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

Authors:
D. P. Thrishantha Nanayakkara;Keigo Watanabe;Kazuo Kiguchi;Kiyotaka Izumi
Affiliations:
Faculty of Engineering Systems and Technology, Graduate School of Science and Engineering, Saga University, 1–/Honjomachi, Saga 840-8502, Japan;Department of Advanced Systems Control Engineering, Graduate School of Science and Engineering, Saga University, 1–/ Honjomachi, Saga 840-8502, Japan/ e-mail: watanabe@me.saga-uac.jp< ...;Department of Advanced Systems Control Engineering, Graduate School of Science and Engineering, Saga University, 1–/ Honjomachi, Saga 840-8502, Japan;Department of Mechanical Engineering, Faculty of Science and Engineering, Saga University, 1–/Honjomachi, Saga 840-8502, Japan
Venue:
Journal of Intelligent and Robotic Systems
Year:
2001

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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.