Trajectory Optimization Algorithm of Trajectory Rehabilitation Training Mode for Rehabilitation Robot

Abstract

It is a challenge for robot-assisted rehabilitation therapy to develop a training program with both customized and optimized characteristics. To optimize the scheme of the trajectory rehabilitation training mode, we design a trajectory optimization algorithm with an intelligent decision mechanism. A trajectory smoothing improvement algorithm is proposed to make the trajectory more suitable for rehabilitation training. In addition, we propose an improved genetic algorithm that reduces the optimization time and obtains a better solution. An adaptive variable time weight improved trapezoidal velocity algorithm is innovatively designed by fusing the above two algorithms with an optimal rehabilitation training program as a guide. Based on the experimental platform of the upper limb rehabilitation robot, it is demonstrated that the algorithm can provide comfortable and high-quality rehabilitation training for patients by adaptively optimizing the parameters of the trajectory model according to the training constraints. By combining an intelligent optimization algorithm with a rehabilitation robot trajectory planning algorithm, this paper realizes the unification of customization and optimization of a trajectory rehabilitation training program.