Aiming at the problem of UAV swarm trajectory planning, this paper constructs a mathematical model of UAV swarm trajectory planning, and uses an improved particle swarm optimization to optimize the solution. First of all, this paper constructs the environment model and the corresponding cost function, the cost function of the single aircraft trajectory, and the constraint function inside the UAV swarm. Then the objective function of UAV swarm trajectory optimization is constructed. After that, in view of the shortcoming of particle swarm optimization (PSO) that is easy to fall into local optimality, based on the multi-agent theory’s Holonic structure, the PSO is improved to optimize the objective function. Finally, the UAV swarm trajectory planning algorithm flow based on the improved PSO algorithm is constructed to realize the trajectory planning of the UAV swarm. Compared with the current mainstream improved PSO algorithm, the algorithm in this paper has better performance.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    UAV Swarm Trajectory Planning Based on a Novel Particle Swarm Optimization


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wu, Meiping (Herausgeber:in) / Niu, Yifeng (Herausgeber:in) / Gu, Mancang (Herausgeber:in) / Cheng, Jin (Herausgeber:in) / Luo, Jing (Autor:in) / Liu, Jie (Autor:in) / Liang, QianChao (Autor:in)

    Kongress:

    International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021



    Erscheinungsdatum :

    18.03.2022


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    UAV Swarm Trajectory Planning Based on a Novel Particle Swarm Optimization

    Luo, Jing / Liu, Jie / Liang, QianChao | British Library Conference Proceedings | 2022


    UAV Swarm Trajectory Planning Based on a Novel Particle Swarm Optimization

    Luo, Jing / Liu, Jie / Liang, QianChao | TIBKAT | 2022



    Solving Constrained Trajectory Planning Problems Using Biased Particle Swarm Optimization

    Chai, Runqi / Tsourdos, Antonios / Savvaris, Al et al. | IEEE | 2021


    Receding-Horizon Trajectory Planning for Multiple UAVs Using Particle Swarm Optimization

    Vijayakumari, Dileep M. / Kim, Seungkeun / Suk, Jinyoung et al. | AIAA | 2019