Autonomous Robots

, Volume 26, Issue 4, pp 223–239

Contact type dependency of texture classification in a whiskered mobile robot

  • Charles W. Fox
  • Ben Mitchinson
  • Martin J. Pearson
  • Anthony G. Pipe
  • Tony J. Prescott
Article

DOI: 10.1007/s10514-009-9109-z

Cite this article as:
Fox, C.W., Mitchinson, B., Pearson, M.J. et al. Auton Robot (2009) 26: 223. doi:10.1007/s10514-009-9109-z

Abstract

Actuated artificial whiskers modeled on rat macrovibrissae can provide effective tactile sensor systems for autonomous robots. This article focuses on texture classification using artificial whiskers and addresses a limitation of previous studies, namely, their use of whisker deflection signals obtained under relatively constrained experimental conditions. Here we consider the classification of signals obtained from a whiskered robot required to explore different surface textures from a range of orientations and distances. This procedure resulted in a variety of deflection signals for any given texture. Using a standard Gaussian classifier we show, using both hand-picked features and ones derived from studies of rat vibrissal processing, that a robust rough-smooth discrimination is achievable without any knowledge of how the whisker interacts with the investigated object. On the other hand, finer discriminations appear to require knowledge of the target’s relative position and/or of the manner in which the whisker contact its surface.

Keywords

Whiskers Vibrissae Tactile sensing Texture discrimination 

Supplementary material

Below is the link to the electronic supplementary material

Below is the link to the electronic supplementary material

Below is the link to the electronic supplementary material

Below is the link to the electronic supplementary material

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Charles W. Fox
    • 1
  • Ben Mitchinson
    • 1
  • Martin J. Pearson
    • 2
  • Anthony G. Pipe
    • 2
  • Tony J. Prescott
    • 1
  1. 1.Adaptive Behavior Research GroupDepartment of Psychology, University of SheffieldSheffieldUK
  2. 2.Bristol Robotics LaboratoryBristolUK

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