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Autonomous vehicle guidance using analog VLSI neuromorphic sensors

  • Part V: Robotics, Adaptive Autonomous Agents, and Control
  • Conference paper
  • First Online:
Artificial Neural Networks — ICANN'97 (ICANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

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Abstract

Analog VLSI circuits implementing aspects of biological systems are attractive for the construction of compact low-power autonomous systems. We describe such a system, consisting of a mobile robot equipped with a neuromorphic sensor implementing a one dimensional silicon retina. Specifically, we demonstrate how the real-time visual pre-processing capabilities of the neuromorphic sensor are instrumental in enabling the system to reliably and autonomously track a continuous edge. We present data both from the neuromorphic sensor and from the overall system, performing a line tracking task.

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Authors and Affiliations

  1. Institute for Neuroinformatics ETH/UNIZH, Gloriastrasse 32, CH-8006, Zurich, Switzerland

    Giacomo Indiveri & Paul Verschure

Authors
  1. Giacomo Indiveri
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  2. Paul Verschure
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Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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© 1997 Springer-Verlag Berlin Heidelberg

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Indiveri, G., Verschure, P. (1997). Autonomous vehicle guidance using analog VLSI neuromorphic sensors. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020254

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  • DOI: https://doi.org/10.1007/BFb0020254

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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