Journal of Marine Science and Engineering

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18 pages, 62968 KiB

Open AccessArticle

Improving ICP-Based Scanning Sonar Image Matching Performance Through Height Estimation of Feature Point Using Shaded Area

by Gwonsoo Lee, Sukmin Yoon, Yeongjun Lee and Jihong Lee

J. Mar. Sci. Eng. 2025, 13(1), 150; https://doi.org/10.3390/jmse13010150 - 16 Jan 2025

Viewed by 701

Abstract

This study presents an innovative method for estimating the height of feature points through shaded area analysis, to enhance the performance of iterative closest point (ICP)-based algorithms for matching scanning sonar images. Unlike other sensors, such as forward looking sonar (FLS) or BlueView, [...] Read more.

This study presents an innovative method for estimating the height of feature points through shaded area analysis, to enhance the performance of iterative closest point (ICP)-based algorithms for matching scanning sonar images. Unlike other sensors, such as forward looking sonar (FLS) or BlueView, scanning sonar has an extended data acquisition period, complicating data collection while in motion. Additionally, existing ICP-based matching algorithms that rely on two-dimensional scanning sonar data suffer from matching errors due to ambiguities in the nearest-point matching process, typically arising when the feature points demonstrate similarities in size and spatial arrangement, leading to numerous potential connections between them. To mitigate these matching ambiguities, we restrict the matching areas in the two images that need to be aligned. We propose two strategies to limit the matching area: the first utilizes the position and orientation information derived from the navigation algorithm, while the second involves estimating the overlapping region between the two images through height assessments of the feature points, facilitated by shaded area analysis. This latter strategy emphasizes preferential matching based on the height information obtained. We propose integrating these two approaches and validate the proposed algorithm through simulations, experimental basin tests, and real-world data collection, demonstrating its effectiveness. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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21 pages, 17721 KiB

Open AccessArticle

Comparison of Collision Avoidance Algorithms for Unmanned Surface Vehicle Through Free-Running Test: Collision Risk Index, Artificial Potential Field, and Safety Zone

by Jung-Hyeon Kim, Hyun-Jae Jo, Su-Rim Kim, Si-Woong Choi, Jong-Yong Park and Nakwan Kim

J. Mar. Sci. Eng. 2024, 12(12), 2255; https://doi.org/10.3390/jmse12122255 - 9 Dec 2024

Viewed by 1253

Abstract

This paper details the development of a collision avoidance algorithm for unmanned surface vehicles (USVs) and its validation using free-running tests. The USV, designed as a catamaran, incorporates a variety of sensors for its guidance, navigation, and control system. It performs turning maneuvers [...] Read more.

This paper details the development of a collision avoidance algorithm for unmanned surface vehicles (USVs) and its validation using free-running tests. The USV, designed as a catamaran, incorporates a variety of sensors for its guidance, navigation, and control system. It performs turning maneuvers using thrusters positioned on the port and starboard sides. The robot operating system is used to streamline communication, transmitting data such as position, orientation, and situational information from diverse sensors. Using the collision risk index (CRI) method, the algorithm calculates risk based on the distance to obstacles and the angle to the desired waypoint, directing the USV on a path with minimized risk. Noise within the data captured by the two-dimensional light detection and ranging system is filtered out using the k-dimensional tree and Euclidean distance methods, ensuring single obstacles are distinctly identified. To assess the efficacy of the CRI-based collision avoidance algorithm, it was benchmarked against other algorithms rooted in the artificial potential field and safety zone methods within an artificial tank setting. The results highlight the CRI method’s superior time efficiency and optimality in comparison to its counterparts. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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14 pages, 2453 KiB

Open AccessArticle

A Stable Multi-Object Tracking Method for Unstable and Irregular Maritime Environments

by Young-Suk Han and Jae-Yoon Jung

J. Mar. Sci. Eng. 2024, 12(12), 2252; https://doi.org/10.3390/jmse12122252 - 7 Dec 2024

Viewed by 1002

Abstract

In this study, an improved stable multi-object simple online and real-time tracking (StableSORT) algorithm that was specifically designed for maritime environments was proposed to address challenges such as camera instability and irregular object motion. Specifically, StableSORT integrates a buffered IoU (B-IoU) and an [...] Read more.

In this study, an improved stable multi-object simple online and real-time tracking (StableSORT) algorithm that was specifically designed for maritime environments was proposed to address challenges such as camera instability and irregular object motion. Specifically, StableSORT integrates a buffered IoU (B-IoU) and an observation-adaptive Kalman filter (OAKF) into the StrongSORT framework to improve tracking accuracy and robustness. A dataset was collected along the southern coast of Korea using a small autonomous surface vehicle to capture real-world maritime conditions. On this dataset, StableSORT achieved a 2.7% improvement in HOTA, 4.9% in AssA, and 2.6% in IDF1 compared to StrongSORT, and it significantly outperformed ByteTrack and OC-SORT by 84% and 69% in HOTA, respectively. These results underscore StableSORT’s ability to maintain identity consistency and enhance tracking performance under challenging maritime conditions. The ablation studies further validated the contributions of the B-IoU and OAKF modules in maintaining identity consistency and tracking accuracy under challenging maritime conditions. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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20 pages, 1379 KiB

Open AccessArticle

Energy Efficiency Maximization for Multi-UAV-IRS-Assisted Marine Vehicle Systems

by Chaoyue Zhang, Bin Lin, Chao Li and Shuang Qi

J. Mar. Sci. Eng. 2024, 12(10), 1761; https://doi.org/10.3390/jmse12101761 - 4 Oct 2024

Viewed by 1221

Abstract

Mobile edge computing is envisioned as a prospective technology for supporting time-sensitive and computation-intensive applications in marine vehicle systems. However, the offloading performance is highly impacted by the poor wireless channel. Recently, an Unmanned Aerial Vehicle (UAV) equipped with an Intelligent Reflecting Surface [...] Read more.

Mobile edge computing is envisioned as a prospective technology for supporting time-sensitive and computation-intensive applications in marine vehicle systems. However, the offloading performance is highly impacted by the poor wireless channel. Recently, an Unmanned Aerial Vehicle (UAV) equipped with an Intelligent Reflecting Surface (IRS), i.e., UIRS, has drawn attention due to its capability to control wireless signals so as to improve the data rate. In this paper, we consider a multi-UIRS-assisted marine vehicle system where UIRSs are deployed to assist in the computation offloading of Unmanned Surface Vehicles (USVs). To improve energy efficiency, the optimization problem of the association relationships, computation resources of USVs, multi-UIRS phase shifts, and multi-UIRS trajectories is formulated. To solve the mixed-integer nonlinear programming problem, we decompose it into two layers and propose an integrated convex optimization and deep reinforcement learning algorithm to attain the near-optimal solution. Specifically, the inner layer solves the discrete variables by using the convex optimization based on Dinkelbach and relaxation methods, and the outer layer optimizes the continuous variables based on the Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3). The numerical results demonstrate that the proposed algorithm can effectively improve the energy efficiency of the multi-UIRS-assisted marine vehicle system in comparison with the benchmarks. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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22 pages, 5716 KiB

Open AccessArticle

A High-Precision Real-Time Distance Difference Localization Algorithm Based on Long Baseline Measurement

by Huiyu Chen, Zhangming He, Jiongqi Wang, Xinyong Zhang and Bowen Hou

J. Mar. Sci. Eng. 2024, 12(10), 1724; https://doi.org/10.3390/jmse12101724 - 1 Oct 2024

Cited by 1 | Viewed by 1018

Abstract

Underwater navigation practice shows that the long baseline survey has the characteristics of coplanar configuration, flat geometry, and large refraction error, which brings challenges to underwater positioning. To address this challenge, this paper proposes a high-precision real-time range-difference location algorithm based on underwater [...] Read more.

Underwater navigation practice shows that the long baseline survey has the characteristics of coplanar configuration, flat geometry, and large refraction error, which brings challenges to underwater positioning. To address this challenge, this paper proposes a high-precision real-time range-difference location algorithm based on underwater long baseline measurement. Firstly, the system error sources of long baseline positioning are analyzed in detail, the propagation models of different system errors are constructed, and the effects of system error sources on the rangefinder are described. Secondly, the limitations of traditional range iterative location algorithms and geometric analytic location algorithms in long baseline locations are analyzed. Then, using the strategy of converting the long baseline range information into the distance difference information, a high-precision real-time distance difference location algorithm based on long baseline measurement is presented. Finally, the feasibility of the algorithm is analyzed from the perspective of precision analysis. Numerical simulation results show that compared with the two traditional long-baseline positioning algorithms, the proposed algorithm has higher positioning accuracy and potential application value in the field of underwater real-time positioning. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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21 pages, 7394 KiB

Open AccessArticle

Output Feedback Adaptive Optimal Control of Multiple Unmanned Marine Vehicles with Unknown External Disturbance

by Liang-En Yuan, Yang Xiao, Tieshan Li and Dalin Zhou

J. Mar. Sci. Eng. 2024, 12(10), 1697; https://doi.org/10.3390/jmse12101697 - 25 Sep 2024

Viewed by 1038

Abstract

This paper presents an optimal output-feedback tracking control problem for multiple unmanned marine vehicles (UMVs) to track a desired trajectory. To guarantee the control objective in an optimal manner, adaptive dynamic programming (ADP) with optimal compensation terms is adopted. A neural velocity observer [...] Read more.

This paper presents an optimal output-feedback tracking control problem for multiple unmanned marine vehicles (UMVs) to track a desired trajectory. To guarantee the control objective in an optimal manner, adaptive dynamic programming (ADP) with optimal compensation terms is adopted. A neural velocity observer is designed based on a neural network (NN) to estimate the unmeasured system states and the unknown system dynamics. Furthermore, a disturbance observer (DO) is proposed to go against the effect of the unknown external disturbance of the sea environment. It is proved that the proposed controller can guarantee that all signals in the closed-loop system are bounded. Simulation results are given to demonstrate the effectiveness of the proposed control algorithm. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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20 pages, 8518 KiB

Open AccessArticle

An Anti-Occlusion Approach for Enhanced Unmanned Surface Vehicle Target Detection and Tracking with Multimodal Sensor Data

by Minjie Zheng, Dingyuan Li, Guoquan Chen, Weijun Wang and Shenhua Yang

J. Mar. Sci. Eng. 2024, 12(9), 1558; https://doi.org/10.3390/jmse12091558 - 5 Sep 2024

Viewed by 1277

Abstract

Multimodal sensors are often employed by USVs (unmanned surface vehicles) to enhance situational awareness, and the fusion of LiDAR and monocular vision is widely used in near-field perception scenarios. However, this strategy of fusing data from LiDAR and monocular vision may lead to [...] Read more.

Multimodal sensors are often employed by USVs (unmanned surface vehicles) to enhance situational awareness, and the fusion of LiDAR and monocular vision is widely used in near-field perception scenarios. However, this strategy of fusing data from LiDAR and monocular vision may lead to the incorrect matching of image targets and LiDAR point cloud targets when targets occlude one another. To address this issue, a target matching network with an attention module was developed to process occlusion information. Additionally, an image target occlusion detection branch was incorporated into YOLOv9 to extract the occlusion relationships of the image targets. The introduction of the attention module and the occlusion detection branch allows for the consideration of occlusion information in matching point cloud and image targets, thereby achieving more accurate target matching. Based on the target matching network, a method for water surface target detection and multi-target tracking was proposed. This method fuses LiDAR point cloud and image data while considering occlusion information. Its effectiveness was confirmed through experimental verification. The experimental results show that the proposed method improved the correct matching rate in complex scenarios by 13.83% compared to IoU-based target matching methods, with an MOTA metric of 0.879 and an average frame rate of 21.98. The results demonstrate that the method effectively reduces the mismatch rate between point cloud and image targets. The method’s frame rate meets real-time requirements, and the method itself offers a promising solution for unmanned surface vehicles (USVs) to perform water surface target detection and multi-target tracking. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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16 pages, 562 KiB

Open AccessArticle

Adaptive Transmission Interval-Based Self-Triggered Model Predictive Control for Autonomous Underwater Vehicles with Additional Disturbances

by Pengyuan Zhang, Liying Hao and Runzhi Wang

J. Mar. Sci. Eng. 2024, 12(9), 1489; https://doi.org/10.3390/jmse12091489 - 28 Aug 2024

Viewed by 831

Abstract

Most existing model predictive control (MPC) methods overlook the network resource limitations of autonomous underwater vehicles (AUVs), limiting their applicability in real systems. This article addresses this gap by introducing an adaptive transmission, interval-based, and self-triggered model predictive control for AUVs operating under [...] Read more.

Most existing model predictive control (MPC) methods overlook the network resource limitations of autonomous underwater vehicles (AUVs), limiting their applicability in real systems. This article addresses this gap by introducing an adaptive transmission, interval-based, and self-triggered model predictive control for AUVs operating under ocean disturbances. This approach enhances system stability while reducing resource consumption by optimizing MPC update frequencies and communication resource usage. Firstly, the method evaluates the discrepancy between system states at sampling instants and their optimal predictions. This significantly reduces the conservatism in the state-tracking errors caused by ocean disturbances compared to traditional approaches. Secondly, a self-triggering mechanism was employed, limiting information exchange to specified triggering instants to conserve communication resources more effectively. Lastly, by designing a robust terminal region and optimizing parameters, the recursive feasibility of the optimization problem is ensured, thereby maintaining the stability of the closed-loop system. The simulation results illustrate the efficacy of the controller. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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19 pages, 1511 KiB

Open AccessArticle

Underwater Long Baseline Positioning Based on B-Spline Surface for Fitting Effective Sound Speed Table

by Yao Xing, Jiongqi Wang, Bowen Hou, Zhangming He and Xuanying Zhou

J. Mar. Sci. Eng. 2024, 12(8), 1429; https://doi.org/10.3390/jmse12081429 - 19 Aug 2024

Cited by 2 | Viewed by 1115

Abstract

Due to the influence of the complex underwater environment, the sound speed constantly changes, resulting in the acoustic signal propagation trajectory being curved, which greatly affects the positioning accuracy of the underwater long baseline (LBL) system. In this paper, an improved LBL positioning [...] Read more.

Due to the influence of the complex underwater environment, the sound speed constantly changes, resulting in the acoustic signal propagation trajectory being curved, which greatly affects the positioning accuracy of the underwater long baseline (LBL) system. In this paper, an improved LBL positioning method based on a B-spline surface for fitting the effective sound speed table (ESST) is proposed. Firstly, according to the underwater sound speed profile, the discrete ESST of each measurement station is constructed before the positioning test, and then, the node position of the B-spline surface is optimized by particle swarm optimization (PSO) to accurately fit the discrete ESST. Based on this, the improved LBL positioning method is constructed. In the underwater positioning test, the effective sound speed can be quickly found by measuring the time of arrival (TOA) of the acoustic signal and the target depth, and moreover, the target position parameters can be quickly and accurately estimated. The numerical simulation results show that the improved positioning method proposed in this paper can effectively improve the LBL positioning accuracy and provide the theoretical basis and the technical support for the underwater navigation and positioning. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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21 pages, 821 KiB

Open AccessArticle

Fuzzy Fault Detection Observer Design for Unmanned Marine Vehicles Based on Membership-Function-Dependent H_∞/H_ Performance

by Yue Wu, Yang Wang, Kai Zhang, Shanfeng Zhang and Ying Wu

J. Mar. Sci. Eng. 2024, 12(8), 1288; https://doi.org/10.3390/jmse12081288 - 31 Jul 2024

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Abstract

This paper studies the design problem of fault detection (FD) observer for unmanned marine vehicles (UMVs) based on the T-S fuzzy model. Firstly, T-S fuzzy systems are used to approximate the nonlinear dynamics in UMVs. Secondly, to improve the FD performance of UMVs, [...] Read more.

This paper studies the design problem of fault detection (FD) observer for unmanned marine vehicles (UMVs) based on the T-S fuzzy model. Firstly, T-S fuzzy systems are used to approximate the nonlinear dynamics in UMVs. Secondly, to improve the FD performance of UMVs, a new

H_{\infty} / H_

performance index, which depends on the membership functions, is defined. Then, based on the membership-function-dependent

H_{\infty} / H_

performance index, a new fuzzy FD observer strategy, where the fuzzy submodels are not all required to be with the same

H_

performance index, is developed to detect the sensor fault in UMVs; the corresponding synthesis conditions of the FD observer are derived based on the Lyapunov theory. Different from the conventional FD strategies, in the proposed membership-function-dependent FD method, the fuzzy submodels—which the system always works on—can have a larger

H_

performance index, such that the performance of the FD can be improved. In the end, an example is given to show the effectiveness of the presented method. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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26 pages, 5789 KiB

Open AccessArticle

Adaptive Distributed Heterogeneous Formation Control for UAV-USVs with Input Quantization

by Jun Ning, Yuyang Huang, Zihan Liu, Wei Li and Xingwang Yue

J. Mar. Sci. Eng. 2024, 12(6), 975; https://doi.org/10.3390/jmse12060975 - 11 Jun 2024

Cited by 2 | Viewed by 1320

Abstract

This paper investigates the cooperative formation trajectory tracking problem for heterogeneous unmanned aerial vehicle (UAV) and multiple unmanned surface vessel (USV) systems with input quantization performance. Firstly, at the kinematic level, a distributed guidance law based on an extended state observer (ESO) is [...] Read more.

This paper investigates the cooperative formation trajectory tracking problem for heterogeneous unmanned aerial vehicle (UAV) and multiple unmanned surface vessel (USV) systems with input quantization performance. Firstly, at the kinematic level, a distributed guidance law based on an extended state observer (ESO) is designed to compensate for the unknown speed of neighbor agents for expected trajectory tracking, and subsequently at the dynamic level, an ESO is utilized to estimate model uncertainties and environmental disturbances. Following that, a linear analytic model is employed to depict the input quantization process, and the corresponding adaptive quantization controller is designed without necessitating prior information on quantization parameters. Based on the input-to-state stability, the stability of the proposed control structure is proved, and all the signals in the closed-loop system are ultimately bounded. Finally, a simulation study is provided to show the efficacy of the proposed strategy. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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22 pages, 1457 KiB

Open AccessArticle

Integral Sliding Mode Output Feedback Control for Unmanned Marine Vehicles Using T–S Fuzzy Model with Unknown Premise Variables and Actuator Faults

by Yang Wang, Xin Yang, Liying Hao, Tieshan Li and C. L. (Philip) Chen

J. Mar. Sci. Eng. 2024, 12(6), 920; https://doi.org/10.3390/jmse12060920 - 30 May 2024

Cited by 4 | Viewed by 1058

Abstract

This paper addresses integral sliding mode output feedback fault-tolerant control (FTC) of unmanned marine vessels (UMVs) with unknown premise variables and actuator faults. Due to the complexity of the marine environment, the presence of uncertainties in the yaw angle renders the premise variables [...] Read more.

This paper addresses integral sliding mode output feedback fault-tolerant control (FTC) of unmanned marine vessels (UMVs) with unknown premise variables and actuator faults. Due to the complexity of the marine environment, the presence of uncertainties in the yaw angle renders the premise variables in the Takagi–Sugeno (T–S) fuzzy model of UMVs unknown. Consequently, traditional integral sliding mode techniques become infeasible. To address this issue, a control strategy combining integral sliding mode based on output feedback with a compensator utilizing switching mechanisms is proposed. First, a radial basis function neural network is used to approximate the nonlinear terms in the UMV T–S fuzzy model. In addition, an integral sliding mode surface is constructed based on fault estimation information and membership function estimation. On this basis, an FTC scheme based on integral sliding mode output feedback is developed to ensure that the UMV system is asymptotically stable and satisfies the prescribed

H_{\infty}

performance index. Finally, simulation results are provided to demonstrate the effectiveness of the presented control strategy. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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20 pages, 3583 KiB

Open AccessArticle

FSN-YOLO: Nearshore Vessel Detection via Fusing Receptive-Field Attention and Lightweight Network

by Na Du, Qing Feng, Qichuang Liu, Hui Li and Shikai Guo

J. Mar. Sci. Eng. 2024, 12(6), 871; https://doi.org/10.3390/jmse12060871 - 24 May 2024

Cited by 4 | Viewed by 1555

Abstract

Vessel detection is critical for ensuring maritime transportation and navigational safety, creating a pressing need for detection methodologies that are more efficient, precise, and intelligent in the maritime domain. Nonetheless, accurately detecting vessels across multiple scales remains challenging due to the diversity in [...] Read more.

Vessel detection is critical for ensuring maritime transportation and navigational safety, creating a pressing need for detection methodologies that are more efficient, precise, and intelligent in the maritime domain. Nonetheless, accurately detecting vessels across multiple scales remains challenging due to the diversity in vessel types and locations, similarities in ship hull shapes, and disturbances from complex environmental conditions. To address these issues, we introduce an innovative FSN-YOLO framework that utilizes enhanced YOLOv8 with multi-layer attention feature fusion. Specifically, FSN-YOLO employs the backbone structure of FasterNet, enriching feature representations through super-resolution processing with a lightweight Convolutional Neural Network (CNN), thereby achieving a balance between processing speed and model size without compromising accuracy. Furthermore, FSN-YOLO uses the Receptive-Field Attention (RFA) mechanism to adaptively fine-tune the feature responses between channels, significantly boosting the network’s capacity to capture critical information and, in turn, improve the model’s overall performance and enrich the discriminative feature representation of ships. Experimental validation on the Seaship7000 dataset showed that, compared to the baseline YOLOv8l approach, FSN-YOLO considerably increased accuracy, recall rates, and mAP@0.5:0.95 by absolute margins of 0.82%, 1.54%, and 1.56%, respectively, positioning it at the forefront of current state-of-the-art models. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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15 pages, 3672 KiB

Open AccessArticle

Research on the Influencing Factors of AUV Hovering Control in Null-Speed State

by Jianguo Wang, Chunmeng Jiang, Lei Wan, Yimei Zhou, Gangyi Hu, Xide Cheng and Gongxing Wu

J. Mar. Sci. Eng. 2024, 12(5), 725; https://doi.org/10.3390/jmse12050725 - 27 Apr 2024

Cited by 2 | Viewed by 1261

Abstract

Intelligent underwater vehicles hover by way of a hovering control system. To provide design inputs and maneuver guidance, this study focused on the characteristics of intelligent underwater vehicles during hovering control with the propulsion system shut down, established a mathematical model of hovering [...] Read more.

Intelligent underwater vehicles hover by way of a hovering control system. To provide design inputs and maneuver guidance, this study focused on the characteristics of intelligent underwater vehicles during hovering control with the propulsion system shut down, established a mathematical model of hovering control and determined injection and drainage functions based on optimal control theory. From analysis simulation experiments, the influence laws of control parameters, control timing and rate of injection and drainage control upon hovering control were deduced. It is proposed that, at the time of control parameter selection, the continuous injection and drainage rate at each time should be reduced as far as possible to relieve the demand on the volume of the reservoir when the requirement of depth control accuracy has been satisfied. In addition, the injection and drainage control should initiate when depth changes exceed 0.5 m. Suggestions are included on the minimum injection and drainage rate required for different initial disturbances. The proposed suggestions guide the design of hovering control systems and hovering control over intelligent underwater vehicles. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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Review

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21 pages, 912 KiB

Open AccessReview

Applications of Voronoi Diagrams in Multi-Robot Coverage: A Review

by Meng Zhou, Jianyu Li, Chang Wang, Jing Wang and Li Wang

J. Mar. Sci. Eng. 2024, 12(6), 1022; https://doi.org/10.3390/jmse12061022 - 19 Jun 2024

Cited by 4 | Viewed by 3296

Abstract

In recent decades, multi-robot region coverage has played an important role in the fields of environmental sensing, target searching, etc., and it has received widespread attention worldwide. Due to the effectiveness in segmenting nearest regions, Voronoi diagrams have been extensively used in recent [...] Read more.

In recent decades, multi-robot region coverage has played an important role in the fields of environmental sensing, target searching, etc., and it has received widespread attention worldwide. Due to the effectiveness in segmenting nearest regions, Voronoi diagrams have been extensively used in recent years for multi-robot region coverage. This paper presents a survey of recent research works on region coverage methods within the framework of the Voronoi diagram, to offer a perspective for researchers in the multi-robot cooperation domain. First, some basic knowledge of the Voronoi diagram is introduced. Then, the region coverage issue under the Voronoi diagram is categorized into sensor coverage and task execution coverage problems, respectively, considering the sensor range parameter. Furthermore, a detailed analysis of the application of Voronoi diagrams to the aforementioned two problems is provided. Finally, some conclusions and potential further research perspectives in this field are given. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)

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