An industrial robot pose calibration method based on the optimal measurement poses

With the rapid development of industrial automation, industrial robots play a crucial role in manufacturing processes. To enhance the positioning accuracy and control capabilities of robots in precision manufacturing, this paper proposes a kinematic parameter calibration method based on the optimal measurement poses. Existing calibration methods often use randomly selected measurement poses, which can lead to unstable calibration results and poor robustness. To address this issue, this paper proposes an improved IOOPS(Iterative One-by-One Pose Search) algorithm. This algorithm optimises the selection of measurement poses by combining a greedy algorithm with the IOOPS algorithm, thereby improving calibration accuracy and efficiency. The experiment selected the BRTIRUS0707A robot as the calibration robot, used the improved IOOPS algorithm to select calibration points, and employed a laser tracker to calibrate the pose of the industrial robot. The results show that after calibration, the average position accuracy of the robot improved from 3.4986 mm to 0.3021 mm, and the average attitude accuracy improved from 0.4871° to 0.3521°. This method provides an efficient and precise kinematic parameter calibration method for industrial robots, optimising calibration accuracy and stability through the selection of optimal measurement poses, and has significant application value.