• DocumentCode
    3565772
  • Title

    Genetic algorithms for coordinating multi-agent robotic systems

  • Author

    Lin, Fang-Chang

  • Author_Institution
    Commun. Network Lab., Inst. for Inf. Ind., Taipei, Taiwan
  • Volume
    4
  • fYear
    1997
  • Firstpage
    3431
  • Abstract
    This paper provides a genetic algorithm for solving the object-sorting task. The object-sorting task is a complex multi-agent task which requires the cooperation of multiple agents for searching and moving the objects to their destinations. The agent-object sequence is utilized to represent the solutions and for performance evaluation. The object-agent sequence is developed for chromosome representation and GA operations. A distributed help model and a centralized furniture mover model are used for performance comparison. The experimental results showed that the GA is better than the two compared models. In addition, each chromosome operated in the evolution process is designed to be feasible so as to reduce the execution time
  • Keywords
    genetic algorithms; mobile robots; path planning; performance evaluation; agent-object sequence; centralized furniture mover model; chromosome representation; complex multi-agent task; distributed help model; genetic algorithms; multi-agent robotic systems coordination; object-sorting task; performance evaluation; Biological cells; Biological information theory; Evolution (biology); Genetic algorithms; Mobile robots; Pediatrics; Process design; Robot kinematics; Service robots; Sorting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-4053-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1997.633183
  • Filename
    633183