With the rapid development of economic globalization, waterway transportation plays an increasingly important role in international trade, and therefore the development of ship technology has become very urgent. To guarantee the safety and economy of ship navigation, one of the focal points of researchers’ research is how to plan a path that is both safe and reliable and smooth and gentle with a short range. Therefore, this study focuses on this scientific problem and proposes an improved fast extended random tree algorithm. The traditional fast extended random tree algorithm often suffers from the problem of planning a tortuous path because of its excessive randomness. To solve this problem, we consider the maneuvering performance requirements of the ship based on the traditional algorithm and introduce a sector sampling strategy to avoid large-angle steering, thus making the planned paths smoother and more feasible. To improve the search efficiency, we also design a target biasing strategy to improve the random point sampling mechanism by setting different sampling probabilities according to the distance from the random sampling point to the target point. Finally, we also propose an adaptive dynamic extension length strategy, which takes the extension length as a variable, and the extension length changes with the environment when the random tree is extended. Through simulation experiments, we demonstrate that the algorithm can reduce the path length while improving the search efficiency, and improve the path smoothness, which is more suitable for the actual navigation needs of ships’ vessels.


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    Titel :

    Research on ship path planning technology based on improved RRT algorithm


    Beteiligte:
    Chen, Ran (Autor:in) / Zhu, Yaping (Autor:in) / Liu, Jialun (Autor:in) / Huang, Yamin (Autor:in) / Wang, Xuming (Autor:in)


    Erscheinungsdatum :

    04.08.2023


    Format / Umfang :

    823975 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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