In the development of modern society, because of the strong application performance of uav, it can replace man-machine to perform more dangerous and complex tasks, so it has been widely used in economic construction and modern combat. According to the analysis of uav application in recent years, it is found that mission planning and autonomous flight are the main subjects of practical exploration, and the quality of flight path is the key factor to judge whether the mission can be carried out smoothly. Therefore, an adaptive polymorphic ant colony algorithm is proposed based on the detailed description of ant colony algorithm and the current research results of self-organizing UAV cluster path planning. The final results show that the application of ANT colony algorithm in the path planning of self-organizing UAV cluster can not only optimize the path, but also improve the flight accuracy.


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    Titel :

    Self-organized UAV Cluster Trajectory Planning Method Based on Ant Colony Algorithm


    Beteiligte:
    Ma, Ying (Autor:in) / Liu, Haiying (Autor:in)


    Erscheinungsdatum :

    2022-07-01


    Format / Umfang :

    945878 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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