Journal of Intelligent and Robotic Systems

, Volume 32, Issue 3, pp 255–277 | Cite as

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

  • D. P. Thrishantha Nanayakkara
  • Keigo Watanabe
  • Kazuo Kiguchi
  • Kiyotaka Izumi
Article

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.

nonholonomic mobile robot fuzzy behavior based control evolutionary algorithms dynamic environments fuzzy set based objective functions 

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Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • D. P. Thrishantha Nanayakkara
    • 1
  • Keigo Watanabe
    • 2
  • Kazuo Kiguchi
    • 2
  • Kiyotaka Izumi
    • 3
  1. 1.Faculty of Engineering Systems and Technology, Graduate School of Science and EngineeringSaga UniversitySagaJapan
  2. 2.Department of Advanced Systems Control Engineering, Graduate School of Science and EngineeringSaga UniversitySagaJapan
  3. 3.Department of Mechanical Engineering, Faculty of Science and EngineeringSaga UniversitySagaJapan

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