Given the accelerated advancement of drones in an array of application domains, the imperative of effective path planning has emerged as a quintessential research focus. Particularly in intricate three-dimensional (3D) environments, formulating the optimal flight path for drones poses a substantial challenge. Nonetheless, prevalent path-planning algorithms exhibit issues encompassing diminished accuracy and inadequate stability. To solve this problem, a hybrid improved symbiotic organisms search (ISOS) and sine–cosine particle swarm optimization (SCPSO) method for drone 3D path planning named HISOS-SCPSO is proposed. In the proposed method, chaotic logistic mapping is first used to improve the diversity of the initial population. Then, the difference strategy, the novel attenuation functions, and the population regeneration strategy are introduced to improve the performance of the algorithm. Finally, in order to ensure that the planned path is available for drone flight, a novel cost function is designed, and a cubic B-spline curve is employed to effectively refine and smoothen the flight path. To assess performance, the simulation is carried out in the mountainous and urban areas. An extensive body of research attests to the exceptional performance of our proposed HISOS-SCPSO.


    Access

    Download


    Export, share and cite



    Title :

    A Hybrid Improved Symbiotic Organisms Search and Sine–Cosine Particle Swarm Optimization Method for Drone 3D Path Planning


    Contributors:
    Tao Xiong (author) / Hao Li (author) / Kai Ding (author) / Haoting Liu (author) / Qing Li (author)


    Publication date :

    2023




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    UAV Path Planning Based on Rolling Sine-Cosine Harris Hawks Optimization

    Yang, Huan / Fang, Yangwang | Springer Verlag | 2023



    Improved Sine-cosine Algorithm for the Optimization Design of Truss Structures

    Zhou, Huanlin / Yang, Xiaomeng / Tao, Ran et al. | Springer Verlag | 2024


    Drone path planning

    ALDANA LOPEZ RODRIGO / CAMPOS MACIAS LEOBARDO / GOMEZ GUTIERREZ DAVID et al. | European Patent Office | 2020

    Free access