This article presents a new algorithm for short-term maritime collision avoidance (COLAV) named the branching-course MPC (BC-MPC) algorithm. The algorithm is designed to be robust with respect to noise on obstacle estimates, which is a significant source of disturbance when using exteroceptive sensors such as e.g. radars for obstacle detection and tracking. Exteroceptive sensors do not require vessel-to-vessel communication, which enables COLAV toward vessels not equipped with e.g. automatic identification system (AIS) transponders, in addition to increasing the robustness with respect to faulty information which may be provided by other vessels. The BC-MPC algorithm is compliant with rules 8 and 17 of the International Regulations for Preventing Collisions at Sea (COLREGs), and favors maneuvers following rules 13-15. This results in a COLREGs-aware algorithm which can ignore rules 13-15 when necessary. The algorithm is experimentally validated in several full-scale experiments in the Trondheimsfjord in 2017 using a radar-based system for obstacle detection and tracking. The COLAV experiments show good performance in compliance with the desired algorithm behavior.

中文翻译：

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海上避碰分支航向模型预测控制算法

本文提出了一种新的短期海上避碰 (COLAV) 算法，称为分支路线 MPC (BC-MPC) 算法。该算法被设计为对于障碍物估计的噪声具有鲁棒性，当使用外感受传感器例如用于障碍物检测和跟踪的雷达时，这是一个重要的干扰源。外感传感器不需要船对船的通信，这使得 COLAV 能够针对未配备例如自动识别系统 (AIS) 转发器的船只，此外还增加了针对其他船只可能提供的错误信息的鲁棒性。BC-MPC 算法符合《国际海上避碰规则》(COLREGs) 的第 8 条和第 17 条，并有利于遵循规则 13-15 的机动。这会导致 COLREGs-aware 算法在必要时可以忽略规则 13-15。该算法于 2017 年在特隆赫姆峡湾的几次全面实验中得到了实验验证，使用基于雷达的系统进行障碍物检测和跟踪。COLAV 实验显示出符合所需算法行为的良好性能。