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Motion Control and Path Planning of Marine Vehicles—2nd Edition
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Motion Control and Path Planning of Marine Vehicles—2nd Edition

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: 1 May 2024 | Viewed by 5157

Special Issue Editors

Dr. Bowen Xing

E-Mail Website
Guest Editor
College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China
Interests: unmanned surface vehicles; ship motion control; path planning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Bing Li

E-Mail Website
Guest Editor
College of Intelligent System Science and Engineering, Harbin Engineering University, Harbin 150001, China
Interests: ship motion control; ship attitude control; servo control system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the motion control and path planning of marine vehicles. Recently, more and more kinds of marine vehicles have been designed and used to explore the world, promote economic growth and protect the environment. In order to ensure the implementation of these applications, the intelligence and energy-saving property indicators of their motion control and path planning policies should be satisfied at high levels.

This Special Issue is seeking high-quality original contributions, including technical papers that address the main research challenges related to the motion control and path planning of marine vehicles. Potential topics include, but are not limited to:

  • Modelling and control of vessels and unmanned marine vehicles;
  • Path planning of vessels and unmanned marine vehicles;
  • Navigation systems of vessels and unmanned marine vehicles;
  • Identification and estimation in vessels and unmanned marine vehicles;
  • Cooperative and coordinated control of vessels and unmanned marine vehicle swarms;
  • Multi-device collaborative operation of deep-sea mining systems;
  •  Ice-breaking operation of arctic vessel;
  • Unmanned marine vehicle swarm design and mission applications;
  • Other control and path planning applications in marine systems.

Articles from academia are welcome. This Special Issue aims to advance the field of motion control and the path planning of marine vehicles, as well as related fields.

Dr. Bowen Xing
Prof. Dr. Bing Li
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 vehicle
  • unmanned ocean vehicle
  • deep sea mining system
  • arctic vessel
  • unmanned marine vehicle swarm
  • motion control
  • path planning
  • autonomous
  • learning and AI
  • cooperation and coordination

Related Special Issue

Published Papers (7 papers)

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Research

22 pages, 3045 KiB  
Article
Trajectory Planning for Cooperative Double Unmanned Surface Vehicles Connected with a Floating Rope for Floating Garbage Cleaning
by Mengdi Zhang, Xiang Zheng, Jianhua Wang, Zijun Pan, Wenbo Che and Haozhu Wang
J. Mar. Sci. Eng. 2024, 12(5), 739; https://doi.org/10.3390/jmse12050739 (registering DOI) - 28 Apr 2024
Viewed by 234
Abstract
Double unmanned surface vehicles (DUSVs) towing a floating rope are more effective at removing large floating garbage on the water’s surface than a single USV. This paper proposes a comprehensive trajectory planner for DUSVs connected with a floating rope for cooperative water-surface garbage [...] Read more.
Double unmanned surface vehicles (DUSVs) towing a floating rope are more effective at removing large floating garbage on the water’s surface than a single USV. This paper proposes a comprehensive trajectory planner for DUSVs connected with a floating rope for cooperative water-surface garbage collection with dynamic collision avoidance, which takes into account the kinematic constraints and dynamic cooperation constraints of the DUSVs, which reflects the current collection capacity of DUSVs. The optimal travel sequence is determined by solving the TSP problem with an ant colony algorithm. The DUSVs approach the garbage targets based on the guidance of target key points selected by taking into account the dynamic cooperation constraints. An artificial potential field (APF) combined with a leader–follower strategy is adopted so that the each USV passes from different sides of the garbage to ensure garbage capturing. For dynamic obstacle avoidance, an improved APF (IAPF) combined with a leader–follower strategy is proposed, for which a velocity repulsion field is introduced to reduce travel distance. A fuzzy logic algorithm is adopted for adaptive adjustment of the desired velocities of the DUSVs to achieve better cooperation between the DUSVs. The simulation results verify the effectiveness of the algorithm of the proposed planner in that the generated trajectories for the DUSVs successfully realize cooperative garbage collection and dynamic obstacle avoidance while complying with the kinematic constraints and dynamic cooperation constraints of the DUSVs. Full article
(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles—2nd Edition)
26 pages, 825 KiB  
Article
Comparison of Linear and Nonlinear Model Predictive Control in Path Following of Underactuated Unmanned Surface Vehicles
by Wenhao Li, Xianxia Zhang, Yueying Wang and Songbo Xie
J. Mar. Sci. Eng. 2024, 12(4), 575; https://doi.org/10.3390/jmse12040575 - 28 Mar 2024
Viewed by 555
Abstract
Model predictive control (MPC), an extensively developed rolling optimization control method, is widely utilized in the industrial field. While some researchers have incorporated predictive control into underactuated unmanned surface vehicles (USVs), most of these approaches rely primarily on theoretical simulation research, emphasizing simulation [...] Read more.
Model predictive control (MPC), an extensively developed rolling optimization control method, is widely utilized in the industrial field. While some researchers have incorporated predictive control into underactuated unmanned surface vehicles (USVs), most of these approaches rely primarily on theoretical simulation research, emphasizing simulation outcomes. A noticeable gap exists regarding whether predictive control adequately aligns with the practical application conditions of underactuated USVs, particularly in addressing real-time challenges. This paper aims to fill this void by focusing on the application of MPC in the path following of USVs. Using the hydrodynamic model of USVs, we examine the details of both linear MPC (LMPC) and nonlinear MPC (NMPC). Several different paths are designed to compare and analyze the simulation results and time consumption. To address the real-time challenges of MPC, the calculation time under different solvers, CPUs, and programming languages is detailed through simulation. The results demonstrate that NMPC exhibits superior control accuracy and real-time control potential. Finally, we introduce an enhanced A* algorithm and use it to plan a global path. NMPC is then employed to follow that path, showing its effectiveness in tracking a common path. In contrast to some literature studies using the LMPC method to control underactuated USVs, this paper presents a different viewpoint based on a large number of simulation results, suggesting that LMPC is not fit for controlling underactuated USVs. Full article
(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles—2nd Edition)
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25 pages, 8386 KiB  
Article
An Optimal-Path-Planning Method for Unmanned Surface Vehicles Based on a Novel Group Intelligence Algorithm
by Shitu Chen, Ling Feng, Xuteng Bao, Zhe Jiang, Bowen Xing and Jingxiang Xu
J. Mar. Sci. Eng. 2024, 12(3), 477; https://doi.org/10.3390/jmse12030477 - 11 Mar 2024
Viewed by 813
Abstract
Path planning is crucial for unmanned surface vehicles (USVs) to navigate and avoid obstacles efficiently. This study evaluates and contrasts various USV path-planning algorithms, focusing on their effectiveness in dynamic obstacle avoidance, resistance to water currents, and path smoothness. Meanwhile, this research introduces [...] Read more.
Path planning is crucial for unmanned surface vehicles (USVs) to navigate and avoid obstacles efficiently. This study evaluates and contrasts various USV path-planning algorithms, focusing on their effectiveness in dynamic obstacle avoidance, resistance to water currents, and path smoothness. Meanwhile, this research introduces a novel collective intelligence algorithm tailored for two-dimensional environments, integrating dynamic obstacle avoidance and smooth path optimization. The approach tackles the global-path-planning challenge, specifically accounting for moving obstacles and current influences. The algorithm adeptly combines strategies for dynamic obstacle circumvention with an eight-directional current resistance approach, ensuring locally optimal paths that minimize the impact of currents on navigation. Additionally, advanced artificial bee colony algorithms were used during the research process to enhance the method and improve the smoothness of the generated path. Simulation results have verified the superiority of the algorithm in improving the quality of USV path planning. Compared with traditional bee colony algorithms, the improved algorithm increased the length of the optimization path by 8%, shortened the optimization time by 50%, and achieved almost 100% avoidance of dynamic obstacles. Full article
(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles—2nd Edition)
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14 pages, 4605 KiB  
Article
Dynamic Positioning Control of Large Ships in Rough Sea Based on an Improved Closed-Loop Gain Shaping Algorithm
by Chunyu Song, Teer Guo, Jianghua Sui and Xianku Zhang
J. Mar. Sci. Eng. 2024, 12(2), 351; https://doi.org/10.3390/jmse12020351 - 18 Feb 2024
Viewed by 648
Abstract
In order to solve the problem of the dynamic positioning control of large ships in rough sea and to meet the need for fixed-point operations, this paper proposes a dynamic positioning controller that can effectively achieve large ships’ fixed-point control during Level 9 [...] Read more.
In order to solve the problem of the dynamic positioning control of large ships in rough sea and to meet the need for fixed-point operations, this paper proposes a dynamic positioning controller that can effectively achieve large ships’ fixed-point control during Level 9 sea states (wind force Beaufort No. 10). To achieve a better control effect, a large ship’s forward motion is decoupled to establish a mathematical model of the headwind stationary state. Meanwhile, the closed-loop gain shaping algorithm is combined with the exact feedback linearization algorithm to design the speed controller and the course-keeping controller. This effectively solves the problem of strong external interferences impacting the control system in rough seas and guarantees the comprehensive index of robustness performance. In this paper, three large ships—the “Mariner”, “Taian kou”, and “Galaxy”—are selected as the research objects for simulation research and the final fixing error is less than 10 m. It is proven that the method is safe, feasible, practical, and effective, and provides technical support for the design and development of intelligent marine equipment for use in rough seas. Full article
(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles—2nd Edition)
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29 pages, 8927 KiB  
Article
Adaptive Finite-Time Backstepping Integral Sliding Mode Control of Three-Degree-of-Freedom Stabilized System for Ship Propulsion-Assisted Sail Based on the Inverse System Method
by Sheng Liu, Jian Song, Lanyong Zhang and Yinchao Tan
J. Mar. Sci. Eng. 2024, 12(2), 348; https://doi.org/10.3390/jmse12020348 - 17 Feb 2024
Viewed by 627
Abstract
The three-degree-of-freedom (3-DOF) stabilized control system for ship propulsion-assisted sails is used to control the 3-DOF motion of sails to obtain offshore wind energy. The attitude of the sail is adjusted to ensure optimal thrust along the target course. An adaptive finite-time backstepping [...] Read more.
The three-degree-of-freedom (3-DOF) stabilized control system for ship propulsion-assisted sails is used to control the 3-DOF motion of sails to obtain offshore wind energy. The attitude of the sail is adjusted to ensure optimal thrust along the target course. An adaptive finite-time backstepping integral sliding mode control based on the inverse system method (ABISMC-ISM) is presented for attitude tracking of the sail. Considering the nonlinear dynamics and strong coupling of the system, a decoupling strategy is established using the inverse system method (ISM). Constructing inverse dynamics to eliminate internal coupling, the system is transformed into independent pseudolinear subsystems. For the decoupled open-loop subsystems, an adaptive finite-time backstepping integral sliding mode control is designed to achieve closed-loop control. A backstepping-based integral sliding surface is proposed to eliminate the phase-reaching stage of the sliding surface. Considering the unmodelled dynamics and external disturbances, an adaptive extreme learning machine (AELM) was designed to estimate the disturbances. Furthermore, a sliding mode reaching law based on finite-time theory was employed to ensure that the system returns to the sliding surface in a finite time under chattering conditions. Experiments on a principle prototype demonstrate the effectiveness and energy-saving performance of the proposed method. Full article
(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles—2nd Edition)
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15 pages, 4548 KiB  
Article
Optimizing AUV Navigation Using Factor Graphs with Side-Scan Sonar Integration
by Lin Zhang, Yanbin Gao and Lianwu Guan
J. Mar. Sci. Eng. 2024, 12(2), 313; https://doi.org/10.3390/jmse12020313 - 10 Feb 2024
Viewed by 792
Abstract
For seabed mapping, the prevalence of autonomous underwater vehicles (AUVs) employing side-scan sonar (SSS) necessitates robust navigation solutions. However, the positioning errors of traditional strapdown inertial navigation system (SINS) and Doppler velocity log (DVL) systems accumulated significantly, further exacerbated by DVL’s susceptibility to [...] Read more.
For seabed mapping, the prevalence of autonomous underwater vehicles (AUVs) employing side-scan sonar (SSS) necessitates robust navigation solutions. However, the positioning errors of traditional strapdown inertial navigation system (SINS) and Doppler velocity log (DVL) systems accumulated significantly, further exacerbated by DVL’s susceptibility to failure in complex underwater conditions. This research proposes an integrated navigation approach that utilizes factor graph optimization (FGO) along with an improved pre-integration technique integrating SSS-derived position measurements. Firstly, the reliability of SSS image registration in the presence of strong noise and feature-poor environments is improved by replacing the feature-based methods with a Fourier-based method. Moreover, the high-precision inertial measurement unit (IMU) pre-integration method could correct the heading errors of SINS significantly by considering the Earth’s rotation. Finally, the AUV’s marine experimental results demonstrated that the proposed integration method not only offers improved SSS image registration and corrects initial heading discrepancies but also delivers greater system stability, particularly in instances of DVL data loss. Full article
(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles—2nd Edition)
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19 pages, 6346 KiB  
Article
Path-Following and Obstacle-Avoidance Control of USV Based on Finite-Distance Convergence
by Junbao Wei, Jianqiang Zhang, Zhong Liu, Jianjing Qu, Bowen Sui and Yuanyuan Zhang
J. Mar. Sci. Eng. 2024, 12(1), 34; https://doi.org/10.3390/jmse12010034 - 22 Dec 2023
Viewed by 759
Abstract
The control problem of avoidance-path-following is a critical consideration in the research of unmanned surface vehicle (USV) navigation control, and it holds great significance for the navigation safety of USVs. A guidance and control scheme based on finite-distance convergence is proposed in this [...] Read more.
The control problem of avoidance-path-following is a critical consideration in the research of unmanned surface vehicle (USV) navigation control, and it holds great significance for the navigation safety of USVs. A guidance and control scheme based on finite-distance convergence is proposed in this paper. First, the requirements for the USV to avoid obstacles from the perspective of path-following lateral error are analyzed. Then, a new performance function with finite-distance convergence is proposed to constrain the lateral error. Based on this, a heading guidance law and a backstepping controller are designed to ensure that the lateral error converges to a steady-state value within the prescribed navigation distance and that the stability is maintained, satisfying the requirements of obstacle avoidance for the USV. In addition, an adaptive velocity command is designed to adjust the velocity with the lateral error, which, to a certain extent, avoids the saturation of the heading actuator caused by the large lateral error. Finally, it is proven through theory and simulation that the control algorithm can guide the USV to achieve avoidance-path-following within a limited distance and to avoid obstacles effectively. Full article
(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles—2nd Edition)
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