Robot calibration is an important process used for enhancing the positioning accuracy of robots. In this paper, a modified differential evolution algorithm was proposed for the identification of robot kinematic parameters. The generalized Metropolis acceptance criterion was used in the selection operation of the proposed algorithm to explore more regions of the search space for a better convergence. In addition, the population evaluation function established in this study could greatly enhance the global-optimization ability of the modified differential evolution algorithm. Herein, the kinematic model was developed based on the product of exponentials (POE) formula to describe the relationship between the kinematic parameter errors and the end-effector positioning errors. To verify the efficiency of the proposed algorithm, simulations and experiments were performed using a six-degree-of-freedom robot and laser tracker. Through the kinematics parameter calibration, the average distance precision of robot is reduced from 2.906 0 mm (calibration) to 0.095 2 mm. The experimental results proves the effectiveness of the modified differential evolution algorithm for calibration of robot kinematics parameters.
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