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Advanced Research in Guidance, Navigation, and Control for Autonomous Surface...
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Advanced Research in Guidance, Navigation, and Control for Autonomous Surface Vehicle

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: closed (31 July 2025) | Viewed by 5248

Special Issue Editors

Dr. Cheng Liu

E-Mail Website
Guest Editor
College of Navigation, Dalian Maritime University, Dalian 116026, China
Interests: trajectory tracking; path following; collision avoidance; cooperative control; roll stabilization
Dr. Yaqing Shu

E-Mail Website
Guest Editor
School of Navigation, Wuhan University of Technology, Wuhan 430063, China
Interests: ship path planning; collision avoidance; arctic shipping; maritime traffic risk; ship pollution prevention
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Introducing a high level of autonomy to marine applications has become a pertinent topic across the globe. Autonomous surface vehicles (ASVs) are characterized by intelligence and flexibility; furthermore, the application of an ASV can increase efficiency and protect operators from danger. Guidance, navigation, and control are the key technologies for an ASV. This Special Issue seeks cutting-edge research about the guidance, navigation, and control of ASVs to satisfy the increasing need to perform more complex missions. The Special Issue includes, but is not limited to, the following topics:

  • Modeling and simulation technology for ASVs;
  • Advanced perception technology for ASVs;
  • The path planning method for ASVs;
  • The automatic berthing control method for ASVs;
  • The cooperative control method for ASVs;
  • Path following and roll reduction for ASVs;
  • The automatic collision avoidance for ASVs;
  • The guidance method for ASVs;
  • Navigation technology for ASVs.

Dr. Cheng Liu
Dr. Yaqing Shu
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

  • autonomous surface vehicle
  • mathematical modeling
  • navigation
  • path planning
  • berthing control
  • path following
  • cooperative control
  • collision avoidance
  • trajectory tracking

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Published Papers (7 papers)

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28 pages, 5003 KB  
Article
An Efficient Laser Point Cloud Registration Method for Autonomous Surface Vehicle
by Dongdong Guo, Qianfeng Jing, Yong Yin and Haitong Xu
J. Mar. Sci. Eng. 2025, 13(9), 1720; https://doi.org/10.3390/jmse13091720 - 5 Sep 2025
Abstract
In the field of Autonomous Surface Vehicle (ASV), research on advanced perception technologies is crucial for enhancing their intelligence and autonomy. In particular, laser point cloud registration technology serves as a foundation for improving the navigation accuracy and environmental awareness of ASV in [...] Read more.
In the field of Autonomous Surface Vehicle (ASV), research on advanced perception technologies is crucial for enhancing their intelligence and autonomy. In particular, laser point cloud registration technology serves as a foundation for improving the navigation accuracy and environmental awareness of ASV in complex environments. To address the issues of low computational efficiency, insufficient robustness, and incompatibility with low-power devices in laser point cloud registration technology for ASV, a novel point cloud matching method has been proposed. The proposed method includes laser point cloud data processing, feature extraction based on an improved Fast Point Feature Histogram (FPFH), followed by a two-step registration process using SAC-IA (Sample Consensus Initial Alignment) and Small_GICP (Small Generalized Iterative Closest Point). Registration experiments conducted on the KITTI benchmark dataset and the Pohang Canal dataset demonstrate that the relative translation error (RTE) of the proposed method is 16.41 cm, which is comparable to the performance of current state-of-the-art point cloud registration algorithms. Furthermore, deployment experiments on multiple low-power computing devices showcase the performance of the proposed method under low computational capabilities, providing reference metrics for engineering applications in the field of autonomous navigation and perception research for ASV. Full article
(This article belongs to the Special Issue Advanced Research in Guidance, Navigation, and Control for Autonomous Surface Vehicle)
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25 pages, 2843 KB  
Article
A CDC–ANFIS-Based Model for Assessing Ship Collision Risk in Autonomous Navigation
by Hee-Jin Lee and Ho Namgung
J. Mar. Sci. Eng. 2025, 13(8), 1492; https://doi.org/10.3390/jmse13081492 - 1 Aug 2025
Viewed by 309
Abstract
To improve collision risk prediction in high-traffic coastal waters and support real-time decision-making in maritime navigation, this study proposes a regional collision risk prediction system integrating the Computed Distance at Collision (CDC) method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Unlike Distance at [...] Read more.
To improve collision risk prediction in high-traffic coastal waters and support real-time decision-making in maritime navigation, this study proposes a regional collision risk prediction system integrating the Computed Distance at Collision (CDC) method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Unlike Distance at Closest Point of Approach (DCPA), which depends on the position of Global Positioning System (GPS) antennas, Computed Distance at Collision (CDC) directly reflects the actual hull shape and potential collision point. This enables a more realistic assessment of collision risk by accounting for the hull geometry and boundary conditions specific to different ship types. The system was designed and validated using ship motion simulations involving bulk and container ships across varying speeds and crossing angles. The CDC method was used to define collision, almost-collision, and near-collision situations based on geometric and hydrodynamic criteria. Subsequently, the FIS–CDC model was constructed using the ANFIS by learning patterns in collision time and distance under each condition. A total of four input variables—ship speed, crossing angle, remaining time, and remaining distance—were used to infer the collision risk index (CRI), allowing for a more nuanced and vessel-specific assessment than traditional CPA-based indicators. Simulation results show that the time to collision decreases with higher speeds and increases with wider crossing angles. The bulk carrier exhibited a wider collision-prone angle range and a greater sensitivity to speed changes than the container ship, highlighting differences in maneuverability and risk response. The proposed system demonstrated real-time applicability and accurate risk differentiation across scenarios. This research contributes to enhancing situational awareness and proactive risk mitigation in Maritime Autonomous Surface Ship (MASS) and Vessel Traffic System (VTS) environments. Future work will focus on real-time CDC optimization and extending the model to accommodate diverse ship types and encounter geometries. Full article
(This article belongs to the Special Issue Advanced Research in Guidance, Navigation, and Control for Autonomous Surface Vehicle)
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17 pages, 2420 KB  
Article
Hybrid Obstacle Avoidance Algorithm Based on IAPF and MPC for Underactuated Multi-USV Formation
by Hui Sun, Qing Xue, Mingyang Pan, Zongying Liu and Hangqi Li
J. Mar. Sci. Eng. 2025, 13(8), 1436; https://doi.org/10.3390/jmse13081436 - 27 Jul 2025
Viewed by 445
Abstract
In this paper, we propose a hybrid algorithm that integrates an improved artificial potential field method (IAPF), model predictive control (MPC), and an extended state observer (ESO) to address the obstacle avoidance problem in multi-unmanned surface vehicle (Multi-USV) formations, including both dynamic and [...] Read more.
In this paper, we propose a hybrid algorithm that integrates an improved artificial potential field method (IAPF), model predictive control (MPC), and an extended state observer (ESO) to address the obstacle avoidance problem in multi-unmanned surface vehicle (Multi-USV) formations, including both dynamic and static obstacles, as well as navigation through narrow waterways. Initially, the virtual structure method was applied for formation control. Next, the traditional potential field method was enhanced by employing a saturated attractive potential field and a partitioned repulsive potential field, which improve formation stability and obstacle avoidance accuracy in complex environments. The extended state observer was then employed to estimate and compensate for unknown system dynamics and external disturbances from the marine environment in real time, improving system robustness. On this basis, by leveraging the multi-step predictive optimization capabilities of model predictive control, the proposed algorithm dynamically adjusts control inputs based on the desired trajectories generated from potential field forces, which ensures the stability of formation control and effective obstacle avoidance. The simulation results demonstrate that the proposed algorithm effectively avoids both dynamic and static obstacles in multi-unmanned surface vehicle formations and enables successful navigation through narrow waterways by altering the formation. Full article
(This article belongs to the Special Issue Advanced Research in Guidance, Navigation, and Control for Autonomous Surface Vehicle)
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26 pages, 3018 KB  
Article
Trajectory Tracking Design of Autonomous Surface Vessels with Multiple Perturbations: A Robust Adaptive Fuzzy Approach
by Yung-Hsiang Chen, Sheng-Yan Pan and Yung-Yue Chen
J. Mar. Sci. Eng. 2025, 13(8), 1419; https://doi.org/10.3390/jmse13081419 - 25 Jul 2025
Viewed by 280
Abstract
To achieve robust trajectory tracking performance for autonomous surface vessels (ASVs), a robust adaptive fuzzy control (RAFC) scheme is proposed. The trajectory tracking problem of ASVs is addressed through a unified control framework that integrates a nonlinear controller with an adaptive fuzzy estimator. [...] Read more.
To achieve robust trajectory tracking performance for autonomous surface vessels (ASVs), a robust adaptive fuzzy control (RAFC) scheme is proposed. The trajectory tracking problem of ASVs is addressed through a unified control framework that integrates a nonlinear controller with an adaptive fuzzy estimator. In this framework, a nonlinear transformation is employed to first generate the trajectory tracking error dynamics, and then the adaptive fuzzy estimator is utilized to accurately estimate the effects of multiple ocean perturbations. This unified design ensures both robustness and high-precision trajectory tracking for the controlled ASVs. To validate the effectiveness of the proposed method, two challenging simulation scenarios are investigated. The simulation results demonstrate the superior control performance and robustness of the proposed approach. Full article
(This article belongs to the Special Issue Advanced Research in Guidance, Navigation, and Control for Autonomous Surface Vehicle)
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20 pages, 6056 KB  
Article
Inter-Element Phase Error Compensated Calibration Method for USBL Arrays
by Dejinxuan Zhang, Guangpu Zhang, Xu Zhao, Nan Zou, Jin Fu and Yuanxin Bai
J. Mar. Sci. Eng. 2025, 13(5), 877; https://doi.org/10.3390/jmse13050877 - 28 Apr 2025
Viewed by 390
Abstract
This study addresses the critical limitation of existing Ultra-Short Baseline (USBL) calibration algorithms in handling transducer positional errors and inter-element phase errors. We propose a novel positioning-calibration model based on vector projection theorem. The model achieves two key innovations: it eliminates the influence [...] Read more.
This study addresses the critical limitation of existing Ultra-Short Baseline (USBL) calibration algorithms in handling transducer positional errors and inter-element phase errors. We propose a novel positioning-calibration model based on vector projection theorem. The model achieves two key innovations: it eliminates the influence of inter-element positional errors through its structural design, and, for the first time, incorporates inter-element phase errors from acoustic array measurements as observational parameters to establish joint estimation equations for system installation angle errors and inter-element phase errors. The estimation process is implemented using an unscented Kalman filter (UKF). Simulation results demonstrate that the UKF outperforms the Gauss–Newton method (GNM), achieving estimation errors for installation angles and phase errors within 0.05°. Comparative evaluations confirm the model’s superiority over conventional calibration methods in accurately estimating installation angles under transducer positional errors. Field experiments further validate the algorithm’s effectiveness in real-world marine environments, successfully estimating system installation angle errors and inter-element phase errors to enhance final target positioning accuracy. This approach provides a practical solution to persistent calibration challenges in USBL systems. Full article
(This article belongs to the Special Issue Advanced Research in Guidance, Navigation, and Control for Autonomous Surface Vehicle)
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19 pages, 1464 KB  
Article
Simplified Model Characterization and Control of an Unmanned Surface Vehicle
by Aldo Lovo-Ayala, Roosvel Soto-Diaz, Carlos Andres Gutierrez-Martinez, Jose Fernando Jimenez-Vargas, Javier Jiménez-Cabas and Jose Escorcía-Gutierrez
J. Mar. Sci. Eng. 2025, 13(4), 813; https://doi.org/10.3390/jmse13040813 - 18 Apr 2025
Viewed by 857
Abstract
This study presents the modeling and control of the unmanned surface vehicle (USV) SABALO. Two models were built, one based on a transfer function matrix and another based on state variables, and from these models, two control strategies were developed. The first strategy [...] Read more.
This study presents the modeling and control of the unmanned surface vehicle (USV) SABALO. Two models were built, one based on a transfer function matrix and another based on state variables, and from these models, two control strategies were developed. The first strategy is based on independent Proportional-Integral/Proportional-Derivative (PI/PD) controllers complemented by a decoupling system, and the second strategy is based on state variable feedback. The two control strategies were evaluated and contrasted. Results demonstrated that the decoupler effectively eliminated variable interaction, enhancing stability in straight trajectories and directional changes. Meanwhile, state feedback control demonstrated markedly faster response times and superior precision, accompanied by higher energy consumption. The study concludes that both strategies are effective, but their suitability depends on the mission. The decoupler could be ideal for energy-efficient, long-duration operations, while state feedback could be appropriate for dynamic environments requiring rapid maneuvers. Full article
(This article belongs to the Special Issue Advanced Research in Guidance, Navigation, and Control for Autonomous Surface Vehicle)
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22 pages, 12220 KB  
Article
Prescribed-Time Formation Tracking Control for Underactuated USVs with Prescribed Performance
by Bowen Sui, Jianqiang Zhang and Zhong Liu
J. Mar. Sci. Eng. 2025, 13(3), 480; https://doi.org/10.3390/jmse13030480 - 28 Feb 2025
Cited by 1 | Viewed by 727
Abstract
This article proposes a prescribed-time formation tracking control scheme for USVs with prescribed performance constraints to address the issue of multiple underactuated USV formation tracking control with external environmental disturbances and input saturation. Initially, a prescribed-time extended state observer was constructed, capable of [...] Read more.
This article proposes a prescribed-time formation tracking control scheme for USVs with prescribed performance constraints to address the issue of multiple underactuated USV formation tracking control with external environmental disturbances and input saturation. Initially, a prescribed-time extended state observer was constructed, capable of promptly estimating and compensating for speed and external disturbances within a certain timeframe. Additionally, a unique performance function was developed, enabling the performance function to converge to a predetermined accuracy within a specified time, while allowing for flexible adjustment of the performance constraint shape by parameter modification. Furthermore, a prescribed-time formation control algorithm was developed by combining graph theory and dynamic surface control, enabling the formation error to converge within preset performance constraints at a specified period of T=10 s. It was proved that all signals in the closed-loop system are uniform, ultimately bounded by Lyapunov stability theory and the formation tracking errors display prescribed-time stability. Finally, the efficacy and superiority of the designed control scheme were evaluated by constructing numerical simulations. Full article
(This article belongs to the Special Issue Advanced Research in Guidance, Navigation, and Control for Autonomous Surface Vehicle)
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