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The Scientific World Journal
Volume 2014, Article ID 746260, 8 pages
http://dx.doi.org/10.1155/2014/746260
Research Article

Path Planning Using a Hybrid Evolutionary Algorithm Based on Tree Structure Encoding

Department of Computer Science and Information Engineering, National University of Tainan, Tainan 70005, Taiwan

Received 21 February 2014; Accepted 8 April 2014; Published 28 May 2014

Academic Editors: V. Bhatnagar and Y. Zhang

Copyright © 2014 Ming-Yi Ju et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A hybrid evolutionary algorithm using scalable encoding method for path planning is proposed in this paper. The scalable representation is based on binary tree structure encoding. To solve the problem of hybrid genetic algorithm and particle swarm optimization, the “dummy node” is added into the binary trees to deal with the different lengths of representations. The experimental results show that the proposed hybrid method demonstrates using fewer turning points than traditional evolutionary algorithms to generate shorter collision-free paths for mobile robot navigation.