Control, Guidance, Coordination, and Localization of Autonomous Marine Vehicles

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 (10 February 2022) | Viewed by 24574

Special Issue Editors


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Guest Editor
Technology and Science, Institute for Systems and Computer Engineering, 4200-465 Porto, Portugal
Interests: marine robotics; autonomous underwater vehicle (AUV); autonomous surface vehicles (ASV); guidance; control; coordination; localization; estimation; sensing
Special Issues, Collections and Topics in MDPI journals
Technology and Science, Institute for Systems and Computer Engineering, 4200-465 Porto, Portugal
Interests: marine robotics; adaptive sampling; control; guidance; autonomous underwater vehicles (AUV); autonomous surface vehicles (ASV); underwater system design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Autonomous marine vehicles are means to deploy distributed sensors over aquatic domains to enrich knowledge on otherwise hard-to-reach or even unreachable places. Their use has been widely accepted by the scientific, military, and industrial communities to overcome many barriers (risks, economical, performance). However, aquatic environments pose singular constraints and extreme challenges that demand advanced techniques to enable fully autonomous operation of vehicles. These techniques are composed of, but not limited to, robust guidance and control laws relying on relative or absolute localization based on sensors fusion. These are critical modules that directly impact vehicle performance over an individual mission or on cooperative tasks handled by multiple vehicles.

This Special Issue aims at gathering recent advances on control, guidance, cooperation, and localization of autonomous marine vehicles. Original research papers describing new approaches to motion control, state estimation, and collaborative behaviors of autonomous marine vehicles as well as applications of advanced techniques to specific navigation problems, supported by experimental data, are encouraged. High-quality papers are welcome.


Dr. Bruno Miguel Ferreira
Prof. Dr. Nuno A. Cruz
Guest Editors

Manuscript Submission Information

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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

  • Localization
  • Control and guidance
  • Coordination
  • Mapping
  • Acoustic/visual/inertial navigation
  • Nonlinear control
  • Estimation

Published Papers (9 papers)

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Research

19 pages, 2715 KiB  
Article
Impacts of Discretization and Numerical Propagation on the Ability to Follow Challenging Square Wave Commands
by Sung Mo Koo, Henry Travis and Timothy Sands
J. Mar. Sci. Eng. 2022, 10(3), 419; https://doi.org/10.3390/jmse10030419 - 13 Mar 2022
Cited by 7 | Viewed by 2423
Abstract
This study determines the threshold for the computational rate of actuator motor controllers for unmanned underwater vehicles necessary to accurately follow discontinuous square wave commands. Motors must track challenging square-wave inputs, and identification of key computational rates permit application of deterministic artificial intelligence [...] Read more.
This study determines the threshold for the computational rate of actuator motor controllers for unmanned underwater vehicles necessary to accurately follow discontinuous square wave commands. Motors must track challenging square-wave inputs, and identification of key computational rates permit application of deterministic artificial intelligence (D.A.I.) to achieve tracking to a machine-precision degree of accuracy in direct comparison to other state-of-art approaches. All modeling approaches are validated in MATLAB simulations where the motor process is discretized at varying step-sizes (inversely proportional to computational rate). At a large step-size (fast computational rate), discrete D.A.I. shows a mean error more than three times larger than that of a ubiquitous model-following approach. Yet, at a smaller step size (slower computational rate), the mean error decreases by a factor of 10, only three percent larger than that of continuous D.A.I. Hence, the performance of discrete D.A.I. is critically affected by the sampling period for discretization of the system equations and computational rate. Discrete D.A.I. should be avoided when small step-size discretization is unavailable. In fact, continuous D.A.I. has surpassed all modeling approaches, which makes it the safest and most viable solution to future commercial applications in unmanned underwater vehicles. Full article
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17 pages, 7064 KiB  
Article
Position Correction and Trajectory Optimization of Underwater Long-Distance Navigation Inspired by Sea Turtle Migration
by Ziyuan Li, Huapeng Yu, Ye Li, Tongsheng Shen, Chongyang Wang and Zheng Cong
J. Mar. Sci. Eng. 2022, 10(2), 163; https://doi.org/10.3390/jmse10020163 - 27 Jan 2022
Viewed by 2686
Abstract
Accumulating evidence suggests that migrating animals store navigational “maps” in their brains, decoding location information from geomagnetic information based on their perception of the magnetic field. Inspired by this phenomenon, a novel geomagnetic inversion navigation framework was proposed to address the error constraint [...] Read more.
Accumulating evidence suggests that migrating animals store navigational “maps” in their brains, decoding location information from geomagnetic information based on their perception of the magnetic field. Inspired by this phenomenon, a novel geomagnetic inversion navigation framework was proposed to address the error constraint of a long-distance inertial navigation system. In the first part of the framework, the current paper proposed a geomagnetic bi-coordinate inversion localization approach which enables an autonomous underwater vehicle (AUV) to estimate its current position from geomagnetic information like migrating animals. This paper suggests that the combination of geomagnetic total intensity (F) and geomagnetic inclination (I) can determine a unique geographical location, and that there is a non-unique mapping relationship between the geomagnetic parameters and the geographical coordination (longitude and latitude). Then the cumulative error of the inertial navigation system is corrected, according to the roughly estimated position information. In the second part of the framework, a cantilever beam model is proposed to realize the optimal correction of the INS historical trajectory. Finally, the correctness of the geomagnetic bi-coordinate inversion localization model we proposed was verified by outdoor physical experiments. In addition, we also completed a geomagnetic/inertial navigation integrated long-distance semi-physical test based on the real navigation information of the AUV. The results show that the geomagnetic inversion navigation framework proposed in this paper can constrain long-distance inertial navigation errors and improve the navigation accuracy by 73.28% compared with the pure inertial navigation mode. This implies that the geomagnetic inversion localization will play a key role in long-distance AUV navigation correction. Full article
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20 pages, 3716 KiB  
Article
Distributed Consensus of USVs under Heterogeneous UAV-USV Multi-Agent Systems Cooperative Control Scheme
by Kai Xue and Tingyi Wu
J. Mar. Sci. Eng. 2021, 9(11), 1314; https://doi.org/10.3390/jmse9111314 - 22 Nov 2021
Cited by 23 | Viewed by 3623
Abstract
This paper addresses the formation motion control of heterogeneous multi-agent unmanned systems via a distributed consensus approach. The considered heterogeneous system consisted of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs). A leader-following consensus scheme and APF method are used to construct [...] Read more.
This paper addresses the formation motion control of heterogeneous multi-agent unmanned systems via a distributed consensus approach. The considered heterogeneous system consisted of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs). A leader-following consensus scheme and APF method are used to construct UAV-USVs Formation task requirements. A fuzzy-based sliding mode control approach is proposed to ensure the formation assembles in a finite time, and the finite-time stability is proved by the Lyapunov stability theorem. To highlight the cooperation within the heterogeneous systems, such as UAV and USV, a novel vision-based path re-planning approach is proposed. Simulation results confirm the efficiency of the proposed approach. Full article
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22 pages, 13802 KiB  
Article
Adaptive Digital Disturbance Rejection Controller Design for Underwater Thermal Vehicles
by Guohui Wang, Yanan Yang and Shuxin Wang
J. Mar. Sci. Eng. 2021, 9(4), 406; https://doi.org/10.3390/jmse9040406 - 11 Apr 2021
Cited by 2 | Viewed by 1940
Abstract
Underwater thermal vehicles, as ocean observation tools, are frequently affected by environment disturbances such as waves and currents, which may cause degradation of the observation accuracy of the vehicles. Consequently, it is important to design a controller for a vehicle that can resist [...] Read more.
Underwater thermal vehicles, as ocean observation tools, are frequently affected by environment disturbances such as waves and currents, which may cause degradation of the observation accuracy of the vehicles. Consequently, it is important to design a controller for a vehicle that can resist ocean disturbance. In this study, an underwater thermal vehicle principle is introduced, and the mathematical model is established in the vertical plane motion. On this basis, an adaptive digital disturbance suppression control method is proposed. For known disturbance parameters, this controller could compensate for external disturbances by pre-setting control parameters using the internal model principle and parameterizations method. For the case where the disturbance parameters are unknown, disturbance parameter estimation method based on forgetting factor least-squares method is proposed to transform the unknown parameter disturbance into a disturbance with known parameters, which is then suppressed by the adaptive digital disturbance rejection control approach. This solution could effectively solve the challenges caused by parameter uncertainty and unknown time-varying ocean external disturbances. Finally, simulations are carried out for the Petrel underwater thermal glider as an example. The simulation results show the proposed control method’s superiority and inherent robustness. Full article
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26 pages, 3043 KiB  
Article
A Performance Analysis of Feature Extraction Algorithms for Acoustic Image-Based Underwater Navigation
by António José Oliveira, Bruno Miguel Ferreira and Nuno Alexandre Cruz
J. Mar. Sci. Eng. 2021, 9(4), 361; https://doi.org/10.3390/jmse9040361 - 28 Mar 2021
Cited by 12 | Viewed by 2883
Abstract
In underwater navigation, sonars are useful sensing devices for operation in confined or structured environments, enabling the detection and identification of underwater environmental features through the acquisition of acoustic images. Nonetheless, in these environments, several problems affect their performance, such as background noise [...] Read more.
In underwater navigation, sonars are useful sensing devices for operation in confined or structured environments, enabling the detection and identification of underwater environmental features through the acquisition of acoustic images. Nonetheless, in these environments, several problems affect their performance, such as background noise and multiple secondary echoes. In recent years, research has been conducted regarding the application of feature extraction algorithms to underwater acoustic images, with the purpose of achieving a robust solution for the detection and matching of environmental features. However, since these algorithms were originally developed for optical image analysis, conclusions in the literature diverge regarding their suitability to acoustic imaging. This article presents a detailed comparison between the SURF (Speeded-Up Robust Features), ORB (Oriented FAST and Rotated BRIEF), BRISK (Binary Robust Invariant Scalable Keypoints), and SURF-Harris algorithms, based on the performance of their feature detection and description procedures, when applied to acoustic data collected by an autonomous underwater vehicle. Several characteristics of the studied algorithms were taken into account, such as feature point distribution, feature detection accuracy, and feature description robustness. A possible adaptation of feature extraction procedures to acoustic imaging is further explored through the implementation of a feature selection module. The performed comparison has also provided evidence that further development of the current feature description methodologies might be required for underwater acoustic image analysis. Full article
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18 pages, 9678 KiB  
Article
A Visual Analysis Approach to Understand and Explore Quality Problems of AIS Data
by Wei He, Jinyu Lei, Xiumin Chu, Shuo Xie, Cheng Zhong and Zhixiong Li
J. Mar. Sci. Eng. 2021, 9(2), 198; https://doi.org/10.3390/jmse9020198 - 13 Feb 2021
Cited by 12 | Viewed by 2880
Abstract
Low quality automatic identification system (AIS) data often mislead analysts to a misunderstanding of ship behavior analysis and to making incorrect navigation risk assessments. It is therefore necessary to accurately understand and judge the quality problems in AIS data before a further analysis [...] Read more.
Low quality automatic identification system (AIS) data often mislead analysts to a misunderstanding of ship behavior analysis and to making incorrect navigation risk assessments. It is therefore necessary to accurately understand and judge the quality problems in AIS data before a further analysis of ship behavior. Outliers were filtered in the existing methods of AIS quality analysis based only on mathematical models where AIS data related quality problems are not utilized and there is a lack of visual exploration. Thus, the human brain’s ability cannot be fully utilized to think visually and for reasoning. In this regard, a visual analytics (VA) approach called AIS Data Quality visualization (ADQvis) was designed and implemented here to support evaluations and explorations of AIS data quality. The system interface is overviewed and then the visualization model and corresponding human-computer interaction method are described in detail. Finally, case studies were carried out to demonstrate the effectiveness of our visual analytics approach for AIS quality problems. Full article
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23 pages, 494 KiB  
Article
Performance Analysis of Ice-Relative Upward-Looking Doppler Navigation of Underwater Vehicles Beneath Moving Sea Ice
by Laughlin D. L. Barker and Louis L. Whitcomb
J. Mar. Sci. Eng. 2021, 9(2), 174; https://doi.org/10.3390/jmse9020174 - 09 Feb 2021
Cited by 5 | Viewed by 1803
Abstract
This paper addresses the problem of ice-relative underwater robotic vehicle navigation relative to moving or stationary contiguous sea ice. A review of previously-reported under-ice navigation methods is given, as well as motivation for the use of under-ice robotic vehicles with precision navigation capabilities. [...] Read more.
This paper addresses the problem of ice-relative underwater robotic vehicle navigation relative to moving or stationary contiguous sea ice. A review of previously-reported under-ice navigation methods is given, as well as motivation for the use of under-ice robotic vehicles with precision navigation capabilities. We then describe our proposed approach, which employs two or more satellite navigation beacons atop the sea ice along with other precision vehicle and ship mounted navigation sensors to estimate vehicle, ice, and ship states by means of an Extended Kalman Filter. A performances sensitivity analysis for a simulated 7.7 km under ice survey is reported. The number and the location of ice deployed satellite beacons, rotational and translational ice velocity, and separation of ship-based acoustic range sensors are varied, and their effects on estimate error and uncertainty are examined. Results suggest that increasing the number and/or separation of ice-deployed satellite beacons reduces estimate uncertainty, whereas increasing separation of ship-based acoustic range sensors has little impact on estimate uncertainty. Decreasing ice velocity is also correlated with reduced estimate uncertainty. Our analysis suggests that the proposed method is feasible and can offer scientifically useful navigation accuracy over a range of operating conditions. Full article
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25 pages, 13420 KiB  
Article
A Unifying Task Priority Approach for Autonomous Underwater Vehicles Integrating Homing and Docking Maneuvers
by Cris Thomas, Enrico Simetti and Giuseppe Casalino
J. Mar. Sci. Eng. 2021, 9(2), 162; https://doi.org/10.3390/jmse9020162 - 05 Feb 2021
Cited by 7 | Viewed by 3459
Abstract
This research proposes a unified guidance and control framework for Autonomous Underwater Vehicles (AUVs) based on the task priority control approach, incorporating various behaviors such as path following, terrain following, obstacle avoidance, as well as homing and docking to stationary and moving stations. [...] Read more.
This research proposes a unified guidance and control framework for Autonomous Underwater Vehicles (AUVs) based on the task priority control approach, incorporating various behaviors such as path following, terrain following, obstacle avoidance, as well as homing and docking to stationary and moving stations. The integration of homing and docking maneuvers into the task priority framework is thus a novel contribution of this paper. This integration allows, for example, to execute homing maneuvers close to uneven seafloor or obstacles, ensuring the safety of the AUV, as safety tasks can be given the highest priority. Furthermore, another contribution shown in the paper is that the proposed approach tackles a wide range of scenarios without ad hoc solutions. Indeed, the proposed approach is well suited for both the emerging trend of resident AUVs, which stay underwater for a long period inside garage stations, exiting to perform inspection and maintenance missions and homing back to them, and for AUVs that are required to dock to moving stations such as surface vehicles, or towed docking stations. The proposed techniques are studied in a simulation setting, taking into account the rich number of aforementioned scenarios. Full article
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17 pages, 3648 KiB  
Article
Pulse Ranging Method Based on Active Virtual Time Reversal in Underwater Multi-Path Channel
by Zhichen Zhang, Haiyan Wang and Haiyang Yao
J. Mar. Sci. Eng. 2020, 8(11), 883; https://doi.org/10.3390/jmse8110883 - 05 Nov 2020
Cited by 3 | Viewed by 1634
Abstract
Aiming at improving the accuracy of pulse ranging measurement in underwater multi-path environment, this paper proposes a novel pulse ranging algorithm based on active virtual time reversal (AVTR). By using the focusing characteristics of AVTR, the received signal can be focused at the [...] Read more.
Aiming at improving the accuracy of pulse ranging measurement in underwater multi-path environment, this paper proposes a novel pulse ranging algorithm based on active virtual time reversal (AVTR). By using the focusing characteristics of AVTR, the received signal can be focused at the receiving end, which eliminates the negative influence of multiple pseudo-peaks. In order to extract the received signal, we propose an energy-based adaptive windowed method which preserves the signal focus peak while truncates the side peak component. Numerical simulations are provided and outfield experiments are conducted. The results demonstrate the effectiveness of the proposed method comparing with correlation-based method. Full article
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