Table of Content

Open Access iconOpen Access

ARTICLE

Research on Robot Control Technology Based on Vision Localization

Ruijiao Yin1, Jie Yang1,*

Heilongjiang University, Harbin, 150080, China.

*Corresponding Author: Jie Yang. Email: email.

Journal on Artificial Intelligence 2019, 1(1), 37-44. https://doi.org/10.32604/jai.2019.05815

Abstract

Based on the understanding of machine vision localization technology at home and abroad, this paper outlines the overall design of the system, and analyses the working principle and workflow of the robot with vision system in workpiece grinding. The hardware design of the system is introduced. The process of image processing is analyzed in detail, and the results of image processing are given. The basic parameters of camera imaging are taken as internal parameters. The camera calibration is obtained by rotation matrix R and translation parameter T. The coordinate transformation of camera coordinate system and world coordinate system is analyzed. Finally, the positions and postures of the actual workpiece and the end-effector in the world coordinate system are given respectively, and the robot with the vision system is used to grasp the actual workpiece. The difficulties of this project are visual calibration, image processing and coordinate transformation. Robot vision technology can directly grasp the location. Compared with the manual mechanical positioning, the robot that realizes autonomous vision localization has more flexibility, better quality and higher efficiency.

Keywords


Cite This Article

R. Yin and J. Yang, "Research on robot control technology based on vision localization," Journal on Artificial Intelligence, vol. 1, no.1, pp. 37–44, 2019. https://doi.org/10.32604/jai.2019.05815

Citations




cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 2556

    View

  • 1549

    Download

  • 2

    Like

Share Link