simulation results prove the scientificity and effectiveness of the method.
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