Enhancement of Process Capability for the Vision-Guided Robot


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.

Share and Cite:

Kwon, Y. (2015) Enhancement of Process Capability for the Vision-Guided Robot. Journal of Computer and Communications, 3, 78-84. doi: 10.4236/jcc.2015.311013.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] 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
[2] Oitzman, M. and Campbell, J. (2000) High Accuracy Positioning System Implements Robotic Applications with Guaranteed Placement Accuracy. Journal of Industrial Robot, 27, 274-278. http://dx.doi.org/10.1108/01439910010372091
[3] iVY System User’s Manual (2012) Yamaha Robot Vision System, Shizuoka, Japan.
[4] Watanabe, A., Sakakibara, S., Ban, K., Yamada, M. and Shen, G. (2005) Autonomous Visual Measurement for Accurate Setting of Workpieces in Robotic Cells. CIRP Annals—Manufacturing Technology, 54, 13-18. http://dx.doi.org/10.1016/S0007-8506(07)60039-0
[5] Montgomery, D.C. (2005) Introduction to Statistical Quality Control. John Wiley & Sons, Inc., Hoboken.
[6] Pawar, S. and Chavan, H. (2011) Tolerance Stack up Analysis and Simulation Using Visualization VSA. Journal of Advanced Engineering Technology, 2, 169-175.
[7] Chase, K. (2004) Chapter 7. Basic Tools for Tolerance Analysis of Mechanical Assemblies: Manufacturing Engineering Handbook. McGraw-Hill Publishing Co. Inc., New York.

Copyright © 2022 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.