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Transactions on Computational Collective Intelligence XX pp 54–77Cite as

Shape Recognition Through Tactile Contour Tracing

A Simulation Study

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Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 9420))

Abstract

We present Contour-net, a bio-inspired model for tactile contour-tracing driven by an Hopf oscillator. By controlling the rhythmic movements of a simulated insect-like feeler, the model executes both wide searching and local sampling movements. Contour-tracing is achieved by means of contact-induced phase-forwarding of the oscillator. To classify the shape of an object, collected contact events can be directly fed into machine learning algorithms with minimal pre-processing (scaling). Three types of classifiers were evaluated, the best one being a Support Vector Machine. The likelihood of correct classification steadily increases with the number of collected contacts, enabling an incremental classification during sampling. Given a sufficiently large training data set, tactile shape recognition can be achieved in a position-, orientation- and size-invariant manner. The suitability for robotic applications is discussed.

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Acknowledgements

This work was supported by EU grant EMICAB (FP7-ICT, grant no. 270182) to Prof. Volker Dürr. We thank Thierry Hoinville for many important suggestion regarding the model, and Holk Cruse for valuable comments on earlier versions of the manuscript.

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Authors and Affiliations

  1. Department of Biological Cybernetics, Bielefeld University, Bielefeld, Germany

    André Frank Krause, Nalin Harischandra & Volker Dürr

  2. Cognitive Interaction Technology - Centre of Excellence (CITEC), Bielefeld University, Bielefeld, Germany

    André Frank Krause, Nalin Harischandra & Volker Dürr

Authors
  1. André Frank Krause
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  2. Nalin Harischandra
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  3. Volker Dürr
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Corresponding author

Correspondence to André Frank Krause .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Manageme, Wroclaw University of Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Swinburne University of Technology, Hawthorn, Australia

    Ryszard Kowalczyk

  3. LERIA - UFR Sciences, Angers Cedex 01, France

    Béatrice Duval

  4. Leiden, Zuid-Holland, Leiden University, Leiden, The Netherlands

    Jaap van den Herik

  5. LERIA - UFR Sciences, Angers Cedex 01, France

    Stephane Loiseau

  6. INSTICC, Polytechnic Institute of Setubal, Setubal, Portugal

    Joaquim Filipe

Appendix

Appendix

The following link provides a zip archive that contains the Matlab scripts and data sets that were used to train the neural networks and support vector machines. Further, scripts are included to generate custom training data sets using the Contour-net method. http://www.andre-krause.net/publications/tcci15krause.zip

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Krause, A.F., Harischandra, N., Dürr, V. (2015). Shape Recognition Through Tactile Contour Tracing. In: Nguyen, N., Kowalczyk, R., Duval, B., van den Herik, J., Loiseau, S., Filipe, J. (eds) Transactions on Computational Collective Intelligence XX . Lecture Notes in Computer Science(), vol 9420. Springer, Cham. https://doi.org/10.1007/978-3-319-27543-7_3

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  • DOI: https://doi.org/10.1007/978-3-319-27543-7_3

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