Browse Menu >>

Browse Subjects >>

Biomedical & Life Sciences

Business & Economics

Chemistry & Materials Science

Computer Science & Communications

Earth & Environmental Sciences

Engineering

Medicine & Healthcare

Physics & Mathematics

Social Sciences & Humanities

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.

 

Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
   
Paper Publishing WeChat
Book Publishing WeChat
(or Email:book@scirp.org)

Article citations

More>>

Kwon, Y. and Park, Y. (2013) Improvement of Vision Guided Robotic Accuracy Using Kalman Filter. Journal of Computers & Industrial Engineering, 65, 148-155. http://dx.doi.org/10.1016/j.cie.2011.11.018

has been cited by the following article:

  • TITLE: Enhancement of Process Capability for the Vision-Guided Robot

    AUTHORS: Yongjin Kwon

    KEYWORDS: Process Capability, Assembly Robot, Vision Calibration, Positioning Accuracy

    JOURNAL NAME: Journal of Computer and Communications, Vol.3 No.11, November 19, 2015

    ABSTRACT: This study addresses a critical problem in the control of process capability as to the positioning accuracy of vision-guided robot. Depending on the calibration accuracy, the process capability varies widely, which renders the precise control of assembly tasks difficult. Furthermore, some vision sensors prohibit the programming access to rectify the lens distortion effects, which even complicates the problem. This study proposes a method of circumventing the lack of programming access by implementing the lens optical center alignment. Three different calibration methods are compared as to the process capability, and the proposed method shows a very good accuracy. The method can be easily adopted on the shop floor since it doesn’t require a complex setup and mathematical derivation process. Therefore, the practitioners can benefit from the proposed method, while maintaining a high level of precision in terms of robot positioning accuracy.