• DocumentCode
    1561173
  • Title

    A path replanning algorithm based on roadmap-diagram

  • Author

    Yan, Ping ; Ding, Mingyue ; Zhou, Chengping ; Zheng, Changwen

  • Author_Institution
    Dept. of Weaponry Eng., Naval Univ. of Eng., Wuhan, China
  • Volume
    3
  • fYear
    2004
  • Firstpage
    2433
  • Abstract
    Unmanned air vehicles (UAVs) have many useful military applications. Among the many open issues to be addressed in the development of UAVs is that of path planning. Different from the past researches, the problems presented in this paper include not only the single-mission path planning in a known environment, but also the path replanning in uncertain and mission-changeable environment. In this paper, a hybrid path replanning algorithm is proposed, which is based on roadmap-diagram. The path planning process is split into two phases: the learning phase and the query phase. Environmental information and mission constraints of UAVs are integrated into building flight roadmap and searching for paths. The implementation and experiments have demonstrated that this hybrid algorithm is an efficient, robust algorithm that is able to handle different kinds of mission parameters and generate near-optimal paths with computation times that are acceptable for real-time in-flight applications.
  • Keywords
    aerospace computing; military aircraft; optimisation; path planning; remotely operated vehicles; hybrid algorithm; learning phase; military applications; path planning; path replanning algorithm; query phase; roadmap diagram; robust algorithm; unmanned air vehicles; Hybrid power systems; Military computing; Path planning; Reconnaissance; Remotely operated vehicles; Road vehicles; Robots; Robustness; Unmanned aerial vehicles; Weapons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
  • Print_ISBN
    0-7803-8273-0
  • Type

    conf

  • DOI
    10.1109/WCICA.2004.1342031
  • Filename
    1342031