• DocumentCode
    3167023
  • Title

    Coordinating networked uninhabited air vehicles for persistent area denial

  • Author

    Liu, Yong ; Cruz, Jose B., Jr. ; Sparks, Andrew G.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Ohio State Univ., Columbus, OH, USA
  • Volume
    3
  • fYear
    2004
  • fDate
    17-17 Dec. 2004
  • Firstpage
    3351
  • Abstract
    This paper explores the problem of cooperative control among multiple networked unmanned air vehicles (UAVs) for persistent area denial (PAD) mission. An adaptive Markov chain model is used to predict the locations of pop-up threats. The mixed information of predicted pop-up threats and actual pop-up targets is utilized to develop cooperative strategies for networked UAVs. The approach is illustrated by use of a simulation test bed for multiple networked UAVs and Monte Carlo simulation runs to evaluate our cooperative strategy. Both theoretical analysis and simulation results are presented to demonstrate the effectiveness of using predicted pop-up information in improving the overall PAD mission performance.
  • Keywords
    Markov processes; Monte Carlo methods; aircraft control; cooperative systems; remotely operated vehicles; Monte Carlo simulation; adaptive Markov chain model; cooperative control; cooperative strategies; multiple networked unmanned air vehicles; networked uninhabited air vehicles; persistent area denial; persistent area denial mission; predicted pop-up threats; Analytical models; Atherosclerosis; Communication system control; Information analysis; Performance analysis; Predictive models; Sparks; Telecommunication control; Testing; Unmanned aerial vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2004. CDC. 43rd IEEE Conference on
  • Conference_Location
    Nassau
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-8682-5
  • Type

    conf

  • DOI
    10.1109/CDC.2004.1429003
  • Filename
    1429003