Reprint

Maritime Autonomous Surface Ships

Edited by
July 2024
238 pages
  • ISBN978-3-7258-1532-6 (Hardback)
  • ISBN978-3-7258-1531-9 (PDF)

This is a Reprint of the Special Issue Maritime Autonomous Surface Ships that was published in

Engineering
Environmental & Earth Sciences
Summary

The maritime industry faces many pressing challenges due to increasing environmental and safety concerns. In light of these challenges, autonomous ships can provide potential solutions to addressing smart shipping, fuel efficiency, and safety issues. The development of marine autonomy technology will significantly improve the situation and is expected to become a cost-efficient alternative to conventional ships. Currently, automated shipping technology is rapidly transitioning from theoretical to practical applications as the number and scope of autonomous ship prototypes increase around the globe. These prototypes are widely used in both navy and commercial applications, such as ocean observation, coast patrols, underwater monitoring, and underwater production system operation. This reprint is a printed edition of the Special Issue on “Maritime Autonomous Surface Ships” that was published in the Journal of Marine Science and Engineering. It contains an editorial and 10 peer-reviewed research papers in the field of maritime ships, and the following topics are included in this book: ship control methods, collision avoidance, ship detection methods, and manoeuvring models and digital twin (DT) technology. The main goal of this reprint is to address key challenges, thereby promoting research on marine autonomous ships.

Format
  • Hardback
License and Copyright
© 2024 by the authors; CC BY-NC-ND license
Keywords
digital twin; digitalization; smart shipping; autonomous surface vehicles; citespace; scientometric analysis; anti-vertical motion; model test; T-foil; control method; attitude estimation; light detection and ranging; point cloud feature extraction; improved random sample consensus; data-driven; parameter estimation; large-scale training set; truncated LS-SVM; shallow water; machine learning; artificial intelligence; synthetic aperture radar; ship detection; autonomous ships; collision risk situation; graph-based model; validation scenario; MASS; multi-ship autonomous collision avoidance decision-making; data-driven; MADRL; heterogeneous formation control system; UAV-USVs; extended state observer; collision avoidance; artificial potential field method; multi-USV systems; formation-containment tracking control; quadratic programming; collision avoidance; control barrier function; dual-layer scheme; fault-tolerant control; guaranteed performance; model uncertainties; autonomous surface vehicle; active fault-tolerant control; n/a