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Autonomous Underwater Vehicle Navigation Ⅱ
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Autonomous Underwater Vehicle Navigation Ⅱ

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

Deadline for manuscript submissions: closed (24 March 2022) | Viewed by 10273

Special Issue Editor

Prof. Dr. Boris Miller

E-Mail Website
Guest Editor
Laboratory of Image Analysis and Processing, Institute for Information Transmission Problems, Russian Academy of Sciences (IITP RAS), Moscow, Russia
Interests: control theory; discrete-continuous systems; stochastic control; filtering; unmanned vehicles
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Navigation of autonomous underwater vehicles (AUV) is a challenging issue of modern robotic science. Even in the case of well-developed inertial navigation systems (INS), the position estimates obtained by dead reckoning suffer from the integration drift. The sensors utilized for external measurement (e.g., acoustic sonars, acoustic beacons, GPS) either provide bearing-only measurements, which means that an independent position estimate is not possible, or require preliminary path equipping or path adjustment (emersion), which means that they cannot be used on an ongoing basis. Another problem is the dependence of the measurement accuracy on the unknown environment properties such as acoustic speed (which in turn depends on the salinity), currents, and seabed relief. That is why the precise navigation of AUV requires rather delicate data fusion of the measurement provided by various sensors which work on different physical principles, including mechanics, magnetics, acoustics, etc.

This Special Issue invites researchers working in the navigation theory based on the data fusion of different sensors and practitioners, whose work is connected with AUV applications in solutions to practical problems of underwater robotics. Thus, this special issue welcomes contributions on AUV navigation subjects including but not limited to the following topics:

  • AUV guidance, navigation and path planning;
  • AUV attitude estimation;
  • Underwater target tracking;
  • Acoustic sonars, acoustic SLAM;
  • Seabed profiling.

Prof. Dr. Boris Miller
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. Sensors is an international peer-reviewed open access semimonthly 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 vehicles
  • Guidance, navigation, path planning
  • Attitude estimation
  • Underwater target tracking
  • Inertial navigation system
  • Acoustic sonars
  • Acoustic SLAM
  • Seabed profiling
  • Data fusion

Published Papers (4 papers)

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Research

16 pages, 4727 KiB  
Article
3DupIC: An Underwater Scan Matching Method for Three-Dimensional Sonar Registration
by António Ferreira, José Almeida, Alfredo Martins, Aníbal Matos and Eduardo Silva
Sensors 2022, 22(10), 3631; https://0-doi-org.brum.beds.ac.uk/10.3390/s22103631 - 10 May 2022
Cited by 1 | Viewed by 1335
Abstract
This work presents a six degrees of freedom probabilistic scan matching method for registration of 3D underwater sonar scans. Unlike previous works, where local submaps are built to overcome measurement sparsity, our solution develops scan matching directly from the raw sonar data. Our [...] Read more.
This work presents a six degrees of freedom probabilistic scan matching method for registration of 3D underwater sonar scans. Unlike previous works, where local submaps are built to overcome measurement sparsity, our solution develops scan matching directly from the raw sonar data. Our method, based on the probabilistic Iterative Correspondence (pIC), takes measurement uncertainty into consideration while developing the registration procedure. A new probabilistic sensor model was developed to compute the uncertainty of each scan measurement individually. Initial displacement guesses are obtained from a probabilistic dead reckoning approach, also detailed in this document. Experiments, based on real data, demonstrate superior robustness and accuracy of our method with respect to the popular ICP algorithm. An improved trajectory is obtained by integration of scan matching updates in the localization data fusion algorithm, resulting in a substantial reduction of the original dead reckoning drift. Full article
(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation Ⅱ)
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27 pages, 5679 KiB  
Article
Simu2VITA: A General Purpose Underwater Vehicle Simulator
by Pedro Daniel de Cerqueira Gava, Cairo Lúcio Nascimento Júnior, Juan Ramón Belchior de França Silva and Geraldo José Adabo
Sensors 2022, 22(9), 3255; https://0-doi-org.brum.beds.ac.uk/10.3390/s22093255 - 24 Apr 2022
Cited by 3 | Viewed by 2325
Abstract
This article presents an Unmanned Underwater Vehicle simulator named Simu2VITA, which was designed to be rapid to set up, easy to use, and simple to modify the vehicle’s parameters. Simulation of the vehicle dynamics is divided into three main Modules: the Actuator Module, [...] Read more.
This article presents an Unmanned Underwater Vehicle simulator named Simu2VITA, which was designed to be rapid to set up, easy to use, and simple to modify the vehicle’s parameters. Simulation of the vehicle dynamics is divided into three main Modules: the Actuator Module, the Allocation Module and the Dynamics Model. The Actuator Module is responsible for the simulation of actuators such as propellers and fins, the Allocation Module translates the action of the actuators into forces and torques acting on the vehicle and the Dynamics Module implements the dynamics equations of the vehicle. Simu2VITA implements the dynamics of the actuators and of the rigid body of the vehicle using the MATLAB/Simulink® framework. To show the usefulness of the Simu2VITA simulator, simulation results are presented for an unmanned underwater vehicle navigating inside a fully flooded tunnel and then compared with sensor data collected when the real vehicle performed the same mission using the controllers designed employing the simulator. Full article
(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation Ⅱ)
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15 pages, 3677 KiB  
Communication
Adaptive Navigation Algorithm with Deep Learning for Autonomous Underwater Vehicle
by Hui Ma, Xiaokai Mu and Bo He
Sensors 2021, 21(19), 6406; https://0-doi-org.brum.beds.ac.uk/10.3390/s21196406 - 25 Sep 2021
Cited by 7 | Viewed by 3526
Abstract
Precise navigation is essential for autonomous underwater vehicles (AUVs). The measurement deviation of the navigation sensors, especially the microelectromechanical systems (MEMS) sensors, is a crucial factor that affects the localization accuracy. Deep learning is a novel method to solve this problem. However, the [...] Read more.
Precise navigation is essential for autonomous underwater vehicles (AUVs). The measurement deviation of the navigation sensors, especially the microelectromechanical systems (MEMS) sensors, is a crucial factor that affects the localization accuracy. Deep learning is a novel method to solve this problem. However, the calculation cycle and robustness of the deep learning method may be insufficient in practical application. This paper proposes an adaptive navigation algorithm with deep learning to address these questions and realize accurate navigation. Firstly, this algorithm uses deep learning to generate low-frequency position information to correct the error accumulation of the navigation system. Secondly, the χ2 rule is selected to judge if the Doppler velocity log (DVL) measurement fails, which could avoid interference from DVL outliers. Thirdly, the adaptive filter, based on the variational Bayesian (VB) method, is employed to estimate the navigation information simultaneous with the measurement covariance, improving navigation accuracy even more. The experimental results, based on AUV field data, show that the proposed algorithm could realize robust navigation performance and significantly improve position accuracy. Full article
(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation Ⅱ)
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24 pages, 3071 KiB  
Article
2D Optimal Trajectory Planning Problem in Threat Environment for UUV with Non-Uniform Radiation Pattern
by Andrey A. Galyaev, Pavel V. Lysenko and Victor P. Yakhno
Sensors 2021, 21(2), 396; https://0-doi-org.brum.beds.ac.uk/10.3390/s21020396 - 08 Jan 2021
Cited by 5 | Viewed by 2082
Abstract
Path planning is necessary in many applications using unmanned underwater vehicles (UUVs). The main class of tasks is the planning of safe routes with minimal energy costs and/or minimal levels of emitted physical and information signals. Since the action planner is on board [...] Read more.
Path planning is necessary in many applications using unmanned underwater vehicles (UUVs). The main class of tasks is the planning of safe routes with minimal energy costs and/or minimal levels of emitted physical and information signals. Since the action planner is on board the UUV, the main focus is on methods and algorithms that allow it to build reference trajectories while minimizing the number of calculations. The study is devoted to the problem of the optimal route planning for a UUV with a non-uniform radiation pattern. The problem is stated in the form of two point variational problem for which necessary and sufficient optimality conditions are proved. Particular attention is paid to cases where optimality conditions are not met. These cases are directly related to found specific forms of a radiation pattern. Sufficient optimality conditions are extended on the class of two-link and multi-link motion paths. Software tools have been developed and computer simulations have been performed for various types of radiation patterns. Full article
(This article belongs to the Special Issue Autonomous Underwater Vehicle Navigation Ⅱ)
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