Trajectory planning for Service Ship during emergency STS transfer operation

A review of ship collision risk assessment, hotspot detection and path planning for maritime traffic control in restricted waters

“…The static collision-avoidance-based ship path planning problems ensure the avoidance of a collision with any stable obstacles, such as an island, buoys, shallows, rocks and fishing nets. It can be solved by the traditional algorithms including a spatial structural model, approaches based on raster grids, the lineof-sight method and the potential field approach, as well as artificial intelligence-based algorithms and simulations such as particle swarm, evolutionary, neural networks and fuzzy logic, as stated by Yan et al (2009), Tsou and Hsueh (2010), Szłapczyński (2012), Chen et al (2016), Kolendo and Śmierzchalski (2016), Deng et al (2017), Hinostroza et al (2017), Witkowska et al (2017), Zhou et al (2017), Wang et al (2018b) and Tang et al (2019).…”

Comparison of Discrete Artificial Potential Field Algorithm and Wave-Front Algorithm for Autonomous Ship Trajectory Planning

“…In marine applications recently introduced path planning methods are, i.a., an A* algorithm based approach [16], Fuzzy Sets and Game Theory methods [17], the Beam Search Algorithm (BSA) [18] and an evolutionary algorithm (EA) approach for ship collision avoidance [19]- [22], a reinforcement learning approach for maritime autonomous surface ships path planning (MASS) [23] and a trajectory planning approach for emergency ship to ship (STS) transfer operation [24]. Other promising methods for ship's trajectory planning include the Fuzzy logic (FL) based approach [25], [26], the Artificial Potential Field (APF) and the Modified Artificial Potential Field (MAPF) methods [27], [28], the Cooperative Path Planning (CPP) algorithm [29] and an approach based upon the Particle Swarm Optimization (PSO) method [30].…”