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http://dx.doi.org/10.9708/jksci.2015.20.4.025

Effective Robot Path Planning Method based on Fast Convergence Genetic Algorithm  

Seo, Min-Gwan (Dept. of Computer Science, Chung-Ang University)
Lee, Jae-Sung (Dept. of Computer Science, Chung-Ang University)
Kim, Dae-Won (Dept. of Computer Science, Chung-Ang University)
Publication Information
Journal of the Korea Society of Computer and Information / v.20, no.4, 2015 , pp. 25-32 More about this Journal
Abstract
The Genetic algorithm is a search algorithm using evaluation, genetic operator, natural selection to populational solution iteratively. The convergence and divergence characteristic of genetic algorithm are affected by selection strategy, generation replacement method, genetic operator when genetic algorithm is designed. This paper proposes fast convergence genetic algorithm for time-limited robot path planning. In urgent situation, genetic algorithm for robot path planning does not have enough time for computation, resulting in quality degradation of found path. Proposed genetic algorithm uses fast converging selection strategy and generation replacement method. Proposed genetic algorithm also uses not only traditional crossover and mutation operator but additional genetic operator for shortening the distance of found path. In this way, proposed genetic algorithm find reasonable path in time-limited situation.
Keywords
Genetic Algorithm; Genetic Operator; Robot Path Planning; Fast Convergence;
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