International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Evolvable Neural Networks Based on Developmental Models for Mobile Robot Navigation

  • Lee, Dong-Wook (Korea Institute of Industrial Technology(KITECH)) ;
  • Seo, Sang-Wook (School of Electrical and Electronic Engineering, Chung-Ang University) ;
  • Sim, Kwee-Bo (School of Electrical and Electronic Engineering, Chung-Ang University)
  • Published : 2007.09.01
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Abstract

This paper presents evolvable neural networks based on a developmental model for navigation control of autonomous mobile robots in dynamic operating environments. Bio-inspired mechanisms have been applied to autonomous design of artificial neural networks for solving practical problems. The proposed neural network architecture is grown from an initial developmental model by a set of production rules of the L-system that are represented by the DNA coding. The L-system is based on parallel rewriting mechanism motivated by the growth models of plants. DNA coding gives an effective method of expressing general production rules. Experiments show that the evolvable neural network designed by the production rules of the L-system develops into a controller for mobile robot navigation to avoid collisions with the obstacles.

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