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European Workshop on Evolutionary Robotics

EvoRobots 1998: Evolutionary Robotics pp 227–247Cite as

Incremental evolution of neural controllers for robust obstacle-avoidance in Khepera

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1468))

Abstract

A two-stage incremental approach has been used to simulate the evolution of neural controllers for robust obstacle-avoidance in a Khepera robot and has proved to be more efficient than a competing direct approach. During a first evolutionary stage, obstacle-avoidance controllers in medium-light conditions have been generated. During a second evolutionary stage, controllers avoiding strongly-lighted regions, where the previously acquired obstacle-avoidance capacities would be impaired, have been obtained. The best controller thus evolved has been successfully downloaded on a Khepera robot. The SGOCE evolutionary paradigm that has been used in these experiments is described in the text. Additional experiments are required to assess the usefulness of the corresponding implementation details. Future research will target furthering the incremental evolutionary process and evolving more intricate behaviors.

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Authors and Affiliations

  1. AnimatLab, Ecole Normale Supérieure, France

    Joël Chavas, Christophe Corne, Peter Horvai, Jérôme Kodjabachian & Jean-Arcady Meyer

Authors
  1. Joël Chavas
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  2. Christophe Corne
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  3. Peter Horvai
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  4. Jérôme Kodjabachian
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  5. Jean-Arcady Meyer
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Philip Husbands Jean-Arcady Meyer

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© 1998 Springer-Verlag Berlin Heidelberg

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Chavas, J., Corne, C., Horvai, P., Kodjabachian, J., Meyer, JA. (1998). Incremental evolution of neural controllers for robust obstacle-avoidance in Khepera. In: Husbands, P., Meyer, JA. (eds) Evolutionary Robotics. EvoRobots 1998. Lecture Notes in Computer Science, vol 1468. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64957-3_75

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  • DOI: https://doi.org/10.1007/3-540-64957-3_75

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64957-1

  • Online ISBN: 978-3-540-49902-2

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