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High-Performance Combination of Low Resolution Tactile Images Using a Bit-Based Representation

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Advances in Autonomous Robotics (TAROS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7429))

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Abstract

Since the seminal work of Harmon[1] through to more recent reviews such as that of Dahiya et al.[2], the focus in the field of tactile sensing has been on creating sensors with resolutions as low as 1mm2. Such specifications are justified by the simplicity of manufacturing a single resolution of skin sensor for all possible applications. Unfortunately, this approach requires not only that a robot has some means of connecting to potentially millions of sensors, but more significantly that it has some means of processing the commensurately large volume of data. The work presented here reduces the volume of data that must be processed by allowing the requirement for high resolution sensors to be relaxed and by the novel use of the bitboard data structure that has been used to represent board games for computers as well as solve complex graph problems [3].

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References

  1. Harmon, L.D.: Robotic Taction for Industrial Assembly. Int. J. Rob. Res. 3(2), 72–76 (1984)

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  2. Dahiya, R.S., Metta, G., Valle, M., Sandini, G.: Tactile Sensing – From Humans to Humanoids. IEEE Trans. Rob. 26(1), 1–20 (2010)

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  3. Segundo, P.S., Galan, R., Matia, F., Rodriguez-Losada, D., Jimenez, A.: Efficient Search Using Bitboard Models. In: Proc. 18th IEEE Int. Conf. Tools with A.I., pp. 132–138 (2006)

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  4. van den Heever, D.J., Schreve, K., Scheffer, C.: Tactile Sensing Using Force Sens-ing Resistors and a Super-Resolution Algorithm. IEEE Sensors 9(1), 29–35 (2009)

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Author information

Authors and Affiliations

  1. Department of Electronic and Electrical Engineering, University of Bath, Bath, UK

    Frederick Pollard

Authors
  1. Frederick Pollard
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Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering and Bristol Robotics Laboratory, University of Bristol, Bristol, UK

    Guido Herrmann

  2. Intelligent Autonomous Systems Lab Faculty of Computing, Engineering & Mathematical Sciences, University of the West of England, BS16 1QY, Bristol, U.K.

    Matthew Studley

  3. University of the West of England, BS34 8QZ, Bristol, UK

    Martin Pearson , Andrew Conn  & Chris Melhuish ,  & 

  4. Department of Electrical and Electronic Engineering, Imperial College London, Exhibition Road, SW7 2BT, London, UK

    Mark Witkowski

  5. Robot Intelligence Technology Laboratory, Department of EECS, KAIST, Daejeon, Korea

    Jong-Hwan Kim

  6. National University of Singapore, Singapore

    Prahlad Vadakkepat

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© 2012 Springer-Verlag Berlin Heidelberg

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Pollard, F. (2012). High-Performance Combination of Low Resolution Tactile Images Using a Bit-Based Representation. In: Herrmann, G., et al. Advances in Autonomous Robotics. TAROS 2012. Lecture Notes in Computer Science(), vol 7429. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32527-4_49

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  • DOI: https://doi.org/10.1007/978-3-642-32527-4_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32526-7

  • Online ISBN: 978-3-642-32527-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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