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

Research output: Contribution to journalArticle

9 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)255-277
Number of pages23
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Issue number3
Publication statusPublished - Nov 2001
Externally publishedYes



  • Dynamic environments
  • Evolutionary algorithms
  • Fuzzy behavior based control
  • Fuzzy set based objective functions
  • Nonholonomic mobile robot

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence

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