Geometric Parameter Calibration of Industrial Robots Based on Grey Wolf Optimization Algorithm

Over the past decades, industrial robots have been widely used in various intelligent manufacturing fields such as aerospace and automobile production. However, uncalibrated industrial robots are unable to meet the demands of these fields due to their own insufficient absolute localization accuracy, thus greatly limiting their application in high-precision intelligent manufacturing. In order to improve the absolute positioning accuracy of industrial robots, this paper proposes a method for calibrating the geometric parameters of industrial robots based on the Grey Wolf Optimization (GWO) algorithm. Firstly, the kinematic model of a typical industrial robot is established according to the Denavit-Hartenberg (DH) modeling method, and its error model is obtained through mathematical calculation, and then its calibration problem is transformed into an optimization problem by analyzing the error model. Secondly, a new calibration method based on the GWO algorithm is used to calibrate the geometric parameters of the industrial robot. Finally, the industrial robot ABB IRB4600 is taken as an experimental object, and the GWO algorithm is used to identify the geometric parameters of the industrial robot. An error compensation calibration experiment is carried out to verify the effectiveness of the GWO algorithm by means of a laser tracker. The results show that after calibrating the geometric parameters of the industrial robot using the GWO optimization algorithm, the value of the absolute positioning accuracy of the industrial robot is reduced from 1.943 mm to 0.546 mm.