• DocumentCode
    2370015
  • Title

    UAV route planning based on the genetic simulated annealing algorithm

  • Author

    Meng, Hao ; Xin, Guizhou

  • Author_Institution
    Autom. Coll., Harbin Eng. Univ., Harbin, China
  • fYear
    2010
  • fDate
    4-7 Aug. 2010
  • Firstpage
    788
  • Lastpage
    793
  • Abstract
    For the local minimum problem of genetic algorithm in unmanned aerial vehicle route planning, the Metropolis acceptance criteria of simulated annealing algorithm is incorporated into the genetic algorithm in this paper. In the algorithm, the original DEM (Digital Elevation Map) is processed into the smallest threat surface. In order to obtain a more smooth surface of flight, the original digital elevation map are processed in four directions, and then the genetic simulated annealing algorithm is used for three-dimensional route planning in this minimal threat surface. In addition, the distance between the track segment and threats are converted into elevation values and the value is added to the fitness function, a smaller code space was proposed at the same time. The simulation results show that the Genetic Simulated Annealing Algorithm proposed is good.
  • Keywords
    aircraft; digital elevation models; genetic algorithms; path planning; remotely operated vehicles; simulated annealing; UAV route planning; digital elevation map; genetic simulated annealing algorithm; unmanned aerial vehicle route planning; Genetics; Interpolation; Planning; Simulated annealing; Smoothing methods; Surface treatment; Unmanned aerial vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2010 International Conference on
  • Conference_Location
    Xi´an
  • ISSN
    2152-7431
  • Print_ISBN
    978-1-4244-5140-1
  • Electronic_ISBN
    2152-7431
  • Type

    conf

  • DOI
    10.1109/ICMA.2010.5589035
  • Filename
    5589035