Research on Robot Accuracy Compensation Method Based on Modified Grey Wolf Algorithm

Abstract

This paper proposes a method using the modified grey wolf algorithm for optimizing robot motion accuracy to address problems of insufficient robot trajectory accuracy and low efficiency of traditional optimization algorithms. First, the Denavit-Hartenberg method is used to establish a robotics kinematic error model. Considering the parameters for optimization in the model as variables in the system, the problem of improving the accuracy of the robot is transformed into a problem of optimization for a nonlinear system. An objective function is designed according to the robot's trajectory it will be solved by the MGWO (modified grey wolf) algorithm to obtain the optimal parameters of the robot in order to improve the positioning accuracy of the robot. The experimental results show that this method is effective and can effectively reduce the robot motion error and improve positioning accuracy after algorithm optimization.