Optimizing the trajectories of autonomous unmanned aerial vehicles (UAVs) in a decentralized cooperative tracking of a ground target is not a trivial undertaking. In this case, the UAV formation is a complex interconnected nonlinear system. This paper investigates a genetic algorithm for optimizing the trajectories of UAVs engaged in cooperative target tracking by means of vector field guidance, thus performing collective circumnavigation. Computational modeling shows that the genetic algorithm can effectively address trajectory optimization. Post-optimization reduction in the fitness function value is noted. Another finding is that it is necessary, when tuning the UAV heading controllers, to minimize not only the error of distance to the circular path around the target but also the relative inter-UAV distance error.


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    Titel :

    Application of Genetic Algorithm for Vector Field Guidance Optimization in a UAV Collective Circumnavigation Scenario


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Cascalho, José M. (Herausgeber:in) / Tokhi, Mohammad Osman (Herausgeber:in) / Silva, Manuel F. (Herausgeber:in) / Mendes, Armando (Herausgeber:in) / Goher, Khaled (Herausgeber:in) / Funk, Matthias (Herausgeber:in) / Muslimov, Tagir (Autor:in)

    Kongress:

    Climbing and Walking Robots Conference ; 2022 ; Ponta Delgada, Portugal September 12, 2022 - September 14, 2022



    Erscheinungsdatum :

    2022-08-25


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch