Steady-state genetic algorithms for growing topological mapping and localization

Authors:
Jinseok Woo;Naoyuki Kubota;Beom-Hee Lee
Affiliations:
Tokyo Metropolitan University, Tokyo, Japan;Tokyo Metropolitan University, Tokyo, Japan;School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Korea
Venue:
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Year:
2010

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Abstract

This paper proposes a method of simultaneous localization and mapping based on computational intelligence for a robot partner in unknown environments. First, we propose a method of topological map building based on a growing neural network. Next, we propose a method of localization based on steady-state genetic algorithm. Finally, we discuss the effectiveness of the proposed methods through several experimental results.