TACTIP - Tactile Fingertip Device, Texture Analysis through Optical Tracking of Skin Features

  • Benjamin Winstone
  • Gareth Griffiths
  • Tony Pipe
  • Chris Melhuish
  • Jonathon Rossiter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8064)


In this paper we present texture analysis results for TACTIP, a versatile tactile sensor and artificial fingertip which exploits compliant materials and optical tracking. In comparison to previous MEMS sensors, the TACTIP device is especially suited to tasks for which humans use their fingertips; examples include object manipulation, contact sensing, pressure sensing and shear force detection. This is achieved whilst maintaining a high level of robustness. Previous development of the TACTIP device has proven the device’s capability to measure force interaction and identify shape through edge detection. Here we present experimental results which confirm the ability to also identify textures. This is achieved by measuring the vibration of the in-built human-like skin features in relation to textured profiles. Modifications to the mechanical design of the TACTIP are explored to increase the sensitivity to finer textured profiles. The results show that a contoured outer skin, similar to a finger print, increases the sensitivity of the device.


Tactile Sensor Optical Tracking Robot Hand Texture Recognition Pacinian Corpuscle 
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  1. 1.
    Chorley, C., Melhuish, C., Pipe, T., Rossiter, J.: Development of a Tactile Sensor Based on Biologically Inspired Edge Encoding. Design (2008)Google Scholar
  2. 2.
    Chorley, C., Melhuish, C., Pipe, T., Rossiter, J.: Tactile Edge Detection. Sensors, 2593–2598 (2010)Google Scholar
  3. 3.
    Roke, C., Melhuish, C., Pipe, T., Drury, D., Chorley, C.: Deformation-Based Tactile Feedback Using a Biologically-Inspired Sensor and a Modified Display. Technology, 114–124 (2011)Google Scholar
  4. 4.
    Assaf, T., Chorley, C., Rossiter, J., Pipe, T., Stefanini, C., Melhuish, C.: Realtime Processing of a Biologically Inspired Tactile Sensor for Edge Following and Shape Recognition. In: TAROS (2010)Google Scholar
  5. 5.
    Winstone, B., Griffiths, G., Melhuish, C., Pipe, T.: TACTIP - Tactile Fingertip Device, Challenges in reduction of size to ready for robot hand integration. In: ROBIO, pp. 160–166 (2012)Google Scholar
  6. 6.
    Brooks, R., Aryananda, L., Edsinger, A., Fitzpatrick, P., Kemp, C., Torres-jara, E., Varshavskaya, P., Weber, J.: Sensing and manipulating built-for-human environments. International Journal of Humanoid Robotics, 1–28 (2004)Google Scholar
  7. 7.
    Cole, J.: Pride and a Daily Marathon. 1 edn. The MIT Press (1995)Google Scholar
  8. 8.
    Hollins, M.: Somesthetic senses. Annual Review of Psychology 61, 243–271 (2010)CrossRefGoogle Scholar
  9. 9.
    Hollins, M., Bensmaïa, S.J.: The coding of roughness. Canadian Journal of Experimental Psychology 61(3), 184–195 (2007)CrossRefGoogle Scholar
  10. 10.
    Mayol-Cuevas, W.W., Juarez-Guerrero, J., Munoz-Gutierrez, S.: A First Approach to Tactile Texture Recognition. In: SMC. Number 1993, pp. 4246–4250 (1998)Google Scholar
  11. 11.
    Diamond, M.E., von Heimendahl, M., Arabzadeh, E.: Whisker-mediated texture discrimination. PLoS Biology 6(8), e220 (2008)Google Scholar
  12. 12.
    Pearson, M.J., Mitchinson, B., Sullivan, J.C., Pipe, A.G., Prescott, T.J.: Biomimetic vibrissal sensing for robots.. Philosophical transactions of the Royal Society of London. Series B, Biological Sciences 366(1581), 3085–3096 (2011)CrossRefGoogle Scholar
  13. 13.
    Gomez, G., Pfeifer, R.: Haptic discrimination of material properties by a robotic hand. In: ICDL, pp. 1–6 (July 2007)Google Scholar
  14. 14.
    Mukaibo, Y., Shirado, H., Konyo, M., Maeno, T.: Development of a Texture Sensor Emulating the Tissue Structure and Perceptual Mechanism of Human Fingers. In: ICRA. Number, 2576–2581 (April 2005)Google Scholar
  15. 15.
    Torres-Jara, E.M., Vasilescu, I.M., Coral, R.M., Asilescu, I.: A soft touch: Compliant Tactile Sensors for Sensitive Manipulation (2006)Google Scholar
  16. 16.
    Lang, P.: Optical Tactile Sensors for Medical Palpation Pencilla Lang. (2004)Google Scholar
  17. 17.
    Ferrier, N.J., Brockett, R.W., Hristu, D., Cdcss, T.R.: The performance of a deformable-membrane tactile sensor: basic results on geometrically-defined tasks. In: ICRA, vol. 0114, pp. 508–513 (2000)Google Scholar
  18. 18.
    Dandekar, K., Raju, B.I., Srinivasan, M.A.: 3-D Finite-Element Models of Human and Monkey Fingertips to Investigate the Mechanics of Tactile Sense. Journal of Biomechanical Engineering 125(5), 682 (2003)CrossRefGoogle Scholar
  19. 19.
    Salehi, S., Cabibihan, J.J., Ge, S.S.: Artificial skin ridges enhance local tactile shape discrimination. Sensors 11(9), 8626–8642 (2011)CrossRefGoogle Scholar
  20. 20.
    Scheibert, J., Debregeas, G., Prevost, A.: A MEMS-based tactile sensor to study human digital touch: mechanical transduction of the tactile information and role of fingerprints. In: EPJ Web of Conferences, vol. 6, p. 21006 (June 2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Benjamin Winstone
    • 1
  • Gareth Griffiths
    • 1
  • Tony Pipe
    • 1
  • Chris Melhuish
    • 1
  • Jonathon Rossiter
    • 2
  1. 1.Bristol Robotics LaboratoryUniversity of the West of EnglandUK
  2. 2.Engineering MathematicsUniversity of BristolUK

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