Training Path Optimization Method of a Moveable Multifunction Rehabilitation Robot

Abstract

Passive path tracking training is usually used for robot assisted lower limb rehabilitation. The movement of robot will cause the fluctuation of joint force. This letter presents an optimal training path planning algorithm to reduce the patient's joint force caused by a moveable multifunction rehabilitation robot during passive pedaling training. The dynamics model of the human-robot system is established, and the joint forces of the patient are analysed. The planning process is divided into a series of motion steps based on the original training path, at which the optimal algorithm is applied to search the best path. Then, the optimal path is fitted by Bezier curve to get a closed training trajectory. Finally, a Bionic Experiment Platform (BEP) and Human-robot Interaction Platform (HIP) are established to verify the effectiveness of the optimal algorithm. The (BEP) experimental results show that the knee joint force drops by an average of 12.71%, and the maximum drops by 15.41%.The HIP experiment results show that the interaction force drops by an average of 8.5%.