Automatic Hand-Eye Calibration Method of Welding Robot Based on Linear Structured Light

Abstract

Aiming at solving the problems such as long calibration time, low precision, and complex operation in hand-eye calibration of welding robot, an automatic hand-eye calibration algorithm based on linear structured light was proposed to solve the calibration matrix X by using AX=ZB calibration equation. Firstly, a square calibration plate is customized to effectively constrain the structured light. The α-shape algorithm was adopted to extract the contour of the 3D point cloud model of the calibration plate. Secondly, an improved random sampling consistency algorithm which could determine the optimal iterative number was proposed to fit the contour point cloud, the contour point cloud model fitted was obtained. Finally, the 3D coordinates of the target points were determined with the linear structured light to complete the hand-eye calibration. In order to prevent the calibration plate from deviating from the acquisition range of the vision sensor during the calibration process, the distance between the linear structural light and the inner circle in the calibration plate was set to limit the motion range of the robot. In order to eliminate the error transfer of the robot body, an optimal solution of the rotation matrix R and the translation vector t of the calibration data was calculated with the singular value decomposition (SVD) and the least square rigid transpose method. The experimental results show that the calibration accuracy reaches 0.3 mm without compensating the robot body error, and the calibration speed is improved by 36% than the existing automatic calibration method. Therefore, the algorithm proposed can automatically complete the calibration only by establishing the user coordinates in advance, which improves the working accuracy and efficiency of the welding robots greatly.