• DocumentCode
    2539225
  • Title

    Ant Colony System Based Mobile Robot Path Planning

  • Author

    Chia, Song-Hiang ; Su, Kuo-Lan ; Guo, Jr-Hung, Jr. ; Chung, Cheng-Yun

  • Author_Institution
    Dept. of Electron. Eng., Wu-Feng Inst. of Technol., Chiayi, Taiwan
  • fYear
    2010
  • fDate
    13-15 Dec. 2010
  • Firstpage
    210
  • Lastpage
    213
  • Abstract
    Ant colony optimization (ACO) is a new evolvement algorithm that is proposed by Dorigo M., and solves some task allocation and target search problems to program the motion path searching food. The topic of the article uses the ant colony optimization algorithm to mobile robot system, and solve the problem of mobile robot path planning such that the target point in a collision free space. The simulated results presents that ACO can finds the optimization motion path for mobile robot moving to the target position (food) from the start position (nest) in a collision-free environment.
  • Keywords
    collision avoidance; mobile robots; motion control; search problems; ant colony optimization algorithm; ant colony system; collision-free environment; evolvement algorithm; mobile robot path planning; target search problems; task allocation problems; Ant colony optimization; Conferences; Mobile robots; Optimization; Path planning; Resource management; Ant colony optimization; collision-freee; task allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4244-8891-9
  • Electronic_ISBN
    978-0-7695-4281-2
  • Type

    conf

  • DOI
    10.1109/ICGEC.2010.59
  • Filename
    5715407