Robot hand-eye calibration improvement method for input parameter optimization
Due to the camera pose error and the robot motion solution error,the calibration result has a large error.In order to improve the accuracy of robot positioning and grasping,a hand-eye calibration method with error compensation and image correc-tion was proposed.Based on dual quaternion theory to describe spiral motion,the hand-eye transformation matrix was solved by singular value decomposition method.After studying the nonlinear camera imaging model,the reprojection error of the camera was minimized,then the optimized external reference of the camera was obtained,and the robot motion error was compensated according to the robot kinematic model.Finally,the robot monocular vision experimental platform was built,and the method was compared with the dual quaternion method and the Tasi two-step method.The experimental results showed that the coordinate error of the method in the three directions of XYZ was 0.46 and the standard deviation was 0.25.In terms of calibration accura-cy and stability,it is better than the other two methods,and has certain theoretical and practical significance.
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维普
