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New Technologies in Autonomous Ship Navigation
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New Technologies in Autonomous Ship Navigation

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: 20 February 2026 | Viewed by 399

Special Issue Editors

Dr. Jiqiang Li

E-Mail Website
Guest Editor
Navigation College, Dalian Maritime University, Dalian 116026, China
Interests: marine vehicles; path following; robust control; guidance; nonlinear control; cooperative control; USV-UAV
Prof. Dr. Guoqing Zhang

E-Mail Website
Guest Editor
Navigation College, Dalian Maritime University, Dalian 116026, China
Interests: ship motion prediction; wireless marine communication; intelligent transportation systems; global maritime distress and safety systems
Special Issues, Collections and Topics in MDPI journals
Dr. Antonio M. Pascoal

E-Mail Website
Guest Editor
Dynamical Systems and Ocean Robotics Lab, University of Lisbon, Lisbon, Portugal
Interests: cooperative control of marine vehicles; path following control; adaptive control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Weidong Zhang

E-Mail Website
Guest Editor
Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: marine vehicles; robust control; intelligent control; guidance; nonlinear control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advancements have propelled autonomous ship navigation to the forefront of maritime innovation driven by challenging operational demands in global shipping, along with growing requirements for enhanced safety and efficiency. Significant progress in sensor fusion and actuation systems, artificial intelligence, and connectivity now enables vessels to perceive complex environments, make real-time decisions, and execute precise maneuvers with minimal human intervention. This Special Issue aims to integrate cutting-edge developments such as next-generation methods and systems for enhanced perception and situational awareness, AI-driven collision avoidance, adaptive path planning, multi-vessel operations, cross-domain collaboration, and resilient communication architectures. The purpose of this Special Issue in the Journal of Marine Science and Engineering is to present pioneering research and engineering solutions advancing the reliability and intelligence of autonomous maritime operation. Topics of interest include, but are not limited to, the following: marine surface vehicles, sensor-fusion navigation technology, autonomous ship navigation, optimal path planning, dynamic positioning, and intelligent control for multiple vehicles.

Dr. Jiqiang Li
Prof. Dr. Guoqing Zhang
Dr. Antonio M. Pascoal
Prof. Dr. Weidong Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • marine surface vehicles
  • sensor-fusion navigation technology
  • autonomous ship navigation
  • optimal path planning
  • dynamic positioning
  • cooperative control
  • intelligent control for multiple vehicles

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Published Papers (2 papers)

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Research

25 pages, 1904 KB  
Article
Integrated LiDAR-Based Localization and Navigable Region Detection for Autonomous Berthing of Unmanned Surface Vessels
by Haichao Wang, Yong Yin, Liangxiong Dong and Helang Lai
J. Mar. Sci. Eng. 2025, 13(11), 2079; https://doi.org/10.3390/jmse13112079 (registering DOI) - 31 Oct 2025
Abstract
Autonomous berthing of unmanned surface vehicles (USVs) requires high-precision positioning and accurate detection of navigable region in complex port environments. This paper presents an integrated LiDAR-based approach to address these challenges. A high-precision 3D point cloud map of the berth is first constructed [...] Read more.
Autonomous berthing of unmanned surface vehicles (USVs) requires high-precision positioning and accurate detection of navigable region in complex port environments. This paper presents an integrated LiDAR-based approach to address these challenges. A high-precision 3D point cloud map of the berth is first constructed by fusing LiDAR data with real-time kinematic (RTK) measurements. USV pose is then estimated by matching real-time LiDAR scans to the prior map, achieving robust, RTK-independent localization. For safe navigation, a novel navigable region detection algorithm is proposed, which combines point cloud projection, inner-boundary extraction, and target clustering. This method accurately identifies quay walls and obstacles, generating reliable navigable areas and ensuring collision-free berthing. Field experiments conducted in Ling Shui Port, Dalian, China, validate the proposed approach. Results show that the map-based positioning reduces absolute trajectory error (ATE) by 55.29% and relative trajectory error (RTE) by 38.71% compared to scan matching, while the navigable region detection algorithm provides precise and stable navigable regions. These outcomes demonstrate the effectiveness and practical applicability of the proposed method for autonomous USV berthing. Full article
(This article belongs to the Special Issue New Technologies in Autonomous Ship Navigation)
25 pages, 2727 KB  
Article
Berthing State Estimation for Autonomous Surface Vessels Using Ship-Based 3D LiDAR
by Haichao Wang, Yong Yin, Qianfeng Jing and Chen-Liang Zhang
J. Mar. Sci. Eng. 2025, 13(10), 1975; https://doi.org/10.3390/jmse13101975 - 15 Oct 2025
Viewed by 223
Abstract
Automated berthing remains a critical challenge for autonomous surface vessels (ASVs), necessitating precise berthing state estimation as a fundamental prerequisite. In this paper, we present a novel berthing state estimation method tailored for ASVs and based on 3D LiDAR technology. Firstly, a berthing [...] Read more.
Automated berthing remains a critical challenge for autonomous surface vessels (ASVs), necessitating precise berthing state estimation as a fundamental prerequisite. In this paper, we present a novel berthing state estimation method tailored for ASVs and based on 3D LiDAR technology. Firstly, a berthing plane acquisition scheme based on point cloud plane fitting is proposed; the feasibility of the scheme was verified by experiments. The point cloud registration algorithm was used to realize the ship pose estimation. Before registration, the preprocessing technology was used to filter out the noise and outliers in the point cloud data to improve the accuracy of pose estimation. A detailed method for calculating the berthing state information is proposed. This method considers the influence of ship roll, pitch, and yaw during berthing, and ensures the accuracy of the obtained state information. Finally, a real-time ship berthing perception framework was constructed using the Robot Operating System (ROS), enabling the continuous output of vital berthing state information, including berthing distance, velocity, approaching angle, and yaw rate, at a frequency of 10 Hz. To validate the effectiveness of our algorithm, extensive real ship experiments were conducted, yielding highly promising results. The average angle error was found to be less than 0.26°, with an average distance error below 0.023 m. Full article
(This article belongs to the Special Issue New Technologies in Autonomous Ship Navigation)
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