Unmanned Aerial Vehicles (UAVs) have proven their effectiveness in various types of missions, such as inspecting very high voltage transmission lines. They have successfully overcome several problems caused by traditional methods. To ensure accuracy and security in this mission, the UAV must follow a defined path that respects the safety distance and allows for the inspection of all the equipment along the electrical line, taking into account the UAV’s autonomy. Therefore, the development of a UAV path planning algorithm is necessary to determine the shortest path among a set of defined points. In this chapter, we focus on two approaches: the Genetic Algorithm (GA) and the Ant Colony Optimization (ACO) algorithm. We present their principles, methods, and steps, and simulate them in two different scenarios, varying the iteration numbers, to compare their results and execution times. The results show that the GA outperforms the ACO in terms of speed, but the ACO demonstrates quicker convergence. However, the ACO occasionally produces incorrect results.


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    Titel :

    Unmanned Aerial Vehicle Path Planning Algorithms for Very High Voltage Transmission Lines Inspection


    Weitere Titelangaben:

    Advances in Science, Technology & Innovation


    Beteiligte:
    Bendaoud, Mohamed (Herausgeber:in) / El Fathi, Amine (Herausgeber:in) / Bakhsh, Farhad Ilahi (Herausgeber:in) / Pierluigi, Siano (Herausgeber:in) / Fahmani, Lamyae (Autor:in) / Benhadou, Siham (Autor:in) / Medromi, Hicham (Autor:in)

    Kongress:

    International Conference on Electrical Systems & Automation ; 2023 ; Al Hoceïma, Morocco May 29, 2023 - May 30, 2023



    Erscheinungsdatum :

    01.06.2024


    Format / Umfang :

    6 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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