Ship Motion

Ship motion research focuses on understanding and predicting vessel movements in various environments, aiming to improve navigation safety and efficiency. Current research heavily utilizes machine learning, particularly recurrent neural networks (like LSTMs) and transformers, to model complex ship dynamics and predict trajectories, often incorporating data from sources like Automatic Identification Systems (AIS) and onboard sensors. These advancements are crucial for autonomous navigation, particularly in challenging conditions like ice-covered waters or high sea states, and for enhancing maritime safety and operational efficiency through improved trajectory prediction and sea state estimation.