Maritime Autonomous Vessels

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 March 2022) | Viewed by 51329

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Special Issue Editors

Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal
Interests: autonomous ships; guidance navigation and control; nonlinear control; ship manoeuvering model; system identification method; full-scale trials and model tests
Special Issues, Collections and Topics in MDPI journals
Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal
Interests: autonomous vehicles; guidance, navigation and control; ship dynamics; artificial intelligence in maritime applications
Special Issues, Collections and Topics in MDPI journals
Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal
Interests: marine environment; ship dynamics; marine structures; safety and reliability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent years have seen the rapid development of autonomous ships. The maritime industry is currently experiencing a disruptive change in technology through the increased development of advanced autonomy technologies leading to Maritime Autonomous Surface Ships (MASS), Unmanned Surface Vessels(USVs), Autonomous Underwater Vehicles (AUVs), underwater gliders, just to name a few. Automated vessel technology is rapidly transiting from the theoretical to the practical applications as the number and scope of unmanned vessels or autonomous ship projects increase around the globe. They have been widely used both in navy applications and even some commercial applications such as marine survey, coast patrol, inspection and operation of underwater production system. The most important reasons for the rapid development of autonomous vessels are safety concerns and economic benefit. Maritime accidents cause the loss of human lives, damage to the environment, and loss in the economy. The development towards autonomous marine ships will improve the situation greatly and are expected to become a cost-efficient alternative to conventional ships, improving the safety and environmental impact at sea.

The main goal of this special issue is to address the key challenges, thereby promoting research on marine autonomous ships. Topics of interest of this special issue include, but are not limited to, the following aspects:

  • Intelligent and autonomous marine ships
  • Mathematical models for marine ships
  • AIS data analysis
  • Maritime safety and risk assessment for autonomous ships and respective regulations
  • Guidance, navigation and Control system design and applications
  • Path following, path planning, trajectory planning and automatic collison avoidace for marine ships
  • Machine learning methods (Least square, Regularization methods, Neural Networks, Kalman filter, SVM, etc.) and its application in marine autonomous ships
  • Measurements and experiments in relationship to the behaviour of ships
  • Sea trials and ship model tests
  • Data Acquisition system and multi-sensor data fusion
  • Multi-objective optimization design (evolutionary opt., swarm opt.)
  • Applications of autonomous vessles (MASS, ROVs, AUVs, USVs, underwater gliders, etc.) in environmental monitoring, mapping and surveillance, search and rescuing operations, habitat mapping, marine biology and geology, hydrographic explorations
  • Automatic berthing and unberthing
  • Automated onboard systems
Dr. Haitong Xu
Dr. Lúcia Moreira
Dr. Carlos Guedes Soares
Guest Editors

Manuscript Submission Information

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Keywords

  • ship dynamics
  • guidance, navigation and control systems
  • seakeeping model
  • machine learning methods
  • safety and risk
  • ship model tests
  • captive model test
  • autonomous maritime vessles
  • automatic collision avoidance
  • path planning
  • automated onboard systems

Published Papers (18 papers)

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Editorial

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3 pages, 204 KiB  
Editorial
Maritime Autonomous Vessels
by Haitong Xu, Lúcia Moreira and C. Guedes Soares
J. Mar. Sci. Eng. 2023, 11(1), 168; https://doi.org/10.3390/jmse11010168 - 10 Jan 2023
Cited by 4 | Viewed by 2130
Abstract
Recent years have seen the rapid development of autonomous ships [...] Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)

Research

Jump to: Editorial

15 pages, 4116 KiB  
Article
Simulating Ship Manoeuvrability with Artificial Neural Networks Trained by a Short Noisy Data Set
by Lúcia Moreira and C. Guedes Soares
J. Mar. Sci. Eng. 2023, 11(1), 15; https://doi.org/10.3390/jmse11010015 - 22 Dec 2022
Cited by 4 | Viewed by 1857
Abstract
Artificial neural networks are applied to model the manoeuvrability characteristics of a ship based on empirical information acquired from experiments with a scaled model. This work aims to evaluate the performance of the proposed method of training the artificial neural network model even [...] Read more.
Artificial neural networks are applied to model the manoeuvrability characteristics of a ship based on empirical information acquired from experiments with a scaled model. This work aims to evaluate the performance of the proposed method of training the artificial neural network model even with a very small quantity of noisy data. The data used for the training consisted of zig-zag and circle manoeuvres carried out in agreement with the IMO standards. The wind effect is evident in some of the recorded experiments, creating additional disturbance to the fitting scheme. The method used for the training of the network is the Levenberg–Marquardt algorithm, and the results are compared with the scaled conjugate gradient method and the Bayesian regularization. The results obtained with the different methodologies show very suitable accuracy in the prediction of the referred manoeuvres. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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17 pages, 3098 KiB  
Article
Ship Target Identification via Bayesian-Transformer Neural Network
by Zhan Kong, Yaqi Cui, Wei Xiong, Fucheng Yang, Zhenyu Xiong and Pingliang Xu
J. Mar. Sci. Eng. 2022, 10(5), 577; https://doi.org/10.3390/jmse10050577 - 24 Apr 2022
Cited by 7 | Viewed by 2134
Abstract
Ship target identification is of great significance in both military and civilian fields. Many methods have been proposed to identify the targets using tracks information. However, most of existing studies can only identify two or three types of targets, and the accuracy of [...] Read more.
Ship target identification is of great significance in both military and civilian fields. Many methods have been proposed to identify the targets using tracks information. However, most of existing studies can only identify two or three types of targets, and the accuracy of identification needs to be further improved. Meanwhile, they do not provide a reliable probability of the identification result under a high-noise environment. To address these issues, a Bayesian-Transformer Neural Network (BTNN) is proposed to complete the ship target identification task using tracks information. The aim of the research is improving the ability of ship target identification to enhance the maritime situation awareness and strengthen the protection of maritime traffic safety. Firstly, a Bayesian-Transformer Encoder (BTE) module that contains four different Bayesian-Transformer Encoders is used to extract discriminate features of tracks. Then, a Bayesian fully connected layer and a SoftMax layer complete the classification. Benefiting from the superiority of the Bayesian neural network, BTNN can provide a reliable probability of the result, which captures both aleatoric uncertainty and epistemic uncertainty. The experiments show that the proposed method can successfully identify nine types of ship targets. Compared with traditional methods, the identification accuracy of BTNN increases by 3.8% from 90.16%. In addition, compared with non-Bayesian Transformer Neural Network, the BTNN can provide a more reliable probability of the identification result under a high-noise environment. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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21 pages, 7669 KiB  
Article
Ship Type Recognition Based on Ship Navigating Trajectory and Convolutional Neural Network
by Tianyu Yang, Xin Wang and Zhengjiang Liu
J. Mar. Sci. Eng. 2022, 10(1), 84; https://doi.org/10.3390/jmse10010084 - 10 Jan 2022
Cited by 10 | Viewed by 2067
Abstract
With the aim to solve the problem of missing or tampering of ship type information in AIS information, in this paper, a novel ship type recognition scheme based on ship navigating trajectory and convolutional neural network (CNN) is proposed. Firstly, according to speed [...] Read more.
With the aim to solve the problem of missing or tampering of ship type information in AIS information, in this paper, a novel ship type recognition scheme based on ship navigating trajectory and convolutional neural network (CNN) is proposed. Firstly, according to speed and acceleration of the ship, three ship navigating situations, i.e., static, normal navigation and maneuvering, are integrated into the process of trajectory images generation in the form of pixels. Then, three kinds of modular network structures with different depths are trained and optimized to determine the appropriate convolutional neural network structure. In the validation phase of the model, a large amount of verified data with a time span of one month was used, covering a variety of water conditions including open water, ports, rivers and lakes. Following this approach, a kind of CNN scheme which can be directly used to identify ship types in a wide range of waters is proposed. This scheme can be used to judge the ship type when the static information is completely missing and to test the data when the ship type information is partially missing. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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20 pages, 7043 KiB  
Article
An Efficient Ship Automatic Collision Avoidance Method Based on Modified Artificial Potential Field
by Zhongxian Zhu, Hongguang Lyu, Jundong Zhang and Yong Yin
J. Mar. Sci. Eng. 2022, 10(1), 3; https://doi.org/10.3390/jmse10010003 - 21 Dec 2021
Cited by 30 | Viewed by 3526
Abstract
A novel collision avoidance (CA) algorithm was proposed based on the modified artificial potential field (APF) method, to construct a practical ship automatic CA system. Considering the constraints of both the International Regulations for Preventing Collisions at Sea (COLREGS) and the motion characteristics [...] Read more.
A novel collision avoidance (CA) algorithm was proposed based on the modified artificial potential field (APF) method, to construct a practical ship automatic CA system. Considering the constraints of both the International Regulations for Preventing Collisions at Sea (COLREGS) and the motion characteristics of the ship, the multi-ship CA algorithm was realized by modifying the repulsive force model in the APF method. Furthermore, the distance from the closest point of approach-time to the closest point of approach (DCPA-TCPA) criterion was selected as the unique adjustable parameter from the perspective of navigation practice. Collaborative CA experiments were designed and conducted to validate the proposed algorithm. The results of the experiments revealed that the actual DCPA and TCPA agree well with the parameter setup that keeps the ship at a safe distance from other ships in complex encountering situations. Consequently, the algorithm proposed in this study can achieve efficient automatic CA with minimal parameter settings. Moreover, the navigators can easily accept and comprehend the adjustable parameters, enabling the algorithm to satisfy the demand of the engineering applications. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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16 pages, 4540 KiB  
Article
Navigation Situation Clustering Model of Human-Operated Ships for Maritime Autonomous Surface Ship Collision Avoidance Tests
by Taewoong Hwang and Ik-Hyun Youn
J. Mar. Sci. Eng. 2021, 9(12), 1458; https://doi.org/10.3390/jmse9121458 - 20 Dec 2021
Cited by 12 | Viewed by 2490
Abstract
The collision avoidance system is one of the core systems of MASS (Maritime Autonomous Surface Ships). The collision avoidance system was validated using scenario-based experiments. However, the scenarios for the validation were designed based on COLREG (International Regulations for Preventing Collisions at Sea) [...] Read more.
The collision avoidance system is one of the core systems of MASS (Maritime Autonomous Surface Ships). The collision avoidance system was validated using scenario-based experiments. However, the scenarios for the validation were designed based on COLREG (International Regulations for Preventing Collisions at Sea) or are arbitrary. Therefore, the purpose of this study is to identify and systematize objective navigation situation scenarios for the validation of autonomous ship collision avoidance algorithms. A data-driven approach was applied to collect 12-month Automatic Identification System data in the west sea of Korea, to extract the ship’s trajectory, and to hierarchically cluster the data according to navigation situations. Consequently, we obtained the hierarchy of navigation situations and the frequency of each navigation situation for ships that sailed the west coast of Korea during one year. The results are expected to be applied to develop a collision avoidance test environment for MASS. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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21 pages, 31904 KiB  
Article
Prediction of Maneuverability in Shallow Water of Fishing Trawler by Using Empirical Formula
by Su-Hyung Kim, Chun-Ki Lee and Yang-Bum Chae
J. Mar. Sci. Eng. 2021, 9(12), 1392; https://doi.org/10.3390/jmse9121392 - 06 Dec 2021
Cited by 3 | Viewed by 2427
Abstract
The length between perpendiculars (LBP) of most fishing vessels is less than 100 m. Thus, they are not subject to the International Maritime Organization (IMO) maneuverability standards, affecting research on maneuverability. However, upon referencing the statistics of marine accidents related to vessel maneuvering, [...] Read more.
The length between perpendiculars (LBP) of most fishing vessels is less than 100 m. Thus, they are not subject to the International Maritime Organization (IMO) maneuverability standards, affecting research on maneuverability. However, upon referencing the statistics of marine accidents related to vessel maneuvering, the number of marine accidents caused by fishing vessels is 3 to 5 times higher than that of merchant ships. Therefore, systematic and consistent research on the maneuverability characteristics of fishing vessels is surely required. In particular, a fishing vessel frequently enters and departs from the same port and often sails at high speed due to familiarity with the characteristics of the situation, which may cause maneuvering-related accidents. In this study, the maneuverability of a fishing vessel in shallow water was predicted using an empirical formula. The results of this study are expected to not only be of great help in conducting simulations when analyzing marine accidents involving fishing vessels, but will also provide unique parameters of fishing vessels that lead to developing autonomous vessels. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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19 pages, 9916 KiB  
Article
Robust Parameter Estimation of an Empirical Manoeuvring Model Using Free-Running Model Tests
by Ana Catarina Costa, Haitong Xu and Carlos Guedes Soares
J. Mar. Sci. Eng. 2021, 9(11), 1302; https://doi.org/10.3390/jmse9111302 - 20 Nov 2021
Cited by 11 | Viewed by 1949
Abstract
The work presents the identification and validation of the hydrodynamic coefficients for the surge, sway, and yaw motion. This is performed in two ways: using simulated data and free-running test data. The identification and validation with the simulation data are carried out using [...] Read more.
The work presents the identification and validation of the hydrodynamic coefficients for the surge, sway, and yaw motion. This is performed in two ways: using simulated data and free-running test data. The identification and validation with the simulation data are carried out using a 25° turning test and a 20°−20° zigzag manoeuvring test. For the free-running test data, two zigzag manoeuvres are used: 30°−30° zigzag for identification and 20°−20° zigzag for validation. A nonlinear manoeuvring model is proposed based on the standard Euler equations, and the hydrodynamic coefficients are computed using empirical equations. To obtain robust results, the truncated singular value decomposition is employed to diminish the multicollinearity and the parameter uncertainties due to noise. The validation is carried out by comparing the result of the measured values with the predictions obtained using the manoeuvring models. Finally, a sensitivity analysis for the simulation data is performed to understand the influence of the parameters in the manoeuvres. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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20 pages, 7698 KiB  
Article
Ship Motion Planning for MASS Based on a Multi-Objective Optimization HA* Algorithm in Complex Navigation Conditions
by Meiyi Wu, Anmin Zhang, Miao Gao and Jiali Zhang
J. Mar. Sci. Eng. 2021, 9(10), 1126; https://doi.org/10.3390/jmse9101126 - 14 Oct 2021
Cited by 5 | Viewed by 2141
Abstract
Ship motion planning constitutes the most critical part in the autonomous navigation systems of marine autonomous surface ships (MASS). Weather and ocean conditions can significantly affect their navigation, but there are relatively few studies on the influence of wind and current on motion [...] Read more.
Ship motion planning constitutes the most critical part in the autonomous navigation systems of marine autonomous surface ships (MASS). Weather and ocean conditions can significantly affect their navigation, but there are relatively few studies on the influence of wind and current on motion planning. This study investigates the motion planning problem for USV, wherein the goal is to obtain an optimal path under the interference of the navigation environment (wind and current), and control the USV in order to avoid obstacles and arrive at its destination without collision. In this process, the influences of search efficiency, navigation safety and energy consumption on motion planning are taken into consideration. Firstly, the navigation environment is constructed by integrating information, including the electronic navigational chart, wind and current field. Based on the environmental interference factors, the three-degree-of-freedom kinematic model of USVs is created, and the multi-objective optimization and complex constraints are reasonably expressed to establish the corresponding optimization model. A multi-objective optimization algorithm based on HA* is proposed after considering the constraints of motion and dynamic and optimization objectives. Simulation verifies the effectiveness of the algorithm, where an efficient, safe and economical path is obtained and is more in line with the needs of practical application. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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18 pages, 5454 KiB  
Article
A Practical Trajectory Tracking Scheme for a Twin-Propeller Twin-Hull Unmanned Surface Vehicle
by Jiucai Jin, Deqing Liu, Dong Wang and Yi Ma
J. Mar. Sci. Eng. 2021, 9(10), 1070; https://doi.org/10.3390/jmse9101070 - 30 Sep 2021
Cited by 5 | Viewed by 1922
Abstract
Trajectory tracking is a basis of motion control for Unmanned Surface Vehicles (USVs), which has been researched well for common USVs. The twin-propeller and twin-hull USV (TPTH-USV) is a special vehicle for applications due to its good stability and high load. We propose [...] Read more.
Trajectory tracking is a basis of motion control for Unmanned Surface Vehicles (USVs), which has been researched well for common USVs. The twin-propeller and twin-hull USV (TPTH-USV) is a special vehicle for applications due to its good stability and high load. We propose a three-layered architecture of trajectory tracking for the TPTH-USV which explicitly decomposes into trajectory guidance, a motion limitator and controller. The trajectory guidance transforms an expected trajectory into an expected speed and expected course in a kinematic layer. The motion limitator describes some restriction for motion features of the USV in the restriction layer, such as the maximum speed and maximum yaw rate. The controller is to control the speed and course of the USV in the kinetic layer. In the first layer, an adaptive line-of-sight guidance law is designed by regulating the speed and course to track a curved line considering the sideslip angle. In the second layer, the motion features are extracted from an identified speed and course coupled model. In the last layer, the course and speed controller are designed based on a twin-PID controller. The feasibility and practicability of the proposed trajectory tracking scheme is validated in sea experiments by a USV called ‘Jiuhang 490’. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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18 pages, 3983 KiB  
Article
Method for the Coordination of Referencing of Autonomous Underwater Vehicles to Man-Made Objects Using Stereo Images
by Valery Bobkov, Alexey Kudryashov and Alexander Inzartsev
J. Mar. Sci. Eng. 2021, 9(9), 1038; https://doi.org/10.3390/jmse9091038 - 21 Sep 2021
Cited by 8 | Viewed by 2044
Abstract
The use of an autonomous underwater vehicle (AUV) to inspect underwater industrial infrastructure requires the precise, coordinated movement of the AUV relative to subsea objects. One significant underwater infrastructure system is the subsea production system (SPS), which includes wells for oil and gas [...] Read more.
The use of an autonomous underwater vehicle (AUV) to inspect underwater industrial infrastructure requires the precise, coordinated movement of the AUV relative to subsea objects. One significant underwater infrastructure system is the subsea production system (SPS), which includes wells for oil and gas production, located on the seabed. The present paper suggests a method for the accurate navigation of AUVs in a distributed SPS to coordinate space using video information. This method is based on the object recognition and computation of the AUV coordinate references to SPS objects. Stable high accuracy during the continuous movement of the AUV in SPS space is realized through the regular updating of the coordinate references to SPS objects. Stereo images, a predefined geometric SPS model, and measurements of the absolute coordinates of a limited number of feature points of objects are used as initial data. The matrix of AUV coordinate references to the SPS object coordinate system is computed using 3D object points matched with the model. The effectiveness of the proposed method is estimated based on the results of computational experiments with virtual scenes generated in the simulator for AUV, and with real data obtained by the Karmin2 stereo camera (Nerian Vision, Stuttgart, Germany) in laboratory conditions. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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14 pages, 3776 KiB  
Article
Ship Target Detection Algorithm Based on Improved YOLOv5
by Junchi Zhou, Ping Jiang, Airu Zou, Xinglin Chen and Wenwu Hu
J. Mar. Sci. Eng. 2021, 9(8), 908; https://doi.org/10.3390/jmse9080908 - 22 Aug 2021
Cited by 46 | Viewed by 5468
Abstract
In order to realize the real-time detection of an unmanned fishing speedboat near a ship ahead, a perception platform based on a target visual detection system was established. By controlling the depth and width of the model to analyze and compare training, it [...] Read more.
In order to realize the real-time detection of an unmanned fishing speedboat near a ship ahead, a perception platform based on a target visual detection system was established. By controlling the depth and width of the model to analyze and compare training, it was found that the 5S model had a fast detection speed but low accuracy, which was judged to be insufficient for detecting small targets. In this regard, this study improved the YOLOv5s algorithm, in which the initial frame of the target is re-clustered by K-means at the data input end, the receptive field area is expanded at the output end, and the loss function is optimized. The results show that the precision of the improved model’s detection for ship images was 98.0%, and the recall rate was 96.2%. Mean average precision (mAP) reached 98.6%, an increase of 4.4% compared to before the improvements, which shows that the improved model can realize the detection and identification of multiple types of ships, laying the foundation for subsequent path planning and automatic obstacle avoidance of unmanned ships. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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24 pages, 4442 KiB  
Article
A Unified Approach for Underwater Homing and Docking of over-Actuated AUV
by Mingjiu Zuo, Guandao Wang, Yongxin Xiao and Gong Xiang
J. Mar. Sci. Eng. 2021, 9(8), 884; https://doi.org/10.3390/jmse9080884 - 17 Aug 2021
Cited by 12 | Viewed by 2907
Abstract
During the implementation of time-consuming tasks such as underwater observation or detection, AUV has to face a difficult and urgent problem that its working duration is greatly shortened by the limited energy stored in the battery device. To solve the power problem, a [...] Read more.
During the implementation of time-consuming tasks such as underwater observation or detection, AUV has to face a difficult and urgent problem that its working duration is greatly shortened by the limited energy stored in the battery device. To solve the power problem, a docking station is installed underwater for AUV charging its battery. However, to realize the automatic underwater charging of AUV via a docking station, the accurate and efficient completion of underwater homing and docking is required for AUV. Underwater automatic homing and docking system is of great significance to improve work efficiency and prolong the endurance of AUV save cost. In this paper, a unified approach that involves such as task planning, guidance and control design, thrust allocation has been proposed to provide a complete solution to the problem of homing and docking of an over-actuated AUV. The task-based hybrid target point/line planning and following strategy are proposed for AUV homing and docking. At the beginning of homing, AUV is planned to follow a straight line via the line of sight (LoS) method. Afterward, AUV starts to follow multiple predefined target points until reaching the docking station. At the final stage of docking (within 10 m), a dedicated computer vision algorithm is applied to detect a newly designed LED light array fixed on the docking station to provide accurate guidance for the AUV to dock. The sliding mode control technique is used for the motion control of the AUV allowing robustness. As the AUV configured with eight thrusters is over-actuated, the problem of the thrust allocation is very important and successfully solved using the quadratic programming (QP) optimization method. Finally, the simulations of homing and docking tasks using the AUV are accomplished to verify the proposed approach. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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17 pages, 2104 KiB  
Article
COLREGs: Compliant Dynamic Obstacle Avoidance of USVs Based on the Dynamic Navigation Ship Domain
by Fang Deng, Leilei Jin, Xiuhui Hou, Longjin Wang, Boyang Li and Hualin Yang
J. Mar. Sci. Eng. 2021, 9(8), 837; https://doi.org/10.3390/jmse9080837 - 01 Aug 2021
Cited by 15 | Viewed by 3096
Abstract
Dynamic obstacle avoidance is essential for unmanned surface vehicles (USVs) to achieve autonomous sailing. This paper presents a dynamic navigation ship domain (DNSD)-based dynamic obstacle avoidance approach for USVs in compliance with COLREGs. Based on the detected obstacle information, the approach can not [...] Read more.
Dynamic obstacle avoidance is essential for unmanned surface vehicles (USVs) to achieve autonomous sailing. This paper presents a dynamic navigation ship domain (DNSD)-based dynamic obstacle avoidance approach for USVs in compliance with COLREGs. Based on the detected obstacle information, the approach can not only infer the collision risk, but also plan the local avoidance path trajectory to make appropriate avoidance maneuvers. Firstly, the analytical DNSD model is established taking into account the ship parameters, maneuverability, sailing speed, and encounter situations regarding COLREGs. Thus, the DNSDs of the own and target ships are utilized to trigger the obstacle avoidance mode and determine whether and when the USV should make avoidance maneuvers. Then, the local avoidance path planner generates the new avoidance waypoints and plans the avoidance trajectory. Simulations were implemented for a single obstacle under different encounter situations and multiple dynamic obstacles. The results demonstrated the effectiveness and superiority of the proposed DNSD-based obstacle avoidance algorithm. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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15 pages, 3776 KiB  
Article
Identification and Prediction of Ship Maneuvering Motion Based on a Gaussian Process with Uncertainty Propagation
by Yifan Xue, Yanjun Liu, Gang Xue and Gang Chen
J. Mar. Sci. Eng. 2021, 9(8), 804; https://doi.org/10.3390/jmse9080804 - 27 Jul 2021
Cited by 8 | Viewed by 3282
Abstract
Maritime transport plays a vital role in economic development. To establish a vessel scheduling model, accurate ship maneuvering models should be used to optimize the strategy and maximize the economic benefits. The use of nonparametric modeling techniques to identify ship maneuvering systems has [...] Read more.
Maritime transport plays a vital role in economic development. To establish a vessel scheduling model, accurate ship maneuvering models should be used to optimize the strategy and maximize the economic benefits. The use of nonparametric modeling techniques to identify ship maneuvering systems has attracted considerable attention. The Gaussian process has high precision and strong generalization ability in fitting nonlinear functions and requires less training data, which is suitable for ship dynamic model identification. Compared with other machine learning methods, the most obvious advantage of the Gaussian process is that it can provide the uncertainty of prediction. However, most studies on ship modeling and prediction do not consider the uncertainty propagation in Gaussian processes. In this paper, a moment-matching-based approach is applied to address the problem. The proposed identification scheme for ship maneuvering systems is verified by container ship simulation data and experimental data from the Workshop on Verification and Validation of Ship Maneuvering Simulation Methods (SIMMAN) database. The results indicate that the identified model is accurate and shows good generalization performance. The uncertainty of ship motion prediction is well considered based on the uncertainty propagation technology. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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19 pages, 52497 KiB  
Article
Vertical Profile Diving and Floating Motion Control of the Underwater Glider Based on Fuzzy Adaptive LADRC Algorithm
by Zhiguang Wang, Caoyang Yu, Mingjie Li, Baoheng Yao and Lian Lian
J. Mar. Sci. Eng. 2021, 9(7), 698; https://doi.org/10.3390/jmse9070698 - 25 Jun 2021
Cited by 19 | Viewed by 2256
Abstract
The underwater glider is a kind of novel invention that has been proven to be perfect for long-duration, wide-range marine environmental monitoring tasks. It is controlled by changing the buoyancy and adjusting the posture. For precise control of the underwater glider’s trajectory, a [...] Read more.
The underwater glider is a kind of novel invention that has been proven to be perfect for long-duration, wide-range marine environmental monitoring tasks. It is controlled by changing the buoyancy and adjusting the posture. For precise control of the underwater glider’s trajectory, a fuzzy adaptive linear active disturbance rejection control (LADRC) is designed in this paper. This controller allows the glider to dive to a predetermined depth precisely and float at a specific depth. In addition, the controller takes some important factors into account, such as model uncertainty, environmental disturbances, and the limited dynamic output of the actual mechanical actuator. Finally, simulation results show the superiority of this fuzzy adaptive LADRC control method. Particularly, when the underwater glider was controlled to dive 100 m at a predetermined attitude angle θ = −1 rad, the maximum overshoot of FLADRC is reduced by 75.1%, 56.6% relative to PID, LADRC, respectively. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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20 pages, 5950 KiB  
Article
Modified Vector Field Path-Following Control System for an Underactuated Autonomous Surface Ship Model in the Presence of Static Obstacles
by Haitong Xu, Miguel A. Hinostroza and C. Guedes Soares
J. Mar. Sci. Eng. 2021, 9(6), 652; https://doi.org/10.3390/jmse9060652 - 12 Jun 2021
Cited by 22 | Viewed by 3464
Abstract
A modified path-following control system using the vector field method for an underactuated autonomous surface ship model is proposed in the presence of static obstacles. With this integrated system, autonomous ships are capable of following the predefined path, while avoiding the obstacles automatically. [...] Read more.
A modified path-following control system using the vector field method for an underactuated autonomous surface ship model is proposed in the presence of static obstacles. With this integrated system, autonomous ships are capable of following the predefined path, while avoiding the obstacles automatically. It is different from the methods in most published papers, which usually study path-following and obstacle collision avoidance, separately. This paper considers the coupled path following and collision avoidance task as a whole. Meanwhile, the paper also shows the heading control design method in the presence of static obstacles. To obtain a strong stability property, a nonlinear autopilot is designed based on the manoeuvring tests of the free-running ship model. The equilibrium point of the controller is globally exponentially stable. For the guidance system, a novel vector field method was proposed, and the proof shows the coupled guidance and control system is uniform semi-global exponentially stable (USGES). To prevent the obstacles near the predefined path, the proposed guidance law is augmented by integrating the repelling field of obstacles so that it can control the ship travel toward the predefined path through the obstacles safely. The repelling field function is given considering the obstacle shape and collision risk using the velocity obstacle (VO) algorithm. The simulations and ship model test were performed to validate the integrated system of autonomous ships. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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18 pages, 28123 KiB  
Article
A Buckling Analysis and Optimization Method for a Variable Stiffness Cylindrical Pressure Shell of AUV
by Zhaoqi Yang, Yonghui Cao and Jing Liu
J. Mar. Sci. Eng. 2021, 9(6), 637; https://doi.org/10.3390/jmse9060637 - 08 Jun 2021
Cited by 7 | Viewed by 2244
Abstract
The composite cylindrical shell pressure structure is widely used for autonomous underwater vehicle (AUV). To analyze the critical buckling problem of variable stiffness (VS) composite pressure structure of AUV, a discrete finite element (DFE) method based on the curve fiber path function is [...] Read more.
The composite cylindrical shell pressure structure is widely used for autonomous underwater vehicle (AUV). To analyze the critical buckling problem of variable stiffness (VS) composite pressure structure of AUV, a discrete finite element (DFE) method based on the curve fiber path function is developed in this work. A design and optimization method based on the radial basis function surrogate method is proposed to optimize the critical buckling pressure for a VS composite cylindrical shell. Both the DFE and surrogate methods are verified to be valid by comparison with the experimental data from the listed references. The effects of the geometric parameter and fiber angle on the critical buckling pressure are studied for different cylindrical shell cases. The results indicate that the proposed simulation model and optimization method are accurate and efficient for the buckling analysis and optimization of a VS composite cylindrical shell. Optimization result shows that the optimum critical buckling pressure for the VS cylindrical shell is improved and is 21.1% larger than that of the constant stiffness cylindrical shell under the same geometric and boundary condition. Full article
(This article belongs to the Special Issue Maritime Autonomous Vessels)
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