Maritime Autonomous Vessels

doi:10.3390/books978-3-0365-6414-2

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Maritime Autonomous Vessels

Edited by

January 2023

332 pages

ISBN978-3-0365-6415-9 (Hardback)
ISBN978-3-0365-6414-2 (PDF)

https://doi.org/10.3390/books978-3-0365-6414-2

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This book is a reprint of the Special Issue Maritime Autonomous Vessels that was published in

Engineering

Environmental & Earth Sciences

Summary

This reprint is a printed edition of the Special Issue on Maritime Autonomous Vessels that was published in the Journal of Marine Science and Engineering. It contains an editorial and 17 peer-reviewed research studies in the field of Maritime Autonomous Surface Ships (MASS), Unmanned Surface Vessels (USVs), Autonomous Underwater Vehicles (AUVs), and underwater gliders, to name a few. The main goal of this reprint is to address key challenges, thereby promoting research on marine autonomous ships. There are many topics on autonomous vessels involved in this reprint, for instance, automatic control, manoeuvrability, collision avoidance, ship target identification, motion planning, and buckling analysis.

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Hardback

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Keywords

cylindrical shell; variable stiffness; buckling; design and optimization; AUV; surrogate-model; path-following; vector field; obstacle avoidance; velocity obstacle algorithm; nonlinear autopilot; underactuated surface ship model; underwater glider; predetermined depth; fuzzy adaptive; LADRC; system identification; ship maneuvering model; gaussian process; prediction uncertainty; unmanned surface vehicles; dynamic obstacle avoidance; dynamic navigation ship domain; local path planning; COLREGs; AUV; homing and docking; vision-based guidance; target point/line planning and following; thrust allocation; machine vision; target detection; YOLOv5; loss function; unmanned ship; autonomous underwater vehicle (AUV); subsea production system (SPS); inspection of underwater object; stereo images; navigation; coordinate referencing; trajectory tracking; unmanned surface vehicle; model identification; line-of-sight; motion planning; MASS; multi-objective optimization; complex navigation conditions; manoeuvring model; parameter estimation; singular values; free-running model tests; truncated singular value decomposition; fishing vessel; shallow water; maneuverability; empirical formula; navigation situation; human-operated ship; MASS; clustering; testbed scenario; artificial potential field; collision avoidance; maritime autonomous surface ships; path planning; ship classification; automatic identification system (AIS); convolutional neural network (CNN); trajectory image; ship target identification; track; neural network; Bayes; ship’s manoeuvrability; model tests data; artificial neural networks; n/a