Bin Zhao, Chengdong Wu, and Fengshan Zou
Nonlinear least-squares iterative, industrial robot, parameter identification, zero-positioncalibration, intelligent computing
This paper introduces a robot zero position parameter identification and calibration method based on high precision and zero cost, in order to solve the shortcomings of the traditional axis pin calibration and laser tracker calibration algorithms. The nonlinear least-squares iterative method proposed in this paper is used to identify the zero position parameters of the robot, and can effectively analyse and correct the kinematic errors of the robot. This method needs to collect 20 – 25 different pose data points of the robot in a fixed position, to determine the unknown deviation parameters in the zero-position model of the robot. At the same time, the four- point tool coordinate system calibration method is used to replace the existing five-point tool coordinate system calibration method. The experimental results show that the accuracy of the calibration method using zero position parameter identification is 69.847% higher than that of the most used shaft pin calibration method. Compared with the laser tracker calibration method with the highest accuracy, its time efficiency is improved by 80%. This method considers the calibration accuracy and efficiency, and significantly improves the adaptability of the zero-position calibration method to the calibration environment.
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