Research

23 pages, 22256 KiB

Open AccessArticle

Underwater Localization System Combining iUSBL with Dynamic SBL in ¡VAMOS! Trials

by José Almeida, Bruno Matias, António Ferreira, Carlos Almeida, Alfredo Martins and Eduardo Silva

Sensors 2020, 20(17), 4710; https://doi.org/10.3390/s20174710 - 20 Aug 2020

Cited by 11 | Viewed by 2693

Abstract

Emerging opportunities in the exploration of inland water bodies, such as underwater mining of flooded open pit mines, require accurate real-time positioning of multiple underwater assets. In the mining operation scenarios, operational requirements deny the application of standard acoustic positioning techniques, posing additional [...] Read more.

Emerging opportunities in the exploration of inland water bodies, such as underwater mining of flooded open pit mines, require accurate real-time positioning of multiple underwater assets. In the mining operation scenarios, operational requirements deny the application of standard acoustic positioning techniques, posing additional challenges to the localization problem. This paper presents a novel underwater localization solution, implemented for the ¡VAMOS! project, based on the combination of raw measurements from a short baseline (SBL) array and an inverted ultrashort baseline (iUSBL). An extended Kalman filter (EKF), fusing IMU raw measurements, pressure observations, SBL ranges, and USBL directional angles, estimates the localization of an underwater mining vehicle in 6DOF. Sensor bias and the speed of sound in the water are estimated indirectly by the filter. Moreover, in order to discard acoustic outliers, due to multipath reflections in such a confined and cluttered space, a data association layer and a dynamic SBL master selection heuristic were implemented. To demonstrate the advantage of this new technique, results obtained in the field, during the ¡VAMOS! underwater mining field trials, are presented and discussed. Full article

(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation)

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19 pages, 2615 KiB

Open AccessArticle

A Deep-Learning Model for Underwater Position Sensing of a Wake’s Source Using Artificial Seal Whiskers

by Mohamed Elshalakani, Muthukumar Muthuramalingam and Christoph Bruecker

Sensors 2020, 20(12), 3522; https://doi.org/10.3390/s20123522 - 22 Jun 2020

Cited by 8 | Viewed by 3302

Abstract

Various marine animals possess the ability to track their preys and navigate dark aquatic environments using hydrodynamic sensing of the surrounding flow. In the present study, a deep-learning model is applied to a biomimetic sensor for underwater position detection of a wake-generating body. [...] Read more.

Various marine animals possess the ability to track their preys and navigate dark aquatic environments using hydrodynamic sensing of the surrounding flow. In the present study, a deep-learning model is applied to a biomimetic sensor for underwater position detection of a wake-generating body. The sensor is composed of a bundle of spatially-distributed optical fibers that act as artificial seal-like whiskers and interact with the body’s wake in the form of time-variant (bending) deflections. Supervised learning is employed to relate the vibrations of the artificial whiskers to the position of an upstream cylinder. The labeled training data are prepared based on the processing and reduction of the recorded bending responses of the artificial whiskers while the cylinder is placed at various locations. An iterative training algorithm is performed on two neural-network models while using the 10-fold cross-validation technique. The models are able to predict the coordinates of the cylinder in the two-dimensional (2D) space with a high degree of accuracy. The current implementation of the sensor can passively sense the wake generated by the cylinder at Re ≃ 6000 and estimate its position with an average error smaller than the characteristic diameter D of the cylinder and for inter-distances (in the water tunnel) up to 25-times D. Full article

(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation)

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22 pages, 13332 KiB

Open AccessArticle

Study on Control System of Integrated Unmanned Surface Vehicle and Underwater Vehicle

by Hyunjoon Cho, Sang-Ki Jeong, Dae-Hyeong Ji, Ngoc-Huy Tran, Mai The Vu and Hyeung-Sik Choi

Sensors 2020, 20(9), 2633; https://doi.org/10.3390/s20092633 - 05 May 2020

Cited by 39 | Viewed by 7097

Abstract

In this paper, in order to overcome certain limitations of previously commercialized platforms, a new integrated unmanned surface vehicle (USV) and unmanned underwater vehicle (UUV) platform connected via underwater cable capable of acquiring real-time underwater data and long-time operation are studied. A catamaran-type [...] Read more.

In this paper, in order to overcome certain limitations of previously commercialized platforms, a new integrated unmanned surface vehicle (USV) and unmanned underwater vehicle (UUV) platform connected via underwater cable capable of acquiring real-time underwater data and long-time operation are studied. A catamaran-type USV was designed to overcome the limitations of an ocean environment and to play the role as the hub of power supply and communication for the integrated platform. Meanwhile, the UUV was designed as torpedo-shaped to minimize hydrodynamic resistance and its hardware design was focused on processing and sending the underwater camera and sonar data. The underwater cable driven by a winch system was installed to supply power from the USV to the UUV and to transmit acquired data form underwater sonar sensor or camera. Different from other previously studied cooperation system of USVs and autonomous underwater vehicles (AUVs), the merit of the proposed system is real-time motion coordination control between the USV and UUV while transmitting large amount of data using the tether cable. The main focus of the study is coordination of the UUV with respect to the global positioning system (GPS) attached at USV and verification of its performance throughout field tests. Waypoint tracking control algorithm was designed and implemented on USV and relative heading, distance control for USV–UUV coordination was implemented to UUV. To ensure the integrity of the coordination control of the integrated platform, a study on accurate measurement system of the relative position between the USV and the UUV by using the GPS and the ultrashort baseline (USBL) device was performed. Individual tests were conducted to verify the performance of USBL and AHRS, which provide the position and heading data of UUV among the sensors mounted on the actual platform, and the effectiveness of the obtained sensor data is presented. Using the accurate measurement system, a number of field tests were conducted to verify the performance of the integrated platform. Full article

(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation)

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19 pages, 3392 KiB

Open AccessArticle

Passive Underwater Target Tracking: Conditionally Minimax Nonlinear Filtering with Bearing-Doppler Observations

by Andrey Borisov, Alexey Bosov, Boris Miller and Gregory Miller

Sensors 2020, 20(8), 2257; https://doi.org/10.3390/s20082257 - 16 Apr 2020

Cited by 13 | Viewed by 2839

Abstract

The paper presents an application of the Conditionally-Minimax Nonlinear Filtering (CMNF) algorithm to the online estimation of underwater vehicle movement given a combination of sonar and Doppler discrete-time noisy sensor observations. The proposed filter postulates recurrent “prediction–correction” form with some predefined basic prediction [...] Read more.

The paper presents an application of the Conditionally-Minimax Nonlinear Filtering (CMNF) algorithm to the online estimation of underwater vehicle movement given a combination of sonar and Doppler discrete-time noisy sensor observations. The proposed filter postulates recurrent “prediction–correction” form with some predefined basic prediction and correction terms, and then they are optimally fused. The CMNF estimates have the following advantageous features. First, the obtained estimates are unbiased. Second, the theoretical covariance matrix of CMNF errors meets the real values. Third, the CMNF algorithm gives a possibility to choose the preliminary observation transform, basic prediction, and correction functions in any specific case of the observation system to improve the estimate accuracy significantly. All the features of conditionally-minimax estimates are demonstrated by the regression example of random position estimate given the noisy bearing observations. The contribution of the paper is the numerical study of the CMNF algorithm applied to the underwater target tracking given bearing-only and bearing-Doppler observations. Full article

(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation)

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21 pages, 1280 KiB

Open AccessArticle

Path Planning in Threat Environment for UUV with Non-Uniform Radiation Pattern

by Andrey A. Galyaev, Alexander V. Dobrovidov, Pavel V. Lysenko, Mikhail E. Shaikin and Victor P. Yakhno

Sensors 2020, 20(7), 2076; https://doi.org/10.3390/s20072076 - 07 Apr 2020

Cited by 7 | Viewed by 2414

Abstract

The problem of optimal trajectory planning of the unmanned underwater vehicle (UUV) is considered and analytically solved. The task is to minimize the risk of detection of the moving object by a static sonar while moving between two given points on a plane. [...] Read more.

The problem of optimal trajectory planning of the unmanned underwater vehicle (UUV) is considered and analytically solved. The task is to minimize the risk of detection of the moving object by a static sonar while moving between two given points on a plane. The detection is based on the primary acoustic field radiated by the object with a non-uniform radiation pattern. In the first part of the article, the probability of non-detection is derived. Further, it is used as an optimization criterion. The non-uniform radiation pattern of the object differentiates this work from previous research in the area. The optimal trajectory and velocity law of the moving object are found, as well as the criterion value on it. Full article

(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation)

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22 pages, 48888 KiB

Open AccessArticle

Flow Field Perception of a Moving Carrier Based on an Artificial Lateral Line System

by Guijie Liu, Huanhuan Hao, Tingting Yang, Shuikuan Liu, Mengmeng Wang, Atilla Incecik and Zhixiong Li

Sensors 2020, 20(5), 1512; https://doi.org/10.3390/s20051512 - 09 Mar 2020

Cited by 11 | Viewed by 3086

Abstract

At present, autonomous underwater vehicles (AUVs) cannot perceive local environments in complex marine environments, where fish can obtain hydrodynamic information about the surrounding environment through a lateral line. Inspired by this biological function, an artificial lateral line system (ALLS) was built on a [...] Read more.

At present, autonomous underwater vehicles (AUVs) cannot perceive local environments in complex marine environments, where fish can obtain hydrodynamic information about the surrounding environment through a lateral line. Inspired by this biological function, an artificial lateral line system (ALLS) was built on a moving bionic carrier using the pressure sensor in this paper. When the carrier operated with different speeds in the flow field, the pressure distribution characteristics surrounding the carrier were analyzed by numerical simulation, where the effect of the flow angle between the fluid velocity direction and the carrier navigation direction was considered. The flume experiment was carried out in accordance with the simulation conditions, and the analysis results of the experiment were consistent with those in the simulation. The relationship between pressure and fluid velocity was established by a fitting method. Subsequently, the pressure difference method was investigated to establish a relationship model between the pressure difference on both sides of the carrier and the flow angle. Finally, a back propagation neural network model was used to predict the fluid velocity, flow angle, and carrier speed successfully in the unknown fluid environment. The local fluid environment perception by moving carrier carrying ALLS was studied which may promote the engineering application of the artificial lateral line in the local perception, positioning, and navigation on AUVs. Full article

(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation)

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20 pages, 19051 KiB

Open AccessArticle

Vision-Based Localization System Suited to Resident Underwater Vehicles

by Petar Trslić, Anthony Weir, James Riordan, Edin Omerdic, Daniel Toal and Gerard Dooly

Sensors 2020, 20(2), 529; https://doi.org/10.3390/s20020529 - 18 Jan 2020

Cited by 13 | Viewed by 3348

Abstract

In recent years, we have seen significant interest in the use of permanently deployed resident robotic vehicles for commercial inspection, maintenance and repair (IMR) activities. This paper presents a concept and demonstration, through offshore trials, of a low-cost, low-maintenance, navigational marker that can [...] Read more.

In recent years, we have seen significant interest in the use of permanently deployed resident robotic vehicles for commercial inspection, maintenance and repair (IMR) activities. This paper presents a concept and demonstration, through offshore trials, of a low-cost, low-maintenance, navigational marker that can eliminate drift in vehicle INS solution when the vehicle is close to the IMR target. The subsea localisation marker system is fixed on location on the resident field asset and is used in on-vehicle machine vision algorithms for pose estimation and facilitation of a high-resolution world coordinate frame registration with a high refresh rate. This paper presents evaluation of the system during trials in the North Atlantic Ocean during January 2019. System performances and propagation of position error is inspected and estimated, and the effect of intermittent visual based position update to Kalman filter and onboard INS solution is discussed. The paper presents experimental results of the commercial state-of-the-art inertial navigation system operating in the pure inertial mode for comparison. Full article

(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation)

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21 pages, 2123 KiB

Open AccessArticle

On AUV Control with the Aid of Position Estimation Algorithms Based on Acoustic Seabed Sensing and DOA Measurements

by Alexander Miller, Boris Miller and Gregory Miller

Sensors 2019, 19(24), 5520; https://doi.org/10.3390/s19245520 - 13 Dec 2019

Cited by 12 | Viewed by 2482

Abstract

This article discusses various approaches to the control of autonomous underwater vehicles (AUVs) with the aid of different velocity-position estimation algorithms. Traditionally this field is considered as the area of the extended Kalman filter (EKF) application: It became a universal tool for nonlinear [...] Read more.

This article discusses various approaches to the control of autonomous underwater vehicles (AUVs) with the aid of different velocity-position estimation algorithms. Traditionally this field is considered as the area of the extended Kalman filter (EKF) application: It became a universal tool for nonlinear observation models and its use is ubiquitous. Meanwhile, the specific characteristics of underwater navigation, such as an incomplete sets of measurements, constraints on the range metering or even impossibility of range measurements, observations provided by rather specific acoustic beacons, sonar observations, and other features seriously narrow the applicability of common instruments due to a high level of uncertainty and nonlinearity. The AUV navigation system, not being able to rely on a single source of position estimation, has to take into account all available information. This leads to the necessity of various complex estimation and data fusion algorithms, which are the matter of the present article. Here we discuss some approaches to the AUV position estimation such as conditionally minimax nonlinear filtering (CMNF) and unbiased pseudo-measurement filters (UPMFs) in conjunction with velocity estimation based on the seabed profile acoustic sensing. The presented estimation algorithms serve as a basis for a locally optimal AUV motion control algorithm, which is also presented. Full article

(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation)

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