  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.
