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Personal Peculiarity Classification of Flat Finishing Skill Training by using Torus type Self-Organizing Maps

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Distributed Computing and Artificial Intelligence, 14th International Conference (DCAI 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 620))

Abstract

The paper proposes an unsupervised classification method for peculiarities of flat finishing motion with an iron file, measured by a 3D stylus. The classified personal peculiarities are used to correct learner’s finishing motions effectively for skill training. In the case of such skill training, the number of classes of peculiarity is unknown. A torus type Self-Organizing Maps is effectively used to classify such unknown number of classes of peculiarity patterns.

Experimental results of the classification with measured data of an expert and sixteen learners show effectiveness of the proposed method.

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References

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Author information

Authors and Affiliations

  1. Hiroshima Institute of Technology, Hiroshima, Japan

    Masaru Teranishi, Shinpei Matsumoto, Nobuto Fujimoto & Hidetoshi Takeno

Authors
  1. Masaru Teranishi
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  2. Shinpei Matsumoto
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  3. Nobuto Fujimoto
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  4. Hidetoshi Takeno
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Corresponding author

Correspondence to Masaru Teranishi .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, Department of Electronics, Information and Communication Engineering , Osaka Institute of Technology, Osaka, Osaka, Japan

    Sigeru Omatu

  2. Departamento de Informática y Automática, Facultad de Ciencias, Universidad de Salamanca , Salamanca, Spain

    Sara Rodríguez

  3. Departamento de Informática y Automática, Facultad de Ciencias, Universidad de Salamanca, Salamanca, Spain

    Gabriel Villarrubia

  4. GECAD - Instituto Superior de Engenharia, Porto, Portugal

    Pedro Faria

  5. Department of Control and Management Systems, Kielce University of Technology, Faculty of Electrical Engineering and Computer Science, Kielce, Poland

    Paweł Sitek

  6. Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, Spain

    Javier Prieto

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Teranishi, M., Matsumoto, S., Fujimoto, N., Takeno, H. (2018). Personal Peculiarity Classification of Flat Finishing Skill Training by using Torus type Self-Organizing Maps. In: Omatu, S., Rodríguez, S., Villarrubia, G., Faria, P., Sitek, P., Prieto, J. (eds) Distributed Computing and Artificial Intelligence, 14th International Conference. DCAI 2017. Advances in Intelligent Systems and Computing, vol 620. Springer, Cham. https://doi.org/10.1007/978-3-319-62410-5_28

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  • DOI: https://doi.org/10.1007/978-3-319-62410-5_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62409-9

  • Online ISBN: 978-3-319-62410-5

  • eBook Packages: EngineeringEngineering (R0)

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