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Manoeuvring in shallow and confined water with model predictive track controllers
In: Journal of Physics: Conference Series. IOP Publishing: Bristol. ISSN 1742-6588; e-ISSN 1742-6596, meer
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| Beschikbaar in | Auteurs |
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Documenttype: Congresbijdrage
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| Trefwoorden |
Harbours and waterways > Manoeuvring behaviour > Autonomous navigation
Simulations
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| Abstract |
Autonomous and computer-assisted navigation, for example through portable pilot units and data-driven decision supportive systems, is in full development. Remote-controlled vessels (manned but without a captain steering continuously on board) are used in Belgium (by Seafar in inland shipping) but also in other countries. A model predictive controller has been used to investigate environmental and operational parameters for the passage of the river Seine in Paris by different ship types. These fast-time simulations have been compared with simulations in real time executed by skippers on a ship manoeuvring simulator or measured real life tracks. A good predictability of the real situation requires accurate manoeuvring models. But what if this accuracy cannot be guaranteed? An illustration is made by comparing the tracks if, in the prescience prediction phase for the controller, wind or bank effects are neglected or doubled. The development of model predictive deep reinforcement learning control algorithms for navigation will be one of the challenges of the Data-driven Smart Shipping project that started May 2024. |
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