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Control and Navigation of Underwater Robot Systems
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Control and Navigation of Underwater Robot Systems

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 (15 February 2024) | Viewed by 6884

Special Issue Editors

Dr. Lei Zhang

E-Mail Website
Guest Editor
Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China
Interests: control and navigation; formation cooperation control
Dr. Bing Huang

E-Mail Website
Guest Editor
School of Naval Engineering, Harbin Engineering University, Harbin, China
Interests: control theory; formation cooperation control

Special Issue Information

Dear Colleagues,

In recent years, emerging intelligent Marine Robotic (MR) technology has been developed and used for missions such as environmental monitoring, marine culture, ocean exploration, reconnaissance and rescue. Meanwhile, various aspects of MR systems need to be improved, wherein. However, the complexities and uncertainties of marine operating environments in conjunction with the system constraints of MR are critical challenges in developing persistent and resilient navigation and control systems. To address these challenges, this Special Issue gathers the latest research and development achievements in the field of control and navigation in intelligent MR technology to handle complex ocean missions, which are robust even without precise operational environment information and dynamic model information. Original papers that address the most current issues and challenges are solicited. Topics of interest include, but are not limited to:

  • Control and navigation for MR subject to unmodeled hydrodynamics;
  • Control and navigation for MR subject to limited communication bandwidth;
  • Control and navigation for MR subject to GPS-denied zones;
  • Control and navigation for MR subject to actuator failures;
  • Control and navigation for MR subject to time-varying external disturbances;
  • Control and navigation for MR subject to state constraints;
  • Formation control for collaborative MR systems.

background:

In recent years, Marine Robotic (MR) technology has been developed and used for missions such as environmental monitoring, marine culture, ocean exploration, reconnaissance and rescue. Meanwhile, various aspects of MR systems need to be improved, wherein control and navigation are essential technologies .

aim and scope:

This Topical Collection is dedicated to addressing the key challenges of developing persistent and resilient navigation and control systems caused by the complexities and uncertainties of marine operating environments in conjunction with the system constraints of MR.

history:

Researchers aim to obtain a satisfactory control performance, and some useful control design tools have been widely constructed, involving sliding mode-based control, backstepping control, fault-tolerant control, prescribed performance control, and network-based control parts.

cutting-edge research:

To address these issues, researchers have adopted machine learning and computational intelligence-based techniques in recent years, which are robust even without precise operational environment information and dynamic model information.

what kind of paper we are looking for:

Topics of interest include, but are not limited to control and navigation of MR.

Dr. Lei Zhang
Dr. Bing Huang
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

  • control and navigation
  • marine robotic
  • formation control
  • complexities marine environments
  • system constraints

Published Papers (8 papers)

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Research

16 pages, 2775 KiB  
Article
Fixed-Time Path-Following-Based Underactuated Unmanned Surface Vehicle Dynamic Positioning Control
by Shuai Zheng, Yumin Su, Jiayuan Zhuang, Yueqi Tang and Guangjie Yi
J. Mar. Sci. Eng. 2024, 12(4), 551; https://doi.org/10.3390/jmse12040551 - 26 Mar 2024
Viewed by 632
Abstract
The development of dynamic positioning (DP) algorithms for an unmanned surface vehicle (USV) is attracting great interest, especially in support of complex missions such as sea rescue. In order to improve the simplicity of the algorithm, a DP algorithm based on its own [...] Read more.
The development of dynamic positioning (DP) algorithms for an unmanned surface vehicle (USV) is attracting great interest, especially in support of complex missions such as sea rescue. In order to improve the simplicity of the algorithm, a DP algorithm based on its own path following control ability is proposed. The algorithm divides the DP problem into two parts: path generation and path following. The key contribution is that the DP ability can be realized only by designing the path generation method, rather than a whole complex independent DP controller. This saves the computing power of the USV onboard computer and can effectively reduce the complexity of the algorithm. In addition, the fixed-time LOS guidance law is designed to improve the convergence rate of the system state in path-following control. The reasonable selection of speed and a heading controller ensures that the number of design parameters to be determined is at a low level. The above algorithms have been thoroughly evaluated and validated through extensive computer simulations, demonstrating their effectiveness in simulated and real marine environments. The simulation results verify the ability of the proposed algorithm to realize the dynamic positioning of USVs, and provide a practical scheme for the design of the dynamic positioning controller of USVs. Full article
(This article belongs to the Special Issue Control and Navigation of Underwater Robot Systems)
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15 pages, 6942 KiB  
Article
Underwater Terrain Matching Method Based on Pulse-Coupled Neural Network for Unmanned Underwater Vehicles
by Pengyun Chen, Zhiru Li, Guangqing Liu, Ziyi Wang, Jiayu Chen, Shangyao Shi, Jian Shen and Lizhou Li
J. Mar. Sci. Eng. 2024, 12(3), 458; https://doi.org/10.3390/jmse12030458 - 6 Mar 2024
Viewed by 679
Abstract
The positioning results of terrain matching in flat terrain areas will significantly deteriorate due to the influence of terrain nonlinearity and multibeam measurement noise. To tackle this problem, this study presents the Pulse-Coupled Neural Network (PCNN), which has been effectively utilized for image [...] Read more.
The positioning results of terrain matching in flat terrain areas will significantly deteriorate due to the influence of terrain nonlinearity and multibeam measurement noise. To tackle this problem, this study presents the Pulse-Coupled Neural Network (PCNN), which has been effectively utilized for image denoising. The interconnection of surface terrain data nodes is achieved through PCNN ignition, which serves to alleviate the reduction in terrain similarity caused by measurement error. This enables the efficient selection of terrain data, ensuring that points with high measurement accuracy are preserved for terrain matching and positioning operations. The simulation results illustrate that the suggested methodology effectively removes terrain data points with low measurement accuracy, thereby improving the performance of terrain matching and positioning. Full article
(This article belongs to the Special Issue Control and Navigation of Underwater Robot Systems)
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28 pages, 4999 KiB  
Article
Three-Dimensional Path Tracking of Over-Actuated AUVs Based on MPC and Variable Universe S-Plane Algorithms
by Feng Xu, Lei Zhang and Jibin Zhong
J. Mar. Sci. Eng. 2024, 12(3), 418; https://doi.org/10.3390/jmse12030418 - 27 Feb 2024
Viewed by 695
Abstract
Autonomous Underwater Vehicles (AUVs) are widely used for the inspection of seabed pipelines. To address the issues of low trajectory tracking accuracy in AUV inspection processes due to uncertain ocean current disturbances, this paper designs a new dual-loop controller based on Model Predictive [...] Read more.
Autonomous Underwater Vehicles (AUVs) are widely used for the inspection of seabed pipelines. To address the issues of low trajectory tracking accuracy in AUV inspection processes due to uncertain ocean current disturbances, this paper designs a new dual-loop controller based on Model Predictive Control (MPC) and Variable Universe S-plane algorithms (S-VUD FLC, where VUD represents Variable Universe Discourse and FLC represents Fuzzy Logic Control) to achieve three-dimensional (3-D) trajectory tracking of an over-actuated AUV under uncertain ocean current disturbances. This paper uses MPC as the outer-loop position controller and S-VUD FLC as the inner-loop speed controller. The outer-loop controller generates desired speed instructions that are passed to the inner-loop speed controller, while the inner-loop speed controller generates control input and uses a direct logic thrust distribution method that approaches optimal energy consumption to distribute the thrust generated by the propellers to the over-actuated AUV, achieving closed-loop tracking of the entire trajectory. When designing the outer-loop MPC controller, the actual control input constraints of the system are considered, and control increments are introduced to reduce control model errors and the impact of uncertain external disturbances on the actual AUV model parameters. When designing the inner-loop S-VUD FLC, the strong robustness of the variable universe fuzzy controller and the easy construction characteristics of the S-plane algorithm are combined, and integral action is introduced to improve the system’s tracking accuracy. The stability of the outer loop controller is proven by the Lyapunov method, and the stability of the inner loop controller is verified by simulation. Finally, simulations show that the over-actuated AUV has fast tracking processes and high tracking result accuracy under uncertain ocean current disturbances, demonstrating the effectiveness of the designed dual-loop controller. Full article
(This article belongs to the Special Issue Control and Navigation of Underwater Robot Systems)
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22 pages, 7292 KiB  
Article
Detection Technique Tailored for Small Targets on Water Surfaces in Unmanned Vessel Scenarios
by Jian Zhang, Wenbin Huang, Jiayuan Zhuang, Renran Zhang and Xiang Du
J. Mar. Sci. Eng. 2024, 12(3), 379; https://doi.org/10.3390/jmse12030379 - 23 Feb 2024
Cited by 1 | Viewed by 974
Abstract
Lightweight detection methods are frequently utilized for unmanned system sensing; however, to tackle the challenge of low precision in detecting small targets on the water’s surface by unmanned surface vessels, we present an enhanced method for ship target detection tailored specifically to this [...] Read more.
Lightweight detection methods are frequently utilized for unmanned system sensing; however, to tackle the challenge of low precision in detecting small targets on the water’s surface by unmanned surface vessels, we present an enhanced method for ship target detection tailored specifically to this context. Building upon the mainstream single-stage Yolov8 object detection model, our approach involves the integration of the Reparameterized Convolutional Spatial Oversampling Attention (RCSOSA) module, replacing the traditional Classic 2D Convolutional (C2f) module to bolster the network’s feature extraction capabilities. Additionally, we introduce a downsampling module, Spatial to Depth Convolution (SPDConv), to amplify the extraction of features relevant to small targets, thereby enhancing detection accuracy. Finally, the Focal Modulation module, based on focal modulation, replaces the SPPF (Spatial Pyramid Pooling with FPN) module, leading to a reduction in channel count, parameter volume, and an augmentation of the network’s feature representation. Experimental results demonstrate that the proposed model achieves a 3.6% increase in [email protected] and a 2.1% improvement in [email protected]:0.95 compared to the original Yolov8 model, while maintaining real-time processing capabilities. The research validates the higher accuracy and stronger generalization capabilities of the proposed improved ship target detection method in various complex water surface environments. Full article
(This article belongs to the Special Issue Control and Navigation of Underwater Robot Systems)
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16 pages, 6368 KiB  
Article
Intelligent Task Allocation and Planning for Unmanned Surface Vehicle (USV) Using Self-Attention Mechanism and Locking Sweeping Method
by Jing Luo, Yuhang Zhang, Jiayuan Zhuang and Yumin Su
J. Mar. Sci. Eng. 2024, 12(1), 179; https://doi.org/10.3390/jmse12010179 - 17 Jan 2024
Viewed by 864
Abstract
The development of intelligent task allocation and path planning algorithms for unmanned surface vehicles (USVs) is gaining significant interest, particularly in supporting complex ocean operations. This paper proposes an intelligent hybrid algorithm that combines task allocation and path planning to improve mission efficiency. [...] Read more.
The development of intelligent task allocation and path planning algorithms for unmanned surface vehicles (USVs) is gaining significant interest, particularly in supporting complex ocean operations. This paper proposes an intelligent hybrid algorithm that combines task allocation and path planning to improve mission efficiency. The algorithm introduces a novel approach based on a self-attention mechanism (SAM) for intelligent task allocation. The key contribution lies in the integration of an adaptive distance field, created using the locking sweeping method (LSM), into the SAM. This integration enables the algorithm to determine the minimum practical sailing distance in obstacle-filled environments. The algorithm efficiently generates task execution sequences in cluttered maritime environments with numerous obstacles. By incorporating a safety parameter, the enhanced SAM algorithm adapts the dimensional influence of obstacles and generates paths that ensure the safety of the USV. The algorithms have been thoroughly evaluated and validated through extensive computer-based simulations, demonstrating their effectiveness in both simulated and practical maritime environments. The results of the simulations verify the algorithm’s capability to optimize task allocation and path planning, leading to improved performance in complex and obstacle-laden scenarios. Full article
(This article belongs to the Special Issue Control and Navigation of Underwater Robot Systems)
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15 pages, 3032 KiB  
Article
Trajectory-Following Control of an Unmanned Aerial–Aquatic Vehicle under Complex Coupling Interferences
by Jian Cao, Jiayuan Mao, Yueming Li, Le Wang and Biao Cao
J. Mar. Sci. Eng. 2024, 12(1), 60; https://doi.org/10.3390/jmse12010060 - 26 Dec 2023
Viewed by 765
Abstract
This article explores trajectory-following control for an unmanned aerial–aquatic vehicle (UAAV) navigating complex ocean disturbances and the interplay of air–seawater coupling factors. First, leveraging the backstepping technology, an adaptive algorithm is proposed to tackle the attitude and position following. Additionally, a nonlinear observer [...] Read more.
This article explores trajectory-following control for an unmanned aerial–aquatic vehicle (UAAV) navigating complex ocean disturbances and the interplay of air–seawater coupling factors. First, leveraging the backstepping technology, an adaptive algorithm is proposed to tackle the attitude and position following. Additionally, a nonlinear observer is crafted to estimate complex ocean disturbances. The UAAV model, characterized by six degrees of freedom (DOF) and nonlinear properties, experiences significant pose changes when emerging from water, underscoring the critical importance of precise pose control. Finally, stability analysis and numerical simulations are demonstrated to verify the feasibility and validity of the proposed control strategies. Full article
(This article belongs to the Special Issue Control and Navigation of Underwater Robot Systems)
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19 pages, 5795 KiB  
Article
Transmedia Performance Research and Motion Control of Unmanned Aerial–Aquatic Vehicles
by Xiangren Sun, Jian Cao, Yueming Li, Haipeng Li and Weikai Wang
J. Mar. Sci. Eng. 2024, 12(1), 51; https://doi.org/10.3390/jmse12010051 - 25 Dec 2023
Viewed by 817
Abstract
This paper presents an improved motion controller based on the backstepping method to address nonlinear control challenges in unmanned aerial–aquatic vehicles (UAAVs), enabling them to navigate between two different media. The nonlinear control approach is applied to UAAV motion control, incorporating filters to [...] Read more.
This paper presents an improved motion controller based on the backstepping method to address nonlinear control challenges in unmanned aerial–aquatic vehicles (UAAVs), enabling them to navigate between two different media. The nonlinear control approach is applied to UAAV motion control, incorporating filters to improve stability. The study designs motion controllers for three UAAV phases: underwater, in the air, and transitioning between media. Fluid simulations of the emergence process of the UAAV for future field experiments were conducted. By fine-tuning the simulations, a comprehensive understanding of the vehicle’s performance is obtained, offering crucial insights for the development of subsequent control systems. Simulation results confirm the controller’s ability to achieve target trajectory tracking with control system responses that meet practical requirements. The controller’s performance in attitude control and trajectory tracking is verified in underwater gliding, transmedia transitions, and airborne phases, demonstrating its effectiveness. Full article
(This article belongs to the Special Issue Control and Navigation of Underwater Robot Systems)
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17 pages, 2417 KiB  
Article
Objective Prediction Tracking Control Technology Assisted by Inertial Information
by Yue Leng and Sheng Zhong
J. Mar. Sci. Eng. 2023, 11(11), 2175; https://doi.org/10.3390/jmse11112175 - 15 Nov 2023
Viewed by 776
Abstract
This paper addresses the challenge of reduced tracking accuracy in maritime electro-optical tracking equipment when dealing with high-mobility targets like speedboats and aircraft due to off-target error delays. We propose an innovative technique that leverages inertial navigation data to enhance target prediction and [...] Read more.
This paper addresses the challenge of reduced tracking accuracy in maritime electro-optical tracking equipment when dealing with high-mobility targets like speedboats and aircraft due to off-target error delays. We propose an innovative technique that leverages inertial navigation data to enhance target prediction and tracking control. Our approach involves the real-time integration of high-frequency inertial navigation-derived attitude information into the tracking system. By combining off-target error information with angular measurements from the tracking mechanism, we project the vector of the tracked target into multiple coordinate systems, including the imaging coordinate system, carrier coordinate system, and geographic coordinate system. Subsequently, we model and predict the target’s motion trajectory in the relatively slow-changing geographic coordinate system. This transformation process increases the update frequency and real-time performance of the tracking control position loop command angle. Unlike traditional control methods that heavily rely on the model of the controlled object, our approach significantly improves tracking accuracy and engineering applicability. It offers a technology-based optimization of tracking and control performance through an interdisciplinary theoretical fusion, deeply integrating inertial navigation technology with tracking control technology. Experimental results with maritime electro-optical tracking equipment demonstrate that our proposed control technique increases tracking accuracy for high-speed targets by approximately threefold compared to traditional methods. Under the same experimental conditions, the off-target error statistics are reduced from 1.8 mrad to 633 μrad. Full article
(This article belongs to the Special Issue Control and Navigation of Underwater Robot Systems)
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