Optimization of eye-in-hand calibration methods

Hand-eye calibration is a vital part in the field of robot vision and motion control, which ensures that the robot system can accurately perceive and operate the surrounding environment. To enhance the accuracy of the hand-eye calibration matrix obtained in the current experimental environment, this paper provides an optimal scheme for the selection of calibration points and hand-eye calibration algorithms on the checkerboard calibration board. The geometric errors, rotation-translation errors and other parameters of Tsai algorithm and Navy algorithm were calculated based on multiple sets of experimental data, and the performance differences between the two algorithms were evaluated. The experimental results show that in the calibration environment of this experiment, the optimal selection number of marker points is about 12, and the optimal calibration algorithm is Tsai algorithm. This study provides a reference for the optimization of robotic hand-eye calibration technology.