A Robot Positional Error Compensation Method Based on Improved Kriging Interpolation and Kronecker Products

This article proposes a stable and high-accuracy model-free calibration method for non-open robotic systems, which can significantly improve the robot positional accuracy. Two improvements are made to the existing kriging-based error compensation method to achieve robustness/practicality enhancement goals. The semivariogram model is solved using the sequential quadratic programming algorithm, and the distance weight coefficients are added to the objective function. The accuracy of semivariogram modeling is guaranteed, thereby improving the performance and stability of error compensation. The hand-eye (the pose matrix between the robot base and the laser tracker) and the tool center point position are calibrated based on Kronecker products without relying on the spatial analyzer software to construct the robot base coordinate system separately. Thus, the calibration accuracy and efficiency are significantly improved. Experiments have been conducted, and the results reveal that the proposed method can significantly reduce the robot positional error. Furthermore, the proposed approach performs better than the existing kriging-based error compensation method without Kronecker products. The maximum, mean, and root mean square values of the absolute positional errors are reduced by 34.48%, 8.09%, and 10.05%, respectively.