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Open AccessArticle

Path Planning of an Unmanned Surface Vessel Based on the Improved A-Star and Dynamic Window Method

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J. Mar. Sci. Eng. 2023, 11(5), 1060; https://doi.org/10.3390/jmse11051060 - 16 May 2023

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Abstract

In order to ensure the safe navigation of USVs (unmanned surface vessels) and real-time collision avoidance, this study conducts global and local path planning for USVs in a variable dynamic environment, while local path planning is proposed under the consideration of USV motion [...] Read more.

In order to ensure the safe navigation of USVs (unmanned surface vessels) and real-time collision avoidance, this study conducts global and local path planning for USVs in a variable dynamic environment, while local path planning is proposed under the consideration of USV motion characteristics and COLREGs (International Convention on Regulations for Collision Avoidance at Sea) requirements. First, the basis of collision avoidance decisions based on the dynamic window method is introduced. Second, the knowledge of local collision avoidance theory is used to study the local path planning of USV, and finally, simulation experiments are carried out in different situations and environments containing unknown obstacles. The local path planning experiments with unknown obstacles can prove that the local path planning algorithm proposed in this study has good results and can ensure that the USV makes collision avoidance decisions based on COLREGs when it meets with a ship. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Maritime Transportation)

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Open AccessArticle

Improved UNet-Based Shoreline Detection Method in Real Time for Unmanned Surface Vehicle

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J. Mar. Sci. Eng. 2023, 11(5), 1049; https://doi.org/10.3390/jmse11051049 - 15 May 2023

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Abstract

Accurate and real-time monitoring of the shoreline through cameras is an invaluable guarantee for the safety of near-shore navigation and berthing of unmanned surface vehicles; existing shoreline detection methods cannot meet both these requirements. Therefore, we propose an improved shoreline detection method to [...] Read more.

Accurate and real-time monitoring of the shoreline through cameras is an invaluable guarantee for the safety of near-shore navigation and berthing of unmanned surface vehicles; existing shoreline detection methods cannot meet both these requirements. Therefore, we propose an improved shoreline detection method to detect shorelines accurately and in real time. We define shoreline detection as the combination of water surface area segmentation and edge detection, the key to which is segmentation. To detect shorelines accurately and in real time, we propose an improved U-Net for water segmentation. This network is based on U-Net, using ResNet-34 as the backbone to enhance the feature extraction capability, with a concise decoder integrated attention mechanism to improve the processing speed while ensuring the accuracy of water surface segmentation. We also introduce transfer learning to improve training efficiency and solve the problem of insufficient data. When obtaining the segmentation result, the Laplace edge detection algorithm is applied to detect the shoreline. Experiments show that our network achieves 97.05% MIoU and 40 FPS with the fewest parameters, which is better than mainstream segmentation networks, and also demonstrate that our shoreline detection method can effectively detect shorelines in real time in various environments. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Maritime Transportation)

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Open AccessArticle

Modelling, Linearity Analysis and Optimization of an Inductive Angular Displacement Sensor Based on Magnetic Focusing in Ships

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J. Mar. Sci. Eng. 2023, 11(5), 1028; https://doi.org/10.3390/jmse11051028 - 11 May 2023

Viewed by 753

Abstract

A sensor for measuring the crankshaft angle of the main engine in ships is designed. Compared with the existing crankshaft angle encoder, this design’s advantage is that there is no need to add a gear system at the free end of the crankshaft, [...] Read more.

A sensor for measuring the crankshaft angle of the main engine in ships is designed. Compared with the existing crankshaft angle encoder, this design’s advantage is that there is no need to add a gear system at the free end of the crankshaft, reducing machining complexity. The purpose of providing high angle resolution over a wide speed range is achieved. Inductive angular displacement sensors (IADSs) require an eddy current magnetic field as a medium to generate the induced voltage. The induced voltage also requires a complex linearization calculation to obtain a linear relationship between angle and voltage. Therefore, a model of the inductive angular displacement sensor based on magnetic focusing (IADSMF) is proposed. Magnetic focusing is introduced into the IADS to replace the eddy current magnetic field with a focusing magnetic field. The main disadvantage of traditional IADSs, which is that they cannot reduce the eddy current magnetic field, is mitigated. An approximate square–shaped focusing magnetic field (12.4 × 12.4 mm²) is formed using the magnetic field constraint of the magnetic conductor. When the receiving coil undergoes a position change relative to the square–shaped focusing magnetic field, the voltage generated via the receiving coil is measured using the electromagnetic induction principle to achieve angular displacement measurement. A mathematical model of the IADSMF is derived. Induced voltages at different frequencies and rotational speeds are simulated and analyzed via MATLAB. The results show that frequency is the main factor affecting the induced voltage amplitude. The sensitivity of the IADSMF is 0.2023 mV/°. The resolution and measurement of the IADSMF range from 0.06° and 0–360°. Compared with a conventional planar coil–based IADS, the eddy current loss is reduced from 2.1304 to 0.3625 W. Direct linearization of the angular displacement with the induced voltage is achieved through designing a square–shaped focusing field and receiving coil. After optimizing the sensor structure with the optimization algorithm, the linearity error is 0.6012%. Finally, this sensor provides a theoretical basis and research ideas for IADS development in ships and navigation. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Maritime Transportation)

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Open AccessArticle

An Improved NSGA-II Based on Multi-Task Optimization for Multi-UAV Maritime Search and Rescue under Severe Weather

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J. Mar. Sci. Eng. 2023, 11(4), 781; https://doi.org/10.3390/jmse11040781 - 04 Apr 2023

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Abstract

The international trade heavily relies on maritime transportation. Due to the vastness of the ocean, once an accident happens, fast maritime search and rescue (MSR) is a must, as it is of life-and-death matter. Using unmanned air vehicles (UAVs) is an effective approach [...] Read more.

The international trade heavily relies on maritime transportation. Due to the vastness of the ocean, once an accident happens, fast maritime search and rescue (MSR) is a must, as it is of life-and-death matter. Using unmanned air vehicles (UAVs) is an effective approach to completing complex MSR tasks, especially when the environment is dangerous and changeable. However, how to effectively plan paths for multi-UAVs under severe weather, e.g., to rescue the most urgent targets in the shortest time, is a challenging task. In this study, an improved NSGA-II based on multi-task optimization (INSGA-II-MTO) is proposed to plan paths for multi-UAVs in the MSR tasks. In the INSGA-II-MTO, a novel population initialization method is proposed to improve the diversity of an initial population. Further, two tasks are introduced during the execution of the search algorithm. Namely, one assistant task, which solves a simplified MSR problem through multi-task optimization, is implemented to provide necessary evolutional knowledge to a main task that solves an original MSR problem. The performance of the proposed INSGA-II-MTO is compared with other competitors in three MSR scenarios. Experimental results indicate that the proposed algorithm performs best among the compared ones. It is observed that the INSGA-II-MTO can find a set of shorter total paths and handle the most urgent task in the shortest possible time. Therefore, the proposed method is an effective and promising approach to solving multi-UAVs MSR problems to reduce human causalities and property losses. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Maritime Transportation)

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Open AccessArticle

A Study on the Correlation between Ship Movement Characteristics and Ice Conditions in Polar Waters

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Liang Chen

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Changhai Huang

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Yanhao Wang

J. Mar. Sci. Eng. 2023, 11(4), 729; https://doi.org/10.3390/jmse11040729 - 27 Mar 2023

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Abstract

The opening of arctic routes provides a new option for international navigation ships. The correlation between ship movement characteristics and ice conditions should be known, which will help ships adapt to the polar waters. Based on the voyage data and sea ice manual [...] Read more.

The opening of arctic routes provides a new option for international navigation ships. The correlation between ship movement characteristics and ice conditions should be known, which will help ships adapt to the polar waters. Based on the voyage data and sea ice manual observation data of the ‘XUE LONG’ ship’s six voyages in polar waters, a correlation analysis model of ice conditions and ship movement characteristics was established in this work. First, the ship movement characteristics in polar waters were analyzed, such as the distribution characteristics of ship speeds, courses, and variation characteristics by using the descriptive statistical analysis method and data visualization analysis method. Then, by using multivariate correlation analysis and univariate controlled correlation analysis methods, the correlation between movement characteristics and ice conditions, such as ice concentration and thickness, and the correlation between different ice conditions themselves, were quantitatively analyzed. The result shows that the correlation analysis model of ice conditions and ship movement characteristics is reliable and effective and can obtain quantitative correlation analysis results. On the one hand, sea ice thickness has almost no significant correlation with ship movement characteristics, excluding the influence of sea ice concentration. On the other hand, excluding the influence of sea ice thickness, sea ice concentration is still significantly correlated with the absolute value of speed, speed variation, and course variation. The conclusions of this work have important reference significance for polar scientific investigations, commercial ships’ voyages in icy waters, and ships’ designs for icy waters. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Maritime Transportation)

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Open AccessArticle

Research on Position Sensorless Control of RDT Motor Based on Improved SMO with Continuous Hyperbolic Tangent Function and Improved Feedforward PLL

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Hongfen Bai

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Bo Yu

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Wei Gu

J. Mar. Sci. Eng. 2023, 11(3), 642; https://doi.org/10.3390/jmse11030642 - 17 Mar 2023

Viewed by 511

Abstract

With the increasing use of electric propulsion ships, the emergence of the shaftless rim-driven thruster (RDT) as a revolutionary integrated motor thruster is gradually becoming an important development direction for green ships. The shaftless structure of RDTs leads to their dependence on position [...] Read more.

With the increasing use of electric propulsion ships, the emergence of the shaftless rim-driven thruster (RDT) as a revolutionary integrated motor thruster is gradually becoming an important development direction for green ships. The shaftless structure of RDTs leads to their dependence on position sensorless control techniques. In this study, a novel control algorithm using a composite sliding mode observer (SMO) with a modified feed-forward phase-locked loop (PLL) is presented for achieving high accuracy position and speed control of shaftless RDT motors. The deviation between the observed and actual currents is exploited to develop a current SMO to extract back electromotive force (back-EMF) errors. On this basis, a back-EMF observer is established to achieve accurate estimation of the back-EMF. The basic structure of the PLL was modified and incorporates a speed feedforward mechanism, which enhances the performance of rotor position estimation and facilitates bidirectional rotation. The stability of the algorithm has been verified in Matlab/Simulink for a range of steady-state, dynamic, and ship propeller loading conditions. Remarkably, the control algorithm boasts an impressive adjustment time of approximately 0.006 s and its position estimation error may be as low as 0.03 rad. Simulation results highlight the performance of the algorithm to achieve bidirectional rotation, while exhibiting fast convergence, minimal vibration, exceptional control accuracy, and robustness. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Maritime Transportation)

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Open AccessArticle

A Novel Intelligent Ship Detection Method Based on Attention Mechanism Feature Enhancement

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J. Mar. Sci. Eng. 2023, 11(3), 625; https://doi.org/10.3390/jmse11030625 - 16 Mar 2023

Viewed by 559

Abstract

The intelligent perception ability of the close-range navigation environment is the basis of autonomous decision-making and control of unmanned ships. In order to realize real-time perception of the close-range environment of unmanned ships, an enhanced attention mechanism YOLOv4 (EA-YOLOv4) algorithm is proposed. First [...] Read more.

The intelligent perception ability of the close-range navigation environment is the basis of autonomous decision-making and control of unmanned ships. In order to realize real-time perception of the close-range environment of unmanned ships, an enhanced attention mechanism YOLOv4 (EA-YOLOv4) algorithm is proposed. First of all, on the basis of YOLOv4, the convolutional block attention module (CBAM) is used to search for features in channel and space dimensions, respectively, to improve the model’s feature perception of ship targets. Then, the improved-efficient intersection over union (EIoU) loss function is used to replace the complete intersection over union (CIoU) loss function of the YOLOv4 algorithm to improve the algorithm’s perception of ships of different sizes. Finally, in the post-processing of algorithm prediction, soft non-maximum suppression (Soft-NMS) is used to replace the non-maximum suppression (NMS) of YOLOv4 to reduce the missed detection of overlapping ships without affecting the efficiency. The proposed method is verified on the large data set SeaShips, and the average accuracy rate of mAP^0.5–0.95 reaches 72.5%, which is 10.7% higher than the original network YOLOv4, and the FPS is 38 frames/s, which effectively improves the ship detection accuracy while ensuring real-time performance. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Maritime Transportation)

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Open AccessArticle

A Refined Collaborative Scheduling Method for Multi-Equipment at U-Shaped Automated Container Terminals Based on Rail Crane Process Optimization

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J. Mar. Sci. Eng. 2023, 11(3), 605; https://doi.org/10.3390/jmse11030605 - 13 Mar 2023

Viewed by 614

Abstract

A U-shaped automated container terminal (ACT) has been proposed for the first time globally and has been adopted to construct the Beibu Gulf Port ACT. In this ACT layout, the double cantilevered rail crane (DCRC) simultaneously provides loading and unloading services for the [...] Read more.

A U-shaped automated container terminal (ACT) has been proposed for the first time globally and has been adopted to construct the Beibu Gulf Port ACT. In this ACT layout, the double cantilevered rail crane (DCRC) simultaneously provides loading and unloading services for the external container trucks (ECTs) and the automatic guided vehicles (AGVs) entering the yard. The DCRC has a complex scheduling coupling relationship with the AGV and the ECT, and its mathematical model is extremely complex. There is an urgent need to study a practical collaborative scheduling optimization model and algorithm for the DCRC, the AGV, and the ECT. In this paper, we optimize the process flow of DCRCs to study the refined collaborative scheduling model of DCRCs, AGVs and ECTs in U-shaped ACTs. Firstly, we analyze the operation process of the DCRC and divide the 16 loading and unloading conditions of the DCRC into four operation modes for process optimization. Secondly, different variables and parameters are set for the DCRC’s four operating modes, and a refined collaborative dispatching model for the DCRCs with AGVs and ECTs is proposed. Finally, a practical adaptive co-evolutionary genetic algorithm solves the model. Meanwhile, arithmetic examples verify the correctness and practicality of the model and algorithm. The experimental results show that the total running time of the DCRCs is the shortest in the U-shaped ACT when the number of quay cranes (QC) to DCRC and AGV ratios are 1:2 and 1:10, respectively. At the same time, the number of QCs and DCRCs has a more significant impact on the efficiency of the ACT than that of AGVs, and priority should be given to the allocation of QCs and DCRCs. The research results have essential guidance value for U-shaped ACTs under construction and enrich the theory and method of collaborative scheduling of U-shaped ACT equipment. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Maritime Transportation)

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