Hierarchical calibration method of industrial robots based on PSO-SVR algorithm

To improve the positional accuracy of universal robot in the application, a hierarchical calibration method was proposed. The first stage of the method was to calibrate the geometric parameter error. Based on the Modified Denavit-Hartenberg (MD-H) model, a complete industrial robot geometric parameter error model was established by adding the factors of reduction ratio and coupling ratio. After that, the Levenberg-Marquarelt (LM) algorithm was used to identify the geometric parameter errors of the robot and calculate the residuals. In the second stage, a residual error prediction model based on the Particle Swarm Optimization-Support Vector Regression (PSO-SVR) algorithm was established to compensate the residual error after correcting the geometric parameters. The universal six degrees of freedoms Industrial robot was used for experimental verification. After hierarchical calibration, the average position error of the robot end center point was reduced from 5. 866 mm to 0. 2116 mm, and the maximum position error was reduced from 10. 3229 mm to 0. 6999 mm, which verified the correctness and effectiveness of the calibration algorithm. © 2023 CIMS. All rights reserved.