• DocumentCode
    163974
  • Title

    Optimal flight path planning for UAVs in 3-D threat environment

  • Author

    Yaohong Qu ; Yintao Zhang ; Youmin Zhang

  • Author_Institution
    Sch. of Autom., Northwestern Polytech. Univ., Xi´an, China
  • fYear
    2014
  • fDate
    27-30 May 2014
  • Firstpage
    149
  • Lastpage
    155
  • Abstract
    Nowadays, the environments surrounding modern battlefield are becoming increasingly complicated, since the threats are not only from the ground but also from the sky. UAV with reconnaissance mission will take more risk when flying along an improper planned path, so path planning of UAV in complex 3-D environments is very significant and challenging. Aimed at the problem, this paper proposes a novel optimal path planning method for UAV based on the flight space partitioning, Dijkstra algorithm and potential field theory. Specifically, under the cases that the locations of threats are assumed to be known and the whole flight space is partitioned into a number of cells and each cell has a safest node. Then, a 3-D network is formed by connecting the nodes of adjacent cells and a shortest suboptimal path is marked on the network with Dijkstra algorithm. Finally, the optimal path is obtained with artificial potential field method. To verify the proposed algorithm, simulation results in two cases are shown.
  • Keywords
    aircraft control; autonomous aerial vehicles; military aircraft; mobile robots; path planning; telerobotics; 3-D network; Dijkstra algorithm; UAV; artificial potential field method; flight space partitioning; optimal flight path planning; optimal path planning method; shortest suboptimal path; unmanned aerial vehicles; Algorithm design and analysis; Mathematical model; Radar; Radar antennas; Trajectory; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Unmanned Aircraft Systems (ICUAS), 2014 International Conference on
  • Conference_Location
    Orlando, FL
  • Type

    conf

  • DOI
    10.1109/ICUAS.2014.6842250
  • Filename
    6842250