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Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly

Publication ,  Journal Article
Jakovljevic, Z; Petrovic, PB; Mikovic, VD; Pajic, M
Published in: Journal of Intelligent Manufacturing
January 1, 2014

This paper presents a methodology for generating a fuzzy inference mechanism (FIM) for recognizing contact states within robotic part mating using active compliant motion. In the part mating process, significant uncertainties are inherently present. As a result it is pertinent that contact states recognition systems operating in such environment be able to make decisions on the contact state currently present in the process, based on data full of uncertainties and imprecision. In such conditions, implementation of fuzzy logic and interval inference brings significant robustness to the system. As a starting point for FIM generation, we use a quasi-static model of the mating force between objects. By applying Discrete Wavelet Transform to the signal generated using this model, we extract qualitative and representative features for classification into contact states. Thus, the obtained patterns are optimally classified using support vector machines (SVM). We exploit the equivalence of SVM and Takagi-Sugeno fuzzy rules based systems for generation of FIM for classification into contact states. In this way, crisp granulation of the feature space obtained using SVM is replaced by optimal fuzzy granulation and robustness of the recognition system is significantly increased. The information machine for contact states recognition that is designed using the given methodology simultaneously uses the advantages of creation of machine based on the process model and the advantages of application of FIM. Unlike the common methods, our approach for creating a knowledge base for the inference machine is neither heuristic, intuitive nor empirical. The proposed methodology was elaborated and experimentally tested using an example of a cylindrical peg in hole as a typical benchmark test. © 2012 Springer Science+Business Media New York.

Duke Scholars

Published In

Journal of Intelligent Manufacturing

DOI

EISSN

1572-8145

ISSN

0956-5515

Publication Date

January 1, 2014

Volume

25

Issue

3

Start / End Page

571 / 587

Related Subject Headings

  • Industrial Engineering & Automation
  • 4601 Applied computing
  • 4014 Manufacturing engineering
  • 0910 Manufacturing Engineering
  • 0899 Other Information and Computing Sciences
  • 0801 Artificial Intelligence and Image Processing
 

Citation

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Jakovljevic, Z., Petrovic, P. B., Mikovic, V. D., & Pajic, M. (2014). Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly. Journal of Intelligent Manufacturing, 25(3), 571–587. https://doi.org/10.1007/s10845-012-0706-x
Jakovljevic, Z., P. B. Petrovic, V. D. Mikovic, and M. Pajic. “Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly.” Journal of Intelligent Manufacturing 25, no. 3 (January 1, 2014): 571–87. https://doi.org/10.1007/s10845-012-0706-x.
Jakovljevic Z, Petrovic PB, Mikovic VD, Pajic M. Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly. Journal of Intelligent Manufacturing. 2014 Jan 1;25(3):571–87.
Jakovljevic, Z., et al. “Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly.” Journal of Intelligent Manufacturing, vol. 25, no. 3, Jan. 2014, pp. 571–87. Scopus, doi:10.1007/s10845-012-0706-x.
Jakovljevic Z, Petrovic PB, Mikovic VD, Pajic M. Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly. Journal of Intelligent Manufacturing. 2014 Jan 1;25(3):571–587.
Journal cover image

Published In

Journal of Intelligent Manufacturing

DOI

EISSN

1572-8145

ISSN

0956-5515

Publication Date

January 1, 2014

Volume

25

Issue

3

Start / End Page

571 / 587

Related Subject Headings

  • Industrial Engineering & Automation
  • 4601 Applied computing
  • 4014 Manufacturing engineering
  • 0910 Manufacturing Engineering
  • 0899 Other Information and Computing Sciences
  • 0801 Artificial Intelligence and Image Processing