Unmanned aerial vehicle (UAV) swarms offer significant advantages in the form of close reconnaissance, flexible self-organized coordination, and attack unknown targets. Distributed online adaptive mission planning is a critical issue that must be addressed in the operational applications. Accordingly, a distributed online adaptive mission planning method for UAV swarm is proposed. We developed an adaptive heuristic information state transition method based on an ant colony optimization algorithm for the two mission modes of reconnaissance-search and attack. Considering the local adjacent range of a UAVs’ consumption attack on its target, an adaptive target allocation decision algorithm is employed to improve the efficiency of the entire swarm’s search and attack mission execution. The proposed method’s effectiveness has been verified through simulation experiments, which reveal the method to yield an optimal weighted comprehensive total target existence time and search coverage rate.


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    Title :

    Online Adaptive Cooperative Search-Attack Mission Planning for UAV Swarm in Unknown Environment


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yan, Liang (editor) / Duan, Haibin (editor) / Deng, Yimin (editor) / Liu, Hongfu (author) / Fu, Yajing (author) / Chen, Libin (author)

    Conference:

    International Conference on Guidance, Navigation and Control ; 2024 ; Changsha, China August 09, 2024 - August 11, 2024



    Publication date :

    2025-03-02


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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