• DocumentCode
    3136862
  • Title

    Task allocation of multiple UAVs and targets using improved genetic algorithm

  • Author

    Zuo, Yong ; Peng, Zhihong ; Liu, Xin

  • Author_Institution
    Key Lab. of Complex Syst. Intell. Control & Decision, Beijing Inst. of Technol., Beijing, China
  • Volume
    2
  • fYear
    2011
  • fDate
    25-28 July 2011
  • Firstpage
    1030
  • Lastpage
    1034
  • Abstract
    In this paper, task allocation of multi-Unmanned Aerial Vehicles (UAVs) is studied, that is, multi-UAVs from different bases should be allocated to attack multiple targets. Based on the existing task allocation model, which just take the values of targets, UAVs and weapons into account, the fuel consumption is added into consideration to make the model much more practical. An improved genetic algorithm is proposed for such a multi-UAVs multi-targets task allocation. Simulation results show that the algorithm is significantly effective and the allocation result is reasonable.
  • Keywords
    aircraft; genetic algorithms; mobile robots; multi-robot systems; remotely operated vehicles; UAV; fuel consumption; improved genetic algorithm; multitargets task allocation; multiunmanned aerial vehicles; Genetics; Indexes; Navigation; Weapons; Zinc; Genetic Algorithm; Task Allocation; UAV;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4577-0813-8
  • Type

    conf

  • DOI
    10.1109/ICICIP.2011.6008408
  • Filename
    6008408