A novel kinematic parameters calibration method for industrial robot based on Levenberg-Marquardt and Differential Evolution hybrid algorithm

Abstract

• A new method is proposed to calibrate the kinematic parameters of robot, solving the high order nonlinear problem of Levenberg-Marquardt algorithm and the issue of slow convergence speed of Differential Evolution algorithm. • This method is validated on a FANUC M710ic/50 robot. • In consideration of the effect of measurement noise, such as measurement error of laser tracker, the coordinate system transformation error between the robot and laser tracker, the absolute positioning accuracy of robot has increased by almost 73.6% after calibration with hybrid algorithm. • A kind of joint space error compensation method is proposed to compensate for robot kinematic parameter deviations, overcoming the problem of authority limitation of modifying the D-H parameters of robot control system. 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.