• DocumentCode
    538872
  • Title

    Chaos Genetic Algorithm for Aircraft Route Planning Problem

  • Author

    Gao, Ye ; Zheng, Tao

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Xi´´an Univ. of Sci. & Technol., Xi´´an, China
  • Volume
    1
  • fYear
    2010
  • fDate
    16-17 Dec. 2010
  • Firstpage
    280
  • Lastpage
    284
  • Abstract
    The paper discusses route planning issues of aircraft by Chaos Genetic Algorithm, emphases on planning its flight track of Chasing targets, at a low altitude. Firstly, the dynamic model of the aircraft is discreted in the low-altitude and complex environments, Secondly, according to the constraints, this paper develops modeling drawing on grid method in the 2D space after the 3D is divided into multiple 2D, Thirdly, chaos genetic algorithm is applied for the path optimization in the 2D space, Finally, the track search process to avoid obstacles is completed in the 3D space. About simulation, Creator and Vega are used as modeling tools to build the simulation platform. It´s proved that the algorithm can plan a flight path which meets the requirements effectively, and avoid the complexity of solving route planning problem in the 3D space by transforming 3D into 2D. Therefore, it improves the engineering practicability of the algorithm.
  • Keywords
    aircraft; attitude control; chaos; collision avoidance; genetic algorithms; path planning; search problems; 2D space; Creator; Vega; aircraft route planning problem; chaos genetic algorithm; chasing targets; flight track; grid method; modeling drawing; obstacle avoidance; path optimization; track search process; Aircraft; Equations; Mathematical model; Optimization; Planning; Solid modeling; Three dimensional displays; Chaos Genetic Algorithm; Creator; Three-dimensional route planning; Vega;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9247-3
  • Type

    conf

  • DOI
    10.1109/GCIS.2010.206
  • Filename
    5708761