With an increasing interest in the deployment of unmanned surface vehicles (USVs) to support complex ocean operations, high‐speed USVs (≥40 knots) have become an important option, especially in accomplishing demanding tasks such as coastal guarding. At present, there is a vast amount of studies focusing on the development of USVs' autonomous navigation systems, and the results of most of them have only been verified by simulations or demonstrations on low‐speed experimental USVs (≤20 knots). It remains unclear how high‐speed USVs would perform in real applications. In particular, when USVs are navigating at high‐speed, reliable obstacle detections and robust motion control become increasingly difficult to achieve than in normal conditions. This paper therefore presents a new autonomous navigation system for high‐speed USVs with the system software and hardware been designed on the basis for ensuring a safe and reliable operation. Within such a system, a collision avoidance algorithm based on velocity obstacle able to adjust the USV's heading and speed in real‐time has been integrated. A local environment modelling method and a heading maintain method by considering Coast Guard International Regulations for Avoiding Collision at Sea are proposed to improve the reliability and stability of the system. The effectiveness and efficiency of the proposed system has been verified and validated by hardware‐in‐the‐loop simulation tests and sea trials on a high‐speed USV (“Tianxing No. 1”) in practical maritime environments. Results show that the autonomous navigation system adapts to the characteristics of high‐speed USVs and can guide high‐speed USVs (≥40 knots) in realising a safe autonomous navigation, which significantly improves the USV's autonomy level.


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    Titel :

    Navigating high‐speed unmanned surface vehicles: System approach and validations


    Beteiligte:
    Zhuang, J (Autor:in) / Zhang, L (Autor:in) / Wang, B (Autor:in) / Su, Y (Autor:in) / Hanbing, S (Autor:in) / Liu, Y (Autor:in) / Bucknall, R (Autor:in)

    Erscheinungsdatum :

    2021-06-01


    Anmerkungen:

    Journal of Field Robotics , 38 (4) pp. 619-652. (2021)


    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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