• CN: 11-2187/TH
  • ISSN: 0577-6686

›› 2011, Vol. 47 ›› Issue (1): 48-54.

• Article • Previous Articles     Next Articles

Positioning Accuracy of Robot Vision System Based on Support Vector Machine Regression

YIN Xiangyun;YIN Guofu;HU Xiaobing;ZHAO Xuefeng   

  1. School of Manufacturing Science and Engineering, Sichuan University
  • Published:2011-01-05

Abstract: It is now a key technical issue to improve positioning accuracy of vision-based industrial robots to carry out complex tasks in dynamic and uncertain environment. Considering the accuracy and stability issues that pertain to position-based visual servo control for the monocular industrial robot, a method by combination of a model-based control method and intelligent-based calculation method is proposed. Based on support vector machine regression (SVR) oriented to small sample principle, an error revising model of the vision system for robots is constructed. A practical method based on SVR is designed to revise the planar positioning errors of robot manipulators, and compared with the error revising method based on linear interpolation and neural network. The experimental results demonstrate that this method can improve positioning accuracy of the vision-based robot and satisfy the demand of the location precision for industrial robots to carry through tasks, such as grabbing and assembly.

Key words: Industrial robot, Positioning accuracy, Support vector machine regression, Visual servo

CLC Number: