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Dynamic trajectory planning for unmanned ship under multi-object environment

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Abstract

Trajectory planning is one of the important technologies to ensure the safe navigation of the unmanned ship. This paper presents a dynamic path planning method based on the multi-layer Morphin adaptive search tree algorithm, which considers ship maneuverability, COLREGS, and good seamanship to harmonize the actions in the mixed traffic environment. First, the environment model is built according to the environment information of the rolling window; second, the feasible avoidance range of collision avoidance is calculated according to the velocity obstacle (VO) method. Finally, path optimization is carried out using the Morphin adaptive search tree algorithm. Through a case study and comparison with traditional artificial potential field (APF) models, the applicability and potential of the method are verified. This model can be applied to the autonomous navigation for unmanned ships as well as conventional manned ships and demonstrate good potential in smart ship**.

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Acknowledgements

The work presented in this study is financially supported by the National key research and development plan (2019YFB1600603), National Natural Science Foundation China (52071249), Transportation Science and Technology Project of Jiangsu Province (2018Z01), and Independent Innovation Fund for Graduate Students of the Wuhan University of Technology (2020-HY-A1-03).

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Authors and Affiliations

  1. School of Navigation, Wuhan University of Technology, Wuhan, China

    Mengxia Li, Junmin Mou, Yixiong He, ** Technology, Wuhan, China

    Mengxia Li, Junmin Mou, Yixiong He, **aohan Zhang, Qinqiong **e & Pengfei Chen

  2. Safety and Security Science Group, Faculty of Technology, Policy and Management, Delft University of Technology, Delft, The Netherlands

    Pengfei Chen

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  1. Mengxia Li
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  2. Junmin Mou
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  3. Yixiong He
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  5. Qinqiong **e
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  6. Pengfei Chen
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Correspondence to Pengfei Chen.

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Li, M., Mou, J., He, Y. et al. Dynamic trajectory planning for unmanned ship under multi-object environment. J Mar Sci Technol 27, 173–185 (2022). https://doi.org/10.1007/s00773-021-00825-x

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