Tracking control of lower limb exoskeleton robot based on human plantar reaction force

Abstract

To improve the safety and effectiveness of lower limb exoskeleton robot (LLER) in rehabilitation training, and bring more effective rehabilitation training for patients with lower limb paralysis. This paper proposes a control strategy for LLER based on the human plantar reaction force. First, the plantar reaction force and gait data are collected from a healthy human through the 3D experimental platform, while the joint torque and gait trajectory of the subject are got by dynamic and kinematic calculations. Second, the gait trajectory is used as the desired gait trajectory. The joint torque is fed to the LLER, which makes the LLER move and track the desired gait trajectory. Then, a radial basis function neural network controller based on tracking error is designed to compensate for the input torque of the LLER. Finally, the simulation results verify the effectiveness of the proposed method.