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Navigation and Localization for Autonomous Marine Vehicles
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Navigation and Localization for 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 July 2024) | Viewed by 9689

Special Issue Editor

Dr. David Moreno-Salinas

E-Mail Website
Guest Editor
Department of Computer Science and Automatic Control, Universidad Nacional de Educación a Distancia (UNED), 28040 Madrid, Spain
Interests: localization; control; sensor networks; marine vehicles; identification and modelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Marine robotics aims to design and develop systems, as well as to provide support to their operation, for scientific research and commercial applications. Recent advances in miniaturized sensors, energy-efficient actuators, and low-cost embedded computer systems are impacting the development of autonomous, remotely operated, and hybrid marine vehicles. Current technology is also enabling the operation of multiple marine vehicles working in cooperation by exploiting the availability of increasingly sophisticated technologies for underwater communication networks. At the core of this trend, navigation and localization of autonomous marine vehicles are key for the suitable and reliable development of missions at sea. Therefore, this Special Issue is focused on collecting the latest experiments, applications, advances, and challenges related to navigation and localization of autonomous, surface and underwater, marine vehicles.

Dr. David Moreno-Salinas
Guest Editor

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

  • autonomous underwater and surface vehicles (AUVs, USVs)
  • guidance, navigation and path planning
  • SLAM, localization and tracking
  • control, modelling and simulation
  • fault diagnosis and fault tolerance
  • sensor networks, underwater sensing
  • cooperative surface and underwater vehicles
  • machine learning methods for marine robotics
  • communication systems
  • applications, case studies, field trials, and experimental results

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Published Papers (7 papers)

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Research

30 pages, 8884 KiB  
Article
Improved Whale Optimization Algorithm for Maritime Autonomous Surface Ships Using Three Objectives Path Planning Based on Meteorological Data
by Gongxing Wu, Hongyang Li and Weimin Mo
J. Mar. Sci. Eng. 2024, 12(8), 1313; https://doi.org/10.3390/jmse12081313 - 3 Aug 2024
Viewed by 350
Abstract
In recent years, global trade volume has been increasing, and marine transportation plays a significant role here. In marine transportation, the choice of transportation route has been widely discussed. Minimizing fuel consumption, minimizing voyage time, and maximizing voyage security are concerns of the [...] Read more.
In recent years, global trade volume has been increasing, and marine transportation plays a significant role here. In marine transportation, the choice of transportation route has been widely discussed. Minimizing fuel consumption, minimizing voyage time, and maximizing voyage security are concerns of the International Maritime Organization (IMO) regarding Maritime Autonomous Surface Ships (MASS). These goals are contradictory and have not yet been effectively resolved. This paper describes the ship path-planning problem as a multi-objective optimization problem that considers fuel consumption, voyage time, and voyage security. The model considers wind and waves as marine environmental factors. Furthermore, this paper uses an improved Whale Optimization Algorithm to solve multi-objective problems. At the same time, it is compared to three advanced algorithms. Through seven three-objective test functions, the performance of the algorithm is tested and applied in path planning. The results indicate that the algorithm can effectively balance the fuel consumption, voyage time, and voyage security of the ship, offering reasonable paths. Full article
(This article belongs to the Special Issue Navigation and Localization for Autonomous Marine Vehicles)
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20 pages, 9230 KiB  
Article
Adaptive Cooperative Ship Identification for Coastal Zones Based on the Very High Frequency Data Exchange System
by Qing Hu, Meng’en Song, Di Zhang and Shuaiheng Huai
J. Mar. Sci. Eng. 2024, 12(8), 1264; https://doi.org/10.3390/jmse12081264 - 27 Jul 2024
Viewed by 449
Abstract
The International Telecommunication Union (ITU) proposed the very high frequency data exchange system (VDES) to improve the efficiency of ship–ship and ship–shore communication; however, its existing single-hop transmission mode is insufficient for identifying all ships within a coastal zone. This paper proposes an [...] Read more.
The International Telecommunication Union (ITU) proposed the very high frequency data exchange system (VDES) to improve the efficiency of ship–ship and ship–shore communication; however, its existing single-hop transmission mode is insufficient for identifying all ships within a coastal zone. This paper proposes an adaptive cooperative ship identification method based on the VDES using multihop transmission, where the coastal zone is divided into a grid, with the ships acting as nodes, and the optimal sink and relay nodes are calculated for each grid element. An adaptive multipath transmission protocol is then applied to improve the transmission efficiency and stability of the links between the nodes. Simulations were performed utilizing real Automatic Identification System (AIS) data from a coastal zone, and the results showed that the proposed method effectively reduced the time-slot occupancy and collision rate while achieving a 100% identification of ships within 120 nautical miles (nm) of the coast with only 4.8% of the usual communication resources. Full article
(This article belongs to the Special Issue Navigation and Localization for Autonomous Marine Vehicles)
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17 pages, 2524 KiB  
Article
Design and Development of an SVM-Powered Underwater Acoustic Modem
by Gabriel S. Guerrero-Chilabert, David Moreno-Salinas and José Sánchez-Moreno
J. Mar. Sci. Eng. 2024, 12(5), 773; https://doi.org/10.3390/jmse12050773 - 5 May 2024
Viewed by 768
Abstract
Underwater acoustic communication is fraught with challenges, including signal distortion, noise, and interferences unique to aquatic environments. This study aimed to advance the field by developing a novel underwater modem system that utilizes machine learning for signal classification, enhancing the reliability and clarity [...] Read more.
Underwater acoustic communication is fraught with challenges, including signal distortion, noise, and interferences unique to aquatic environments. This study aimed to advance the field by developing a novel underwater modem system that utilizes machine learning for signal classification, enhancing the reliability and clarity of underwater transmissions. This research introduced a system architecture incorporating a Lattice Semiconductors FPGA for signal modulation and a half-pipe waveguide to emulate the underwater environment. For signal classification, support vector machines (SVMs) were leveraged with the continuous wavelet transform (CWT) employed for feature extraction from acoustic signals. Comparative analysis with traditional signal processing techniques highlighted the efficacy of the CWT in this context. The experiments and tests carried out with the system demonstrated superior performance in classifying modulated signals under simulated underwater conditions, with the SVM providing a robust classification despite the presence of noise. The use of the CWT for feature extraction significantly enhanced the model’s accuracy, eliminating the need for further dimensionality reduction. Therefore, the integration of machine learning with advanced signal processing techniques presents a promising research line for overcoming the complexities of underwater acoustic communication. The findings underscore the potential of data mining methodologies to improve signal clarity and transmission reliability in aquatic environments. Full article
(This article belongs to the Special Issue Navigation and Localization for Autonomous Marine Vehicles)
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17 pages, 6409 KiB  
Article
Collaborative Path Planning of Multiple AUVs Based on Adaptive Multi-Population PSO
by Liwei Zhi and Yi Zuo
J. Mar. Sci. Eng. 2024, 12(2), 223; https://doi.org/10.3390/jmse12020223 - 26 Jan 2024
Cited by 2 | Viewed by 1182
Abstract
Collaborative operations of multiple AUVs have been becoming increasingly popular and efficient in underwater tasks of marine applications. Autonomous navigation capability and cooperative control stability of multiple AUVs are crucial and challenging issues in underwater environments. To address the collaborative problem of path [...] Read more.
Collaborative operations of multiple AUVs have been becoming increasingly popular and efficient in underwater tasks of marine applications. Autonomous navigation capability and cooperative control stability of multiple AUVs are crucial and challenging issues in underwater environments. To address the collaborative problem of path planning for multiple AUVs, this paper proposes an adaptive multi-population particle swarm optimization (AMP-PSO). In AMP-PSO, we design a grouping strategy of multi-population and an exchanging mechanism of particles between groups. We separate particles into one leader population and various follower populations according to their fitness. Firstly, in the grouping strategy, particles within the leader population are updated by both the leader population and follower populations so as to keep global optimization, while particles within the follower population are updated by their own group so as to keep local priority. Secondly, in the exchanging mechanism, particles are exchanged between the leader population and follower populations so as to improve multi-population diversity. To accommodate multi-population characteristics, an adaptive parameter configuration is also included to enhance the global search capability, convergence speed, and complex environment adaptability of AMP-PSO. In numerical experiments, we simulate various scenarios of collaborative path planning of multiple AUVs in an underwater environment. The simulation results convincingly demonstrate that AMP-PSO can obtain feasible and optimal path solutions compared to classic PSO and other improved PSO, which enable multiple AUVs to effectively achieve objectives under the conditions of collision avoidance and navigation constraint. Full article
(This article belongs to the Special Issue Navigation and Localization for Autonomous Marine Vehicles)
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18 pages, 2228 KiB  
Article
Robust Model Predictive Control Based on Active Disturbance Rejection Control for a Robotic Autonomous Underwater Vehicle
by Jaime Arcos-Legarda and Álvaro Gutiérrez
J. Mar. Sci. Eng. 2023, 11(5), 929; https://doi.org/10.3390/jmse11050929 - 26 Apr 2023
Cited by 9 | Viewed by 2437
Abstract
This work aims to develop a robust model predictive control (MPC) based on the active disturbance rejection control (ADRC) approach by using a discrete extended disturbance observer (ESO). The proposed technique uses the ADRC approach to lump disturbances and uncertainties into a total [...] Read more.
This work aims to develop a robust model predictive control (MPC) based on the active disturbance rejection control (ADRC) approach by using a discrete extended disturbance observer (ESO). The proposed technique uses the ADRC approach to lump disturbances and uncertainties into a total disturbance, which is estimated with a discrete ESO and rejected through feedback control. Thus, the effects of the disturbances are attenuated, and a model predictive control is designed based on a canonical model free of uncertainties and disturbances. The proposed control technique is tested through simulation into a robotic autonomous underwater vehicle (AUV). The AUV’s dynamic model is used to compare the performance of a classical MPC and the combined MPC-ADRC. The evaluation results show evidence of the superiority of the MPC-ADRC over the classical MPC under tests of reference tracking, external disturbances rejection, and model uncertainties attenuation. Full article
(This article belongs to the Special Issue Navigation and Localization for Autonomous Marine Vehicles)
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20 pages, 3463 KiB  
Article
An Efficient Underwater Navigation Method Using MPC with Unknown Kinematics and Non-Linear Disturbances
by Pablo Barreno, Juan Parras and Santiago Zazo
J. Mar. Sci. Eng. 2023, 11(4), 710; https://doi.org/10.3390/jmse11040710 - 25 Mar 2023
Cited by 1 | Viewed by 1260
Abstract
Many Autonomous Underwater Vehicles (AUVs) need to cope with hazardous underwater medium using a limited computational capacity while facing unknown kinematics and disturbances. However, most algorithms proposed for navigation in such conditions fail to fulfil all conditions at the same time. In this [...] Read more.
Many Autonomous Underwater Vehicles (AUVs) need to cope with hazardous underwater medium using a limited computational capacity while facing unknown kinematics and disturbances. However, most algorithms proposed for navigation in such conditions fail to fulfil all conditions at the same time. In this work, we propose an optimal control method, based on a receding horizon approach, namely MPC (Model Predictive Control). Our model also estimates the kinematics of the medium and its disturbances, using efficient tools that rely on the use of linear algebra and first-order optimization methods. We also test our ideas using an extensive set of simulations, which show that the proposed ideas are very competitive in terms of cost and computational efficiency in cases of total and partial observability. Full article
(This article belongs to the Special Issue Navigation and Localization for Autonomous Marine Vehicles)
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9 pages, 2105 KiB  
Article
Underwater Positioning System Based on Drifting Buoys and Acoustic Modems
by Pablo Otero, Álvaro Hernández-Romero, Miguel-Ángel Luque-Nieto and Alfonso Ariza
J. Mar. Sci. Eng. 2023, 11(4), 682; https://doi.org/10.3390/jmse11040682 - 23 Mar 2023
Cited by 5 | Viewed by 1911
Abstract
GNSS (Global Navigation Satellite System) positioning is not available underwater due to the very short range of electromagnetic waves in the sea water medium. In this article a LBL (Long Base Line) acoustic repeater system of the GNSS positioning is presented. The system [...] Read more.
GNSS (Global Navigation Satellite System) positioning is not available underwater due to the very short range of electromagnetic waves in the sea water medium. In this article a LBL (Long Base Line) acoustic repeater system of the GNSS positioning is presented. The system is hyperbolic, i.e., based on time differences and it does not need very accurate atomic clocks to synchronize repeaters. The system architecture and system calculations that demonstrate the feasibility of the solution are presented. The system uses four buoys that sequentially transmit their position and the time of the instant of transmission, for which they are equipped with GNSS receivers and acoustic modems. The buoys can be fixed or even drifting, but they are inexpensive devices, which pose no hazard to navigation and can be easily and quickly deployed for a specific underwater mission. The multilateration algorithm used in the receiver is presented. To simplify the algorithm, the depth of the receiver, measured by a depth sensor, is used. Results are presented for the position error of an underwater vehicle due to its displacement during the transmission frame of the four buoys. Full article
(This article belongs to the Special Issue Navigation and Localization for Autonomous Marine Vehicles)
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