Robot Kinematics Parameter Calibration Based on Improved Differential Evolution Algorithm

In the process of evaluating the robot performance, the positioning accuracy of the robot is an important index. In order to deeply study the positioning accuracy of the robot, it is necessary to calibrate the robot by using the improved differential evolution algorithm. In the application process of improved differential evolution algorithm, Metropolis acceptance criterion should be used to obtain more spatial regions and ensure better convergence. At the same time, the evaluation function of population diversity is proposed to monitor the aggregation degree of population particles. Once the population ions are below a certain threshold, secondary mutation operation can be carried out to prevent local optimization. In order to effectively verify the robot kinematics parameter calibration method based on improved differential evolution algorithm, in the simulation experiment, it is necessary to use six-degree-of-freedom robot and laser tracker to complete the experimental process. Through experimental analysis, the average distance accuracy of the robot that completes the calibration of kinematic parameters is effectively improved, and the experiment proves that the calibration method of robot kinematic parameters based on improved differential evolution algorithm has strong application value. In the concrete research, it is necessary to analyze from different angles, such as differential evolution algorithm, Metropolis acceptance criteria and population diversity evaluation function, to ensure the practicability of the improved differential evolution algorithm.