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Machines
Special Issues
Design and Application of Underwater Vehicles and Robots
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Design and Application of Underwater Vehicles and Robots

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 7425

Special Issue Editors

Prof. Dr. Tomás Salgado-Jiménez

E-Mail Website
Guest Editor
Center for Engineering and Industrial Development-CIDESI, Santiago de Queretaro, Queretaro 76125, Mexico
Interests: underwater robotics; gliders; autonomous underwater vehicle (auv); path planning; unmanned surface vehicles; path following; integrated navigation
Dr. Alfonso Gómez-Espinosa

E-Mail Website
Guest Editor
Tecnologico de Monterrey, Campus Queretaro, Ave. Epigmenio González 500, Fracc. San Pablo, Santiago de Queretaro, Queretaro 76130, Mexico
Interests: automation; control systems; artificial intelligence; robotics

Special Issue Information

Dear Colleagues,

Autonomous underwater vehicles (AUVs) are a challenging issue of modern robotic science. AUVs are an extremely heterogeneous group of vehicles of various sizes that are able to operate in a submarine environment with a certain degree of autonomy. In some applications, an AUV is more often referred to as an unmanned undersea vehicle (UUV). Underwater gliders are a subclass of AUVs.

The AUV category includes simple robots of a few decimetres to large complex systems that are several meters in length, and that are equipped with energy autonomy and controlled without cables.

This Special Issue will accept high-quality articles that contain original research results as well as review articles, and will allow readers to learn more about technologies related to the potentiality of AUVs, including, but not limited to, the following topics:

  • Autonomous underwater vehicles;
  • AUV design;
  • AUV control;
  • AUV guidance, navigation and path planning;
  • AUV attitude estimation;
  • Underwater target tracking;
  • Vehicle modeling and simulation;
  • Cooperative underwater vehicle manipulator systems;
  • Intelligence and autonomy for underwater robotic vehicles;
  • Underwater glider design and applications.

Prof. Dr. Tomás Salgado-Jiménez
Dr. Alfonso Gómez-Espinosa
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. Machines 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 2400 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.

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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15 pages, 7499 KiB  
Article
Optimized Hydrodynamic Design for Autonomous Underwater Vehicles
by Gang Fan, Xiaojin Liu, Yanan Hao, Guoling Yin and Long He
Machines 2025, 13(3), 194; https://doi.org/10.3390/machines13030194 - 28 Feb 2025
Viewed by 418
Abstract
In this study, the drag coefficient and lift-to-drag ratio variation with angle of attack and velocity are analyzed by numerical simulation of the hydrodynamics of the initial shape of an autonomous underwater vehicle (AUV). Based on this, the response surface method (RSM) and [...] Read more.
In this study, the drag coefficient and lift-to-drag ratio variation with angle of attack and velocity are analyzed by numerical simulation of the hydrodynamics of the initial shape of an autonomous underwater vehicle (AUV). Based on this, the response surface method (RSM) and multi-objective genetic algorithm (MOGA) are used to optimize the geometric parameters of the shape, aiming to improve the lift-to-drag ratio and reduce the mass. In the study, a second-order response surface model was constructed to analyze the relationship between the target variables and the structural geometric parameters, and the MOGA algorithm effectively searched for the globally optimal solution. The optimization results show that the lift-to-drag ratio is increased from 0.684 to 0.778 and the mass of the shell is reduced from 26.6 kg to 24.06 kg, which significantly improves the hydrodynamic performance of the AUV. The optimization method not only improves the performance of the AUV, but also provides a valuable reference for its hydrodynamic design, which has a good application prospect. Full article
(This article belongs to the Special Issue Design and Application of Underwater Vehicles and Robots)
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20 pages, 8820 KiB  
Article
Convolutional Long Short-Term Memory Predictor for Collaborative Remotely Operated Vehicle Trajectory Tracking in a Leader–Follower Formation Subject to Communication and Sensor Latency in the Presence of External Disturbances
by Milton Eduardo Pérez-Alvarado, Alfonso Gómez-Espinosa, Josué González-García, Luis Govinda García-Valdovinos and Tomás Salgado-Jiménez
Machines 2024, 12(10), 691; https://doi.org/10.3390/machines12100691 - 1 Oct 2024
Cited by 2 | Viewed by 916
Abstract
Nowadays, collaborative operations between Remotely Operated Vehicles (ROVs) face considerable challenges, particularly in leader–follower schemes. The underwater environment imposes limitations on acoustic modems, leading to reduced transmission speeds and increased latency in ROV position and speed transmission. This complicates effective communication between the [...] Read more.
Nowadays, collaborative operations between Remotely Operated Vehicles (ROVs) face considerable challenges, particularly in leader–follower schemes. The underwater environment imposes limitations on acoustic modems, leading to reduced transmission speeds and increased latency in ROV position and speed transmission. This complicates effective communication between the ROVs. Traditional methods, such as Recursive Least Squares (RLS) predictors and the Kalman filter, have been employed to address these issues. However, these approaches have limitations in handling non-linear patterns and disturbances in underwater environments. This paper introduces a Convolutional Long Short-Term Memory (ConvLSTM) predictor designed to enhance communication and trajectory tracking between ROVs in a leader–follower scheme. The proposed ConvLSTM aims to address the shortcomings of previous methods by adapting effectively to varying conditions, including ocean currents, communication delays, and signal interruptions. Simulations were conducted to evaluate ConvLSTM’s performance and compare it with other advanced predictors, such as Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM), under different conditions. The results demonstrated that ConvLSTM achieved a 13.9% improvement in trajectory tracking, surpassing other predictors in scenarios that replicate real underwater conditions and multi-vehicle communication. These results highlight ConvLSTM’s potential to significantly enhance the performance and stability of collaborative ROV operations in dynamic underwater environments. Full article
(This article belongs to the Special Issue Design and Application of Underwater Vehicles and Robots)
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Review

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32 pages, 1488 KiB  
Review
From Remote Sensing to Artificial Intelligence in Coral Reef Monitoring
by Victor J. Piñeros, Alicia Maria Reveles-Espinoza and Jesús A. Monroy
Machines 2024, 12(10), 693; https://doi.org/10.3390/machines12100693 - 1 Oct 2024
Cited by 3 | Viewed by 5098
Abstract
This review comprehensively covers the development of viable unmanned underwater vehicles based on their technical capabilities, in particular those designed to conduct research exploration in underwater ecosystems and address environmental issues through analysis of coral reef vulnerability. The most important elements to be [...] Read more.
This review comprehensively covers the development of viable unmanned underwater vehicles based on their technical capabilities, in particular those designed to conduct research exploration in underwater ecosystems and address environmental issues through analysis of coral reef vulnerability. The most important elements to be obtained are in situ data samples for analysis and characterization, supported by molecular biomarkers and marine ecology indicators. The following aspects are considered in this study: first, the geographic distribution of coral reefs for the study of marine ecology and molecular biological approaches for the detection of biomarkers to evaluate the vulnerability of coral reefs are detailed; then, the technologies currently available for the study of coral reefs are briefly described, ranging from large-scale capture to local-scale capture directly in the study region, taking advantage of remote sensing systems assisted by aerial technologies, marine vehicles, and artificial intelligence for the mapping, monitoring, and management of coral reefs as well as the characterization of their vulnerability; following this, existing marine vehicle technologies are generally explained, including a categorical description and an updated and highlighted list of innovative and robust marine vehicles that have been used in coral reef applications; the technical capabilities of such vehicle throughout the missions they have been subjected to are presented based on bibliographic references; finally, this review promotes multidisciplinary work to integrate the developments in the associated knowledge areas in order to obtain synergies in the face of challenges related to the massive scale of coral reef degradation worldwide. Full article
(This article belongs to the Special Issue Design and Application of Underwater Vehicles and Robots)
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