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Spatial Representation and Navigation in a Bio-inspired Robot

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Biomimetic Neural Learning for Intelligent Robots

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3575))

Abstract

A biologically inspired computational model of rodent repre-sentation–based (locale) navigation is presented. The model combines visual input in the form of realistic two dimensional grey-scale images and odometer signals to drive the firing of simulated place and head direction cells via Hebbian synapses. The space representation is built incrementally and on-line without any prior information about the environment and consists of a large population of location-sensitive units (place cells) with overlapping receptive fields. Goal navigation is performed using reinforcement learning in continuous state and action spaces, where the state space is represented by population activity of the place cells. The model is able to reproduce a number of behavioral and neuro-physiological data on rodents. Performance of the model was tested on both simulated and real mobile Khepera robots in a set of behavioral tasks and is comparable to the performance of animals in similar tasks.

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Author information

Authors and Affiliations

  1. Laboratory of Computational Neuroscience, Swiss Federal Institute of Technology, CH-1015, Lausanne, Switzerland

    Denis Sheynikhovich, Ricardo Chavarriaga, Thomas Strösslin & Wulfram Gerstner

Authors
  1. Denis Sheynikhovich
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  2. Ricardo Chavarriaga
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  3. Thomas Strösslin
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  4. Wulfram Gerstner
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Editor information

Editors and Affiliations

  1. University of Sunderland, SR6 0DD, Sunderland, United Kingdom

    Stefan Wermter

  2. Institute of Neural Information Processing, University of Ulm, D-89069, Ulm, Germany

    Günther Palm

  3. Hybrid Intelligent Systems, SCAT, University of Sunderland, UK

    Mark Elshaw

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© 2005 Springer-Verlag Berlin Heidelberg

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Sheynikhovich, D., Chavarriaga, R., Strösslin, T., Gerstner, W. (2005). Spatial Representation and Navigation in a Bio-inspired Robot. In: Wermter, S., Palm, G., Elshaw, M. (eds) Biomimetic Neural Learning for Intelligent Robots. Lecture Notes in Computer Science(), vol 3575. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11521082_15

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  • DOI: https://doi.org/10.1007/11521082_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27440-7

  • Online ISBN: 978-3-540-31896-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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