• DocumentCode
    2687661
  • Title

    A fitness-sharing based genetic algorithm for collaborative Multi Robot Localization

  • Author

    Bori, Francesco ; Gasparri, Andrea ; Panzieri, Stefano

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Roma Tre, Rome, Italy
  • fYear
    2009
  • fDate
    10-15 Oct. 2009
  • Firstpage
    3968
  • Lastpage
    3973
  • Abstract
    In this paper, a novel genetic algorithm based on a ¿collaborative¿ fitness-sharing technique to deal with the Multi-Robot Localization problem is proposed. Indeed, the use of the fitness-sharing is twofold and competitive. It preserves the diversity among individuals during the space exploration process, thus maintaining evolutionary niches over time, and reinforces the best hypotheses by means of collaboration among robots, thus augmenting the selection pressure. Simulations by exploiting the robotics framework Player/Stage have been performed along with a proper statistical analysis for performance assessment.
  • Keywords
    genetic algorithms; multi-robot systems; simulation; statistical analysis; collaborative multi robot localization; fitness-sharing; genetic algorithm; performance assessment; simulations; statistical analysis; Collaborative work; Genetic algorithms; Intelligent robots; International collaboration; Multirobot systems; Navigation; Orbital robotics; Robot localization; Robot sensing systems; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on
  • Conference_Location
    St. Louis, MO
  • Print_ISBN
    978-1-4244-3803-7
  • Electronic_ISBN
    978-1-4244-3804-4
  • Type

    conf

  • DOI
    10.1109/IROS.2009.5354581
  • Filename
    5354581