The traditional ant colony algorithm is inefficient to search, easy to fall into algorithm stagnation and local optimization problems in UAV path planning. To ensure that the UAV can avoid obstacles and fly safely, the ant colony algorithm is improved and optimized. First, the target planning area of the UAV is modeled in three dimensions using raster method. Secondly, the update rules of pheromones are improved, and the weight factors of pheromones and heuristics are adjusted. An unmanned aerial path planning algorithm based on improved ant colony algorithm is proposed to plan a safe and optimal path for the unmanned aerial vehicle. Finally, the simulation results show that the improved algorithm has a better flight path than the traditional algorithm.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    UAV path planning based on improved ant colony algorithm


    Beteiligte:

    Kongress:

    Second International Conference on Algorithms, Microchips, and Network Applications (AMNA 2023) ; 2023 ; Zhengzhou, China


    Erschienen in:

    Proc. SPIE ; 12635 ; 126350B


    Erscheinungsdatum :

    08.05.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Autonomous Vehicle Path Planning Based on Improved Ant Colony Algorithm

    Xing, Yan / Rao, Xin / Liu, Weidong et al. | TIBKAT | 2023


    Autonomous Vehicle Path Planning Based on Improved Ant Colony Algorithm

    Xing, Yan / Rao, Xin / Liu, Weidong et al. | Springer Verlag | 2022


    UAV Path Planning and Design Based On Improved ant Colony Algorithm

    Peng, Wenliang / Wang, Lili / Lu, Guiping | IEEE | 2024


    Path planning of UAVs formation based on improved ant colony optimization algorithm

    Qiannan, Zhao / Ziyang, Zhen / Chen, Gao et al. | IEEE | 2014