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Helping a Bio-inspired Tactile Sensor System to Focus on the Essential

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7102)

Abstract

Insects use their antennae (feelers) as near-range sensors for orientation, object localization and communication. This paper presents further developments for an approach for an active tactile sensor system. This includes a hardware construction as well as a software implementation for interpreting the sensor readings. The discussed tactile sensor is able to detect an obstacle and its location. Furthermore the material properties of the obstacles are classified by application of neural networks. The focus of this paper lies in the development of a method which allows to determine automatically the part of the input data which is actually needed to fulfill the classification task. For that, non-negative matrix factorization is evaluated by quantifying the trade-off between classification accuracy and input (and network) dimension.

Keywords

  • Active Tactile Sensing
  • FFT
  • Material Classification
  • Object Localization
  • Acceleration Measurement
  • Non-Negative Matrix Factorization NMF
  • Dimension Reduction

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  • DOI: 10.1007/978-3-642-25489-5_3
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References

  1. Staudacher, E., Gebhardt, M.J., Dürr, V.: Antennal movements and mechanoreception: neurobiology of active tactile sensors. Adv. Insect Physiol. 32, 49–205 (2005)

    CrossRef  Google Scholar 

  2. Dürr, V., König, Y., Kittmann, R.: The antennal motor system of the stick insect Carausius morosus: anatomy and antennal movement pattern during walking. J. Comp. Physiol. A 187, 31–144 (2001)

    Google Scholar 

  3. Dürr, V., Krause, A.: The stick insect antenna as a biological paragon for an actively moved tactile probe for obstacle detection. In: Proc. of CLAWAR 2001, pp. 87–96 (2001)

    Google Scholar 

  4. Hellbach, S., Krause, A.F., Dürr, V.: Feel Like an Insect: A Bio-Inspired Tactile Sensor System. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds.) ICONIP 2010. LNCS, vol. 6444, pp. 676–683. Springer, Heidelberg (2010)

    CrossRef  Google Scholar 

  5. Bebek, O., Cavusoglu, M.C.: Whisker sensor design for three dimensional position measurement in robotic assisted beating heart surgery. In: ICRA, pp. 225–231 (2007)

    Google Scholar 

  6. Kaneko, M., Kanayma, N., Tsuji, T.: Vision-based active sensor using a flexible beam. IEEE-ASME Trans. Mechatronics I 6, 7–16 (2001)

    CrossRef  Google Scholar 

  7. Ueno, N., Svinin, M.M., Kaneko, M.: Dynamic contact sensing by flexible beam. IEEE-ASME Trans. Mechatronics 3, 254–264 (1998)

    CrossRef  Google Scholar 

  8. Kaneko, M., Kanayma, N., Tsuji, T.: Active antenna for contact sensing. IEEE Trans. Robot. Autom. 14, 278–291 (1998)

    CrossRef  Google Scholar 

  9. Lange, O., Reimann, B., Saenz, J., Dürr, V., Elkmann, N.: Insectoid obstacle detection based on an active tactile approach. In: Proc. of AMAM (2005)

    Google Scholar 

  10. Fend, M., Bovet, S., Hafner, V.: The artificial mouse - A robot with whiskers and vision. In: Proc. of the 35th ISR (2004)

    Google Scholar 

  11. Dürr, V., Krause, A.F., Neitzel, M., Lange, O., Reimann, B.: Bionic Tactile Sensor for Near-Range Search, Localisation and Material Classification. In: AMS, pp. 240–246 (2007)

    Google Scholar 

  12. Pearson, K.: On lines and planes of closest fit to a system of points in space. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science. 6, 559–572 (1901)

    CrossRef  MATH  Google Scholar 

  13. Bochner, S., Chandrasekharan, K.: Fourier Transforms. Annals of Mathematics Studies 19 (1949)

    Google Scholar 

  14. Schwartz, W., Kembhavi, A., Harwood, D., Davis, L.: Human Detection using Partial Least Squares Analysis. In: ICCV (2009)

    Google Scholar 

  15. Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature 401, 788–791 (1999)

    CrossRef  MATH  Google Scholar 

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Hellbach, S., Otto, M., Dürr, V. (2011). Helping a Bio-inspired Tactile Sensor System to Focus on the Essential. In: Jeschke, S., Liu, H., Schilberg, D. (eds) Intelligent Robotics and Applications. ICIRA 2011. Lecture Notes in Computer Science(), vol 7102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25489-5_3

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  • DOI: https://doi.org/10.1007/978-3-642-25489-5_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25488-8

  • Online ISBN: 978-3-642-25489-5

  • eBook Packages: Computer ScienceComputer Science (R0)