Mathematics (Nov 2023)

Kinematics Parameter Calibration of Serial Industrial Robots Based on Partial Pose Measurement

  • Tiewu Xiang,
  • Xinyi Jiang,
  • Guifang Qiao,
  • Chunhui Gao,
  • Hongfu Zuo

DOI
https://doi.org/10.3390/math11234802
Journal volume & issue
Vol. 11, no. 23
p. 4802

Abstract

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The kinematics parameter error is the main error factor that affects the absolute accuracy of industrial robots. The absolute accuracy of industrial robots can be effectively improved through kinematics calibration. The error model-based method is one of the main methods for calibrating the kinematics parameter error. This paper presents a kinematics parameter calibration method for serial industrial robots based on partial pose measurement. Firstly, the kinematics and the pose error models have been established based on the modified Denavit–Hartenberg (MDH) model. By introducing the concept of error sensitivity, the average significance index is proposed to quantitatively analyze the effects of the kinematics parameter error on the pose error of a robot. The results show that there is no need to measure the full pose error of the robot. Secondly, a partial pose measurement device and method have been presented. The proposed device can measure the position error and the attitude error on the x-axis or y-axis. Finally, the full pose error model, the NP-type partial pose error model, and the OP-type partial pose error model have been applied for calibrating the kinematics parameter errors. The experimental results show that the effectiveness of the OP-type partial pose error model is consistent with the full pose error model.

Keywords