Details
- Autor(en) / Beteiligte
- Titel
- Maritime Autonomous Vessels
- Ort / Verlag
- Basel: MDPI - Multidisciplinary Digital Publishing Institute
- Erscheinungsjahr
- 2023
- Quelle
- Alma/SFX Local Collection
- Beschreibungen/Notizen
- 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.
- Sprache
- Englisch
- Identifikatoren
- ISBN: 3036564144, 9783036564142, 9783036564159, 3036564152DOI: 10.3390/books978-3-0365-6414-2Titel-ID: cdi_oapen_doabooks_96694
- Format
- –
- Schlagworte
- artificial neural networks, artificial potential field, automatic identification system (AIS), autonomous underwater vehicle (AUV), AUV, Bayes, Book Industry Communication, buckling, clustering, collision avoidance, COLREGs, complex navigation conditions, convolutional neural network (CNN), coordinate referencing, cylindrical shell, design and optimization, dynamic navigation ship domain, dynamic obstacle avoidance, empirical formula, fishing vessel, free-running model tests, fuzzy adaptive, gaussian process, History of engineering & technology, homing and docking, human-operated ship, inspection of underwater object, LADRC, line-of-sight, local path planning, loss function, machine vision, maneuverability, manoeuvring model, maritime autonomous surface ships, MASS, model identification, model tests data, motion planning, multi-objective optimization, n/a, navigation, navigation situation, neural network, nonlinear autopilot, obstacle avoidance, parameter estimation, path planning, path-following, predetermined depth, prediction uncertainty, shallow water, ship classification, ship maneuvering model, ship target identification, ship’s manoeuvrability, singular values, stereo images, subsea production system (SPS), surrogate-model, system identification, target detection, target point/line planning and following, Technology, engineering, agriculture, Technology: general issues, testbed scenario, thrust allocation, track, trajectory image, trajectory tracking, truncated singular value decomposition, underactuated surface ship model, underwater glider, unmanned ship, unmanned surface vehicle, unmanned surface vehicles, variable stiffness, vector field, velocity obstacle algorithm, vision-based guidance, YOLOv5