In scenarios such as inland rivers, automatic navigation for marine vessels is becoming more and more important. To improve the effect of automatic navigation, a visual navigation method based on machine learning for vessels is designed, and simulation validation is conducted. Firstly, vessel images are captured by using visual sensing technology. A semantic segmentation model is employed to separate the shoreline from the water region and identify the shoreline. Secondly, based on the identified shoreline, a reference anchor point is set for the vessel’s navigation. The vessel’s automatic navigation is achieved through a control algorithm. Finally, the proposed visual navigation method is validated through a simulation platform. Simulation experiments have shown that in simple inland waterway scenarios, the proposed method enables autonomous navigation of the vessel.


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    Title :

    Visual Navigation Method and Simulation Validation


    Contributors:
    He, Yi (author) / Ma, Feng (author)


    Publication date :

    2023-08-04


    Size :

    616127 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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