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)

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.

Original languageEnglish
Pages (from-to)255-277
Number of pages23
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Volume32
Issue number3
DOIs
Publication statusPublished - Nov 1 2001
Externally publishedYes

Keywords

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

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Evolutionary learning of a fuzzy behavior based controller for a nonholonomic mobile robot in a class of dynamic environments'. Together they form a unique fingerprint.

  • Cite this