Compensation of Trajectory Error for Industrial Robots by Interpolation and Calibration Method in the Joint Space

doi:10.3901/JME.2021.21.055

Abstract

Abstract: Trajectory accuracy is an important dynamic performance of industrial robots, which is far lower than the positioning accuracy at present. A method based on kinematic parameter identification and interpolation error compensation in the joint space is proposed to improve the trajectory accuracy of industrial robots. The kinematics model of the robot is established based on MD-H method. Then, the positioning error model and the trajectory error model are established by using the differential kinematics theory of robots. To overcome the problem of slow convergence or even divergence of traditional methods such as the least square method when the data noise is large and does not conform to the Gaussian distribution, a robot kinematics parameter identification method based on extended Kalman filter (EKF) algorithm is proposed to realize the fast convergence of kinematic parameter identification. By analysis, we find that the error of robots in joint space has the characteristics of continuity. Therefore, an interpolation error compensation method in the joint space is proposed. The error compensation database in grid form is established. The joint angle error of each control point is calculated by using the distance weight function in the joint space. The experimental results show that the absolute positioning accuracy of the robot is increased from 1.039 mm to 0.226 mm, and the trajectory accuracy is increased from 2.532 mm to 1.873 mm. The trajectory accuracy of the robot is further improved to 1.464 mm after the interpolation error compensation in the joint space.

Key words: industrial robot, trajectory accuracy, extended Kalman filter, error compensation, parameter identification

CLC Number:

TP242

GAO Guanbin, ZHANG Shiwen, NA Jing, LIU Fei. Compensation of Trajectory Error for Industrial Robots by Interpolation and Calibration Method in the Joint Space[J]. Journal of Mechanical Engineering, 2021, 57(21): 55-67.

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