Evolutionary Learning of a Fuzzy Behavior Based Controller for a Nonholonomic Mobile Robot in a Class of Dynamic Environments View Full Text


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Article Info

DATE

2001-11

AUTHORS

D. P. Thrishantha Nanayakkara, Keigo Watanabe, Kazuo Kiguchi, Kiyotaka Izumi

ABSTRACT

This paper presents an approach for evolving optimum behaviors for a nonholonomic mobile robot in a class of dynamic environments. A new evolutionary algorithm reflecting some powerful features in the natural evolutionary process to have flexibility to deal with changes in the environment is used to evolve optimum behaviors. Furthermore, a fuzzy set based multi-objective fitness evaluation function is adopted in the evolutionary algorithm. The multi-objective evaluation function is designed so that it allows incorporating complex linguistic features that a human observer would desire in the behaviors of the mobile robot movements. To illustrate the effectiveness of the proposed method, simulation results are compared using a conventional evolutionary algorithm. More... »

PAGES

255-277

References to SciGraph publications

  • 1998. A Fuzzy-Neural Realization of Behavior-Based Control Systems for a Mobile Robot in SOFT COMPUTING FOR INTELLIGENT ROBOTIC SYSTEMS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1023/a:1013939308620

    DOI

    http://dx.doi.org/10.1023/a:1013939308620

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1037545446


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