• DocumentCode
    2716159
  • Title

    Multiple UAV teams for multiple tasks

  • Author

    Sujit, P.B. ; Sousa, Joao ; Pereira, Fernando

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Porto, Porto, Portugal
  • fYear
    2009
  • fDate
    8-10 July 2009
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In a search and prosecute mission, multiple heterogeneous unmanned aerial vehicles UAVs that carry different resources need to perform the classify, prosecute and battle damage assessment (BDA) tasks on targets sequentially. Depending on the target resource requirement, it may be necessary to deploy a coalition of UAVs to perform the action. In this paper, we propose coalition formation algorithms that have low computational overhead to determine coalitions for the prosecute and the BDA tasks. We also develop a simultaneous strike mechanism based on Dubins curves for the UAVs to prosecute the target simultaneously. Monte-Carlo simulation results are presented to show how the algorithms work and the effect of increasing the number of BDA tasks on the mission performance.
  • Keywords
    Monte Carlo methods; military aircraft; mobile robots; position control; remotely operated vehicles; Dubins curves; Monte-Carlo simulation; battle damage assessment tasks; coalition formation algorithm; heterogeneous unmanned aerial vehicles; prosecute mission; search mission; simultaneous strike mechanism; Command and control systems; Competitive intelligence; Computational intelligence; Fuels; Military computing; Monitoring; Robot sensing systems; Security; Surveillance; Unmanned aerial vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Security and Defense Applications, 2009. CISDA 2009. IEEE Symposium on
  • Conference_Location
    Ottawa, ON
  • Print_ISBN
    978-1-4244-3763-4
  • Electronic_ISBN
    978-1-4244-3764-1
  • Type

    conf

  • DOI
    10.1109/CISDA.2009.5356535
  • Filename
    5356535