Effective Robot Path Planning Method based on Fast Convergence Genetic Algorithm

유전자 알고리즘의 수렴 속도 향상을 통한 효과적인 로봇 길 찾기 알고리즘

  • 서민관 (중앙대학교 컴퓨터공학부) ;
  • 이재성 (중앙대학교 컴퓨터공학부) ;
  • 김대원 (중앙대학교 컴퓨터공학부)
  • Received : 2015.02.02
  • Accepted : 2015.02.24
  • Published : 2015.04.30


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.


Grant : 뮤직 맵: 메타 정보 상관성 도출 및 시각화 기술을 이용한 음악 추천 서비스 개발


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