A path planning method for navigation experiment of Mars exploration is proposed. In this experiment, a cognitive navigation application is designed to research the working pattern of our Radiator-based Artificial Landmark Navigation (RALN) technique; and a path planning method is used to make the pre-set exploration path of this experiment. Regarding the path planning method, first, a series of threat sources, such as the harmful gas, windy weather, and uphill, are simulated. Second, a Sin-Cos Particle Swarm Optimization (SCPSO) method is developed. Third, both the threat sources and the SCPSO are considered to solve the optimal computation of path planning in the navigation experiment. Many experiment results have shown: compared with classic Particle Swarm Optimization (PSO) the mean fitness function of SCPSO can be improved almost 10.0 when the iteration time is 100; and the processing time only increases about 3.0 s.


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    Titel :

    Optimal 3D Path Planning Using SCPSO for Cognitive Navigation Application


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Long, Shengzhao (Herausgeber:in) / Dhillon, Balbir S. (Herausgeber:in) / Liu, Haoting (Autor:in) / Xiong, Tao (Autor:in) / Wang, Mengmeng (Autor:in) / Liu, Fang (Autor:in) / Li, Qing (Autor:in)

    Kongress:

    International Conference on Man-Machine-Environment System Engineering ; 2023 ; Beijing, China October 20, 2023 - October 23, 2023



    Erscheinungsdatum :

    05.09.2023


    Format / Umfang :

    7 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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