Method for collision avoidance based on deep reinforcement learning with path-speed control for an autonomous ship

In this paper, we propose a collision avoidance method based on deep reinforcement learning (DRL) that simultaneously controls the path and speed of a ship. The DRL is actively applied in machine control and artificial intelligence. To verify the proposed method, we applied it to the Imazu problem....

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Autors principals:	Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, Donghun Yu
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2024-01-01
Col·lecció:	International Journal of Naval Architecture and Ocean Engineering
Matèries:	Collision avoidance Collision risk COLREGs Deep reinforcement learning Autonomous ship
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S2092678223000687
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