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Modular Neural Architectures for Robotics

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Book cover Biologically Inspired Robot Behavior Engineering

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 109))

Abstract

The learning of sensory-motor functions have motivated important research works that emphasize a major demand: the combination of multiple neural networks to implement complex functions. A review of a number of works presents some implementations in robotics, describing the purpose of the modular architecture, its structure, and the learning technique that was applied. The second part of the chapter presents an original approach to this problem of network training, proposed by our group. Based on a bi-directional architecture, multiple networks can be trained online with simple local learning rules, while the robotic systems interact with their environment.

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Authors and Affiliations

  1. Trop Research Group, 4 r. Frères Lumière, 68093, Mulhouse, France

    J. L. Buessler & J. P. Urban

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  1. J. L. Buessler
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  2. J. P. Urban
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Editors and Affiliations

  1. Escuela Politécnica Superior, Universidade da Coruña, c/Mendizábal s/n, 15403, Ferrol (La Coruña), Spain

    Richard J. Duro

  2. Departamento de Computación, Universidade da Coruña, Campus de Elviña, 15701, La Coruña, Spain

    José Santos

  3. Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, UPV/EHU, 20018, San Sebastian, Spain

    Manuel Graña

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© 2003 Springer-Verlag Berlin Heidelberg

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Buessler, J.L., Urban, J.P. (2003). Modular Neural Architectures for Robotics. In: Duro, R.J., Santos, J., Graña, M. (eds) Biologically Inspired Robot Behavior Engineering. Studies in Fuzziness and Soft Computing, vol 109. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1775-1_10

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  • DOI: https://doi.org/10.1007/978-3-7908-1775-1_10

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2517-6

  • Online ISBN: 978-3-7908-1775-1

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