The poor absolute positioning accuracy of industrial robots is the main obstacle for its further application in precision grinding of complex surfaces, such as blisk, blade, etc. Based on the established kinematic error model of a typical industrial robot FANUC M710ic/50, a novel kinematic parameters calibration method is proposed in this paper to improve the absolute positioning accuracy of robot. The pre-identification of the kinematic parameter deviations of robot was achieved by using the Levenberg-Marquardt algorithm. Subsequently, these identified suboptimal values of parameter deviations were defined as central values of the components of initial individuals to complete accurate identification by using Differential Evolution algorithm. The above two steps, which were regarded as the core of this Levenberg-Marquardt and Differential Evolution hybrid algorithm, were used to obtain the preferable values for kinematic parameters of the robot. On this basis, the experimental investigations of kinematic parameters calibration were conducted by using a laser tracker and numerical simulation method. The results revealed that the robot positioning error decreased from 0.994 mm, initial positioning error measured by laser tracker, to 0.262 mm after calibration with this proposed hybrid algorithm. The absolute positioning accuracy has increased by 40.86% than that of the Levenberg-Marquardt algorithm, increased by 40.31% than that of the Differential Evolution algorithm, and increased by 25.14% than that of the Simulated Annealing algorithm. This work shows that the proposed kinematic parameters calibration method has a significant improvement on the absolute positioning accuracy of industrial robot.

工业机器人的绝对定位精度差是其进一步应用在复杂表面（如大刀，刀片等）的精密磨削中的主要障碍。基于典型工业机器人FANUC M710ic / 50建立的运动学误差模型，提出了运动学参数标定方法，以提高机器人的绝对定位精度。使用Levenberg-Marquardt算法实现了机器人运动学参数偏差的预识别。随后，将这些识别出的参数偏差的次优值定义为初始个体成分的中心值，以使用差分进化算法完成精确识别。以上两个步骤，作为Levenberg-Marquardt和差分进化混合算法的核心，它们被用来获得机器人运动学参数的优选值。在此基础上，采用激光跟踪仪和数值模拟方法进行了运动学参数标定的实验研究。结果表明，使用该混合算法进行校准后，机器人的定位误差从0.994 mm（由激光跟踪器测量的初始定位误差）降低到0.262 mm。绝对定位精度比Levenberg-Marquardt算法提高了40.86％，比差分进化算法提高了40.31％，比模拟退火算法提高了25.14％。