KNOWLEDGE-BASED ROBOT VISION SYSTEM FOR AUTOMATED PART HANDLING

Authors

  • J. Wang School of Mechanical and Automotive Engineering, Hefei University of Technology
  • T.I. Van Niekerk Faculty of Engineering, the Built Environment and Information Technology, Nelson Mandela Metropolitan University
  • D.G. Hattingh Faculty of Engineering, the Built Environment and Information Technology, Nelson Mandela Metropolitan University
  • T. Hua Faculty of Engineering, the Built Environment and Information Technology, Nelson Mandela Metropolitan University

DOI:

https://doi.org/10.7166/19-1-110

Abstract

ENGLISH ABSTRACT: This paper discusses an algorithm incorporating a knowledge-based vision system into an industrial robot system for handling parts intelligently. A continuous fuzzy controller was employed to extract boundary information in a computationally efficient way. The developed algorithm for on-line part recognition using fuzzy logic is shown to be an effective solution to extract the geometric features of objects. The proposed edge vector representation method provides enough geometric information and facilitates the object geometric reconstruction for gripping planning. Furthermore, a part-handling model was created by extracting the grasp features from the geometric features.

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Published

2011-11-05

How to Cite

Wang, J., Van Niekerk, T., Hattingh, D., & Hua, T. (2011). KNOWLEDGE-BASED ROBOT VISION SYSTEM FOR AUTOMATED PART HANDLING. The South African Journal of Industrial Engineering, 19(1). https://doi.org/10.7166/19-1-110

Issue

Vol. 19 No. 1 (2008)

Section

General Articles

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