The purpose of this paper is to present an efficient path planning method for the multi-UAV system in target coverage problems.

    Design/methodology/approach

    An enhanced particle swarm optimizer (PSO) is used to solve the path planning problem, which concerns the two-dimensional motion of multirotor unmanned aerial vehicles (UAVs) in a three-dimensional environment. Enhancements include an improved initial swarm generation and prediction strategy for succeeding generations. Initial swarm improvements include the clustering process managed by fuzzy c-means clustering method, ordering procedure handled by ant colony optimizer and design vector change. Local solutions form the foundation of a prediction strategy.

    Findings

    Numerical simulations show that the proposed method could find near-optimal paths for multi-UAVs effectively.

    Practical implications

    Simulations indicate the proposed method could be deployed for autonomous multi-UAV systems with target coverage problems.

    Originality/value

    The proposed method combines intelligent methods in the early phase of PSO, handles obstacle avoidance problems with a unique approach and accelerates the process by adding a prediction strategy.


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    Titel :

    An efficient path planning approach for autonomous multi-UAV system in target coverage problems


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    09.07.2024


    Format / Umfang :

    17 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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