유전자 알고리즘의 수렴 속도 향상을 통한 효과적인 로봇 길 찾기 알고리즘

초록

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.

키워드

유전자 알고리즘; 유전자 연산자; 로봇 경로 탐색; 빠른 수렴; Genetic Algorithm; Genetic Operator; Robot Path Planning; Fast Convergence
제목
유전자 알고리즘의 수렴 속도 향상을 통한 효과적인 로봇 길 찾기 알고리즘
저자
Seo, Min-Gwan; Lee, Jae-Sung; Kim, Dae-Won
발행일
2015-04
저널명
한국컴퓨터정보학회논문지
권
20
호
4
페이지
25 ~ 32