Military unmanned aerial vehicles (UAVs) are employed in highly dynamic environments and must often adjust their trajectories based on the evolving situation. To operate autonomously and safely, a UAV must be equipped with a path planning module capable of quickly recalculating a feasible and quasi-optimal path in flight while in the event a new obstacle or threat has been detected or simply if the destination point is changed during the mission. To allow for a fast path planning, this paper proposes a parallel implementation of the genetic algorithm on graphics processing unit (GPU). The trajectories are built as series of line segments connected by circular arcs resulting in smooth paths suitable for fixed-wing UAVs. The fitness function we defined takes into account the dynamic constraints of the UAVs and aims to minimize fuel consumption and average flying altitude in order to improve range and avoid detection by enemy radars. This fitness function is also implemented on the GPU and different parallelization strategies were developed and tested for each step of the fitness evaluation. By exploiting the massively parallel architecture of GPUs, the execution time of the proposed path planner was reduced by a factor of 290x compared to a sequential execution on CPU. The path planning module developed was tested using 18 scenarios on six realistic three-dimensional terrains with multiple no-fly zones. We found that the proposed GPU-based path planner was able to find quasi-optimal solutions in a timely fashion allowing in-flight planning.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Fast Genetic Algorithm Path Planner for Fixed-Wing Military UAV Using GPU


    Beteiligte:


    Erscheinungsdatum :

    2018-10-01


    Format / Umfang :

    6300512 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Decentralized fast-MPC path planner for automated vehicles

    Arrigoni, S. / Braghin, F. / Cheli, F. | IEEE | 2017


    Dynamic trip planner for public transport using genetic algorithm

    Abhishek Basu / Bharathi Raja / Rony Gracious et al. | DOAJ | 2020

    Freier Zugriff

    UNSTRUCTURED VEHICLE PATH PLANNER

    HUANG ZHENQI / KOBILAROV MARIN | Europäisches Patentamt | 2024

    Freier Zugriff

    UNSTRUCTURED VEHICLE PATH PLANNER

    HUANG ZHENQI / HUDECEK JANEK / KOBILAROV MARIN et al. | Europäisches Patentamt | 2023

    Freier Zugriff