Path planning is the key to the realization of drone perception and action capabilities as a core technology. Particle swarm algorithm and its improved algorithm are widely used as one of the commonly algorithms to deal with path planning problems. Taking fixed-wing UAVs as the research object, combining the characteristics of UAV path planning, a mathematical model is established for the known three-dimensional global path planning problems of environmental models. This standard particle swarm algorithm path planning is analyzed and improved. Base on analysis, an improved PSO algorithm (GPSO) is proposed, and the effectiveness of the algorithm is verified through simulation experiments. And its speed and quality are better than PSO.


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    Titel :

    Particle Swarm Optimization for Fixed-Wing UAV Path Planning


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wu, Meiping (Herausgeber:in) / Niu, Yifeng (Herausgeber:in) / Gu, Mancang (Herausgeber:in) / Cheng, Jin (Herausgeber:in) / Lv, Yutao (Autor:in) / Chen, Yongming (Autor:in) / Tian, Jianming (Autor:in)

    Kongress:

    International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021



    Erscheinungsdatum :

    18.03.2022


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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