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Unmanned Underwater Vehicles (UUV)—Advances, Applications & Challenges

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 34571

Special Issue Editors


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Guest Editor
School of Computer Science and Engineering, University of Westminster, 115 New Cavendish Street, London W1W 6UW, UK
Interests: neural networks; fuzzy systems; genetic algorithms; hybrid systems; machine learning; image/signal processing; bio-signal analysis; chemometrics; control; non-invasive sensing systems; robotics
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Guest Editor
Electrical and Computer Engineering Department, Democritus University of Thrace, Xanthi, Greece
Interests: Electronics; Sensors; Embedded Systems; Robotics (undewater, aerial); Image & Signal Processing

Special Issue Information

Dear Colleagues,

Robotics has played a major role in subsea marine science, engineering, and operations since the introduction of Remotely Operated Vehicles (ROV). ROVs, which are tele-operated robotic systems are now the mainstream tool of subsea operations, enabling the performance of many tasks, from construction to inspection, repair and maintenance. During 1990s, torpedo-shaped Autonomous Vehicles (AUV) employed for a fast, large-scale and high-resolution surveys of the seabed. There is still a growing market for AUVs, since manned missions are very expensive. Such vehicles have found widespread applications in defense, oil & gas and cable surveying. However, they were not able to interact with structures for close-up inspection or manipulation. Therefore, the next efforts in UUV technology is focused on the development of intervention AUVs (I-AUVs) and hybrid ROV-AUVs (H-ROVs) equiped with manipulation capabilities. The domain of UUVs is still an area of ongoing research and although much advancement have been realized in this area, the need for advanced sensing systems, navigation, guidance and control systems for UUVs continues to grow as the demands increase for such vehicles to undertake more complex missions. Prospective authors are invited to submit their contributions for review for publication in this Special Issue and to share the cutting edge technology and novel ideas with other researchers and engineers.

Dr. Vassilis S. Kodogiannis
Prof. John Lygouras
Guest Editors

Manuscript Submission Information

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Keywords

Topics of this special issue will include, but are not limited to:

  • Unmanned Underwater Vehicles (ROV, AUV, etc),
  • Underwater Sensing, Multi-Modal Sensor Fusion, and Manipulation for UUVs
  • Vehicle Guidance, Navigation, Path Planning in UUVs
  • Control and Modeling for UUVs
  • Cooperative Underwater Vehicle Manipulator Systems
  • Networked UUVs
  • Intelligence and Autonomy for Underwater Robotic Vehicles
  • Machine Learning methods for Underwater Vehicles

Published Papers (9 papers)

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Research

27 pages, 7256 KiB  
Article
Semantic Mapping for Autonomous Subsea Intervention
by Guillem Vallicrosa, Khadidja Himri, Pere Ridao and Nuno Gracias
Sensors 2021, 21(20), 6740; https://doi.org/10.3390/s21206740 - 11 Oct 2021
Cited by 2 | Viewed by 2188
Abstract
This paper presents a method to build a semantic map to assist an underwater vehicle-manipulator system in performing intervention tasks autonomously in a submerged man-made pipe structure. The method is based on the integration of feature-based simultaneous localization and mapping (SLAM) and 3D [...] Read more.
This paper presents a method to build a semantic map to assist an underwater vehicle-manipulator system in performing intervention tasks autonomously in a submerged man-made pipe structure. The method is based on the integration of feature-based simultaneous localization and mapping (SLAM) and 3D object recognition using a database of a priori known objects. The robot uses Doppler velocity log (DVL), pressure, and attitude and heading reference system (AHRS) sensors for navigation and is equipped with a laser scanner providing non-coloured 3D point clouds of the inspected structure in real time. The object recognition module recognises the pipes and objects within the scan and passes them to the SLAM, which adds them to the map if not yet observed. Otherwise, it uses them to correct the map and the robot navigation if they were already mapped. The SLAM provides a consistent map and a drift-less navigation. Moreover, it provides a global identifier for every observed object instance and its pipe connectivity. This information is fed back to the object recognition module, where it is used to estimate the object classes using Bayesian techniques over the set of those object classes which are compatible in terms of pipe connectivity. This allows fusing of all the already available object observations to improve recognition. The outcome of the process is a semantic map made of pipes connected through valves, elbows and tees conforming to the real structure. Knowing the class and the position of objects will enable high-level manipulation commands in the near future. Full article
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35 pages, 16034 KiB  
Article
Analytical Approach to Sampling Estimation of Underwater Tunnels Using Mechanical Profiling Sonars
by Vitor Augusto Machado Jorge, Pedro Daniel de Cerqueira Gava, Juan Ramon Belchior de França Silva, Thais Machado Mancilha, Waldir Vieira, Geraldo José Adabo and Cairo Lúcio Nascimento, Jr.
Sensors 2021, 21(5), 1900; https://doi.org/10.3390/s21051900 - 09 Mar 2021
Cited by 6 | Viewed by 2848
Abstract
Hydroelectric power plants often make use of tunnels to redirect the flow of water to the plant power house. Such tunnels are often flooded and can span considerable distances. Periodical inspections of such tunnels are highly desirable since a tunnel collapse will be [...] Read more.
Hydroelectric power plants often make use of tunnels to redirect the flow of water to the plant power house. Such tunnels are often flooded and can span considerable distances. Periodical inspections of such tunnels are highly desirable since a tunnel collapse will be catastrophic, disrupting the power plant operation. In many cases, the use of Unmanned Underwater Vehicles (UUVs) equipped with mechanical profiling sonars is a suitable and affordable way to gather data to generate 3D mapping of flooded tunnels. In this paper, we study the resolution of 3D tunnel maps generated by one or more mechanical profiling sonars working in tandem, considering synchronization and occlusion problems. The article derives the analytical equations to estimate the sampling of the underwater tunnels using mechanical profiling sonars (scanning sonars). Experiments in a simulated environment using up to four sensors simultaneously are presented. We also report experimental results obtained by a UUV inside a large power plant tunnel, together with a first map of this environment using a single sonar sensor. Full article
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24 pages, 6539 KiB  
Article
Robust Position Control of an Over-actuated Underwater Vehicle under Model Uncertainties and Ocean Current Effects Using Dynamic Sliding Mode Surface and Optimal Allocation Control
by Mai The Vu, Tat-Hien Le, Ha Le Nhu Ngoc Thanh, Tuan-Tu Huynh, Mien Van, Quoc-Dong Hoang and Ton Duc Do
Sensors 2021, 21(3), 747; https://doi.org/10.3390/s21030747 - 22 Jan 2021
Cited by 79 | Viewed by 5188
Abstract
Underwater vehicles (UVs) are subjected to various environmental disturbances due to ocean currents, propulsion systems, and un-modeled disturbances. In practice, it is very challenging to design a control system to maintain UVs stayed at the desired static position permanently under these conditions. Therefore, [...] Read more.
Underwater vehicles (UVs) are subjected to various environmental disturbances due to ocean currents, propulsion systems, and un-modeled disturbances. In practice, it is very challenging to design a control system to maintain UVs stayed at the desired static position permanently under these conditions. Therefore, in this study, a nonlinear dynamics and robust positioning control of the over-actuated autonomous underwater vehicle (AUV) under the effects of ocean current and model uncertainties are presented. First, a motion equation of the over-actuated AUV under the effects of ocean current disturbances is established, and a trajectory generation of the over-actuated AUV heading angle is constructed based on the line of sight (LOS) algorithm. Second, a dynamic positioning (DP) control system based on motion control and an allocation control is proposed. For this, motion control of the over-actuated AUV based on the dynamic sliding mode control (DSMC) theory is adopted to improve the system robustness under the effects of the ocean current and model uncertainties. In addition, the stability of the system is proved based on Lyapunov criteria. Then, using the generalized forces generated from the motion control module, two different methods for optimal allocation control module: the least square (LS) method and quadratic programming (QP) method are developed to distribute a proper thrust to each thruster of the over-actuated AUV. Simulation studies are conducted to examine the effectiveness and robustness of the proposed DP controller. The results show that the proposed DP controller using the QP algorithm provides higher stability with smaller steady-state error and stronger robustness. Full article
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32 pages, 23557 KiB  
Article
Guidance for Autonomous Underwater Vehicles in Confined Semistructured Environments
by Zorana Milosevic, Ramon A. Suarez Fernandez, Sergio Dominguez and Claudio Rossi
Sensors 2020, 20(24), 7237; https://doi.org/10.3390/s20247237 - 17 Dec 2020
Cited by 8 | Viewed by 3980
Abstract
In this work, we present the design, implementation, and testing of a guidance system for the UX-1 robot, a novel spherical underwater vehicle designed to explore and map flooded underground mines. For this purpose, it needs to navigate completely autonomously, as no communications [...] Read more.
In this work, we present the design, implementation, and testing of a guidance system for the UX-1 robot, a novel spherical underwater vehicle designed to explore and map flooded underground mines. For this purpose, it needs to navigate completely autonomously, as no communications are possible, in the 3D networks of tunnels of semistructured but unknown environments and gather various geoscientific data. First, the overall design concepts of the robot are presented. Then, the guidance system and its subsystems are explained. Finally, the system’s validation and integration with the rest of the UX-1 robot systems are presented. A series of experimental tests following the software-in-the-loop and the hardware-in-the-loop paradigms have been carried out, designed to simulate as closely as possible navigation in mine tunnel environments. The results obtained in these tests demonstrate the effectiveness of the guidance system and its proper integration with the rest of the systems of the robot, and validate the abilities of the UX-1 platform to perform complex missions in flooded mine environments. Full article
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21 pages, 32510 KiB  
Article
The Application of Sector-Scanning Sonar: Strategy for Efficient and Precise Sector-Scanning Using Freedom of Underwater Walking Robot in Shallow Water
by Hyuk Baek, Bong-Huan Jun and Myounggyu D. Noh
Sensors 2020, 20(13), 3654; https://doi.org/10.3390/s20133654 - 29 Jun 2020
Cited by 5 | Viewed by 3446
Abstract
In this paper, we discuss underwater walking robot technology to improve the quality of raw data in sector-scanning sonar images. We propose a strategy for an efficient and precise sector-scanning sonar image acquisition method for use in shallow, strong tidal water with a [...] Read more.
In this paper, we discuss underwater walking robot technology to improve the quality of raw data in sector-scanning sonar images. We propose a strategy for an efficient and precise sector-scanning sonar image acquisition method for use in shallow, strong tidal water with a curved and sloped seabed environment. We verified the strategy by analyzing images acquired through a sea trial using the sector-scanning sonar installed on the CRABSTER (CR200). Before creating this strategy, an experiment was conducted to acquire the seabed image near a pier using a tripod and vertical pole. To overcome the problems and limitations revealed through image analysis, we established two technical strategies. In conclusion, we were able to achieve those technical strategies by using the CR200, which is resistant to strong current, and its six legs provide freedom of movement, allowing for a good sonar attitude. Full article
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18 pages, 16701 KiB  
Article
Rapidly-Exploring Adaptive Sampling Tree*: A Sample-Based Path-Planning Algorithm for Unmanned Marine Vehicles Information Gathering in Variable Ocean Environments
by Chengke Xiong, Hexiong Zhou, Di Lu, Zheng Zeng, Lian Lian and Caoyang Yu
Sensors 2020, 20(9), 2515; https://doi.org/10.3390/s20092515 - 29 Apr 2020
Cited by 21 | Viewed by 2882
Abstract
This research presents a novel sample-based path planning algorithm for adaptive sampling. The goal is to find a near-optimal path for unmanned marine vehicles (UMVs) that maximizes information gathering over a scientific interest area, while satisfying constraints on collision avoidance and pre-specified mission [...] Read more.
This research presents a novel sample-based path planning algorithm for adaptive sampling. The goal is to find a near-optimal path for unmanned marine vehicles (UMVs) that maximizes information gathering over a scientific interest area, while satisfying constraints on collision avoidance and pre-specified mission time. The proposed rapidly-exploring adaptive sampling tree star (RAST*) algorithm combines inspirations from rapidly-exploring random tree star (RRT*) with a tournament selection method and informative heuristics to achieve efficient searching of informative data in continuous space. Results of numerical experiments and proof-of-concept field experiments demonstrate the effectiveness and superiority of the proposed RAST* over rapidly-exploring random sampling tree star (RRST*), rapidly-exploring adaptive sampling tree (RAST), and particle swarm optimization (PSO). Full article
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26 pages, 10918 KiB  
Article
A Fault-tolerant Steering Prototype for X-rudder Underwater Vehicles
by Wenjin Wang, Ying Chen, Yingkai Xia, Guohua Xu, Wei Zhang and Hongming Wu
Sensors 2020, 20(7), 1816; https://doi.org/10.3390/s20071816 - 25 Mar 2020
Cited by 12 | Viewed by 4423
Abstract
The X-rudder concept has been applied to more and more autonomous underwater vehicles (AUVs) in recent years, since it shows better maneuverability and robustness against rudder failure compared to the traditional cruciform rudder. Aiming at the fault-tolerant control of the X-rudder AUV (hereinafter [...] Read more.
The X-rudder concept has been applied to more and more autonomous underwater vehicles (AUVs) in recent years, since it shows better maneuverability and robustness against rudder failure compared to the traditional cruciform rudder. Aiming at the fault-tolerant control of the X-rudder AUV (hereinafter abbreviated as xAUV), a fault-tolerant steering prototype system which can realize dynamics control, autonomous rudder fault detection and fault-tolerant control is presented in this paper. The steering prototype system is deployed on a verification platform, an xAUV, in which the monitor software is developed based on the factory method and the onboard software is developed based on the finite state machine (FSM). Dual-loop increment feedback control (DIFC) is first introduced to obtain smooth virtual rudder commands considering actuator’s limitations. Then the virtual rudder commands are transformed into X-rudder commands based on the mapping theory. In rudder fault diagnosis, an optimized particle filter is proposed for estimating rudder effect deduction, with proposal distribution derived from unscented Kalman filter (UKF). Then the fault type can be determined by analyzing indicators related to the deduction. Fault-tolerant control is addressed by dealing with nonlinear programming (NLP) problem, where minimization of allocation errors and control efforts are set as the optimization objectives, and rudder failure, saturation and actuators limitations are considered as constraints. The fixed-point iteration method is utilized to solve this optimization problem. Many field tests have been conducted in towing tank. The experimental results demonstrate that the proposed steering prototype system is able to detect rudder faults and is robust against rudder failure. Full article
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18 pages, 3690 KiB  
Article
Neuro-Fuzzy Dynamic Position Prediction for Autonomous Work-Class ROV Docking
by Petar Trslić, Edin Omerdic, Gerard Dooly and Daniel Toal
Sensors 2020, 20(3), 693; https://doi.org/10.3390/s20030693 - 27 Jan 2020
Cited by 7 | Viewed by 3677
Abstract
This paper presents a docking station heave motion prediction method for dynamic remotely operated vehicle (ROV) docking, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS). Due to the limited power onboard the subsea vehicle, high hydrodynamic drag forces, and inertia, work-class ROVs are [...] Read more.
This paper presents a docking station heave motion prediction method for dynamic remotely operated vehicle (ROV) docking, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS). Due to the limited power onboard the subsea vehicle, high hydrodynamic drag forces, and inertia, work-class ROVs are often unable to match the heave motion of a docking station suspended from a surface vessel. Therefore, the docking relies entirely on the experience of the ROV pilot to estimate heave motion, and on human-in-the-loop ROV control. However, such an approach is not available for autonomous docking. To address this problem, an ANFIS-based method for prediction of a docking station heave motion is proposed and presented. The performance of the network was evaluated on real-world reference trajectories recorded during offshore trials in the North Atlantic Ocean during January 2019. The hardware used during the trials included a work-class ROV with a cage type TMS, deployed using an A-frame launch and recovery system. Full article
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25 pages, 600 KiB  
Article
Fixed-Time Observer Based Prescribed-Time Containment Control of Unmanned Underwater Vehicles with Faults and Uncertainties
by Tingting Yang and Shuanghe Yu
Sensors 2019, 19(20), 4515; https://doi.org/10.3390/s19204515 - 17 Oct 2019
Cited by 9 | Viewed by 2330
Abstract
The problem of prescribed-time containment control of unmanned underwater vehicles (UUVs) with faults and uncertainties is considered. Different from both regular finite-time control and fixed-time control, the proposed prescribed-time control strategy is built upon a novel coordinate transformation function and the block decomposition [...] Read more.
The problem of prescribed-time containment control of unmanned underwater vehicles (UUVs) with faults and uncertainties is considered. Different from both regular finite-time control and fixed-time control, the proposed prescribed-time control strategy is built upon a novel coordinate transformation function and the block decomposition technique, resulting in the followers being able to move into the convex hull spanned by the leaders in prespecifiable convergence time. Moreover, intermediate variables and the control input terms are also shown to remain uniformly bounded at the prescribed-time. To reduce the magnitude of the bounds, a novel fixed-time observer for the fault is proposed. Two numerical examples are provided to verify the effectiveness of the proposed prescribed-time control strategy. Full article
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