Concept of an Innovative Autonomous Unmanned System for Bathymetric Monitoring of Shallow Waterbodies (INNOBAT System)

Specht, Mariusz; Stateczny, Andrzej; Specht, Cezary; Widźgowski, Szymon; Lewicka, Oktawia; Wiśniewska, Marta

doi:10.3390/en14175370

Cited by 40 publications

(30 citation statements)

References 76 publications

(88 reference statements)

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“…Various echosounders mounted directly on unmanned surface vehicles (USVs) are presented in research given in [50]. In works [2,6,51], the use of UAVs for photogrammetric measurements and USVs for hydroacoustic measurements has been presented. A novel and interesting approach for planning and performing an integrated mission by UAVs and USVs is explained in [52].…”

Section: Introductionmentioning

confidence: 99%

Methodology for Combining Data Acquired by Unmanned Surface and Aerial Vehicles to Create Digital Bathymetric Models in Shallow and Ultra-Shallow Waters

et al. 2021

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This paper presents a method for integrating data acquired by unmanned surface vehicles and unmanned aerial vehicles. The aim of this work was to create a uniform bathymetric surface extending to the shoreline. Such a body of water is usually characterized by ultra-shallow depths, which makes measurement impossible even with hydrographic autonomous vessels. Bathymetric data acquired by the photogrammetric method are, however, characterized by large errors with increasing depth. The presented method is based on processing of two data sets using a bathymetric reference surface and selection of points on the basis of generated masks. Numerical bathymetric models created by interpolation methods confirmed the usefulness of the concept adopted.

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Section: Introductionmentioning

confidence: 99%

Methodology for Combining Data Acquired by Unmanned Surface and Aerial Vehicles to Create Digital Bathymetric Models in Shallow and Ultra-Shallow Waters

et al. 2021

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“…As part of the INNOBAT research project [74], on 19 August 2021, hydrographic surveys were carried out on Kłodno lake in Zawory. The aim of the study was to determine the usefulness of an inertial navigation system for hydrographic surveys.…”

Section: Measurement Equipmentmentioning

confidence: 99%

Study on the Positioning Accuracy of GNSS/INS Systems Supported by DGPS and RTK Receivers for Hydrographic Surveys

Stateczny

Specht

et al. 2021

Energies

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Hydrographic surveys, in accordance with the International Hydrographic Organization (IHO) S-44 standard, can be carried out in the following five orders: Exclusive, Special, 1a, 1b and 2, for which minimum accuracy requirements for the applied positioning system have been set out. They are as follows, respectively: 1, 2, 5, 5 and 20 m, with a confidence level of 95% in two-dimensional space. The Global Navigation Satellite System (GNSS) network solutions (accuracy: 2–3 cm (p = 0.95)) and the Differential Global Positioning System (DGPS) (accuracy: 1–2 m (p = 0.95)) are now commonly used positioning methods in hydrography. Due to the fact that a new order of hydrographic surveys has appeared in the IHO S-44 standard from 2020—Exclusive, looking at the current positioning accuracy of the DGPS system, it is not known whether it can be used in it. The aim of this article is to determine the usefulness of GNSS/Inertial Navigation Systems (INS) for hydrographic surveys. During the research, the following two INSs were used: Ekinox2-U and Ellipse-D by the SBG Systems, which were supported by DGPS and Real Time Kinematic (RTK) receivers. GNSS/INS measurements were carried out during the manoeuvring of the Autonomous/Unmanned Surface Vehicle (ASV/USV) named “HydroDron” on Kłodno lake in Zawory. The acquired data were processed using the mathematical model that allows us to assess whether any positioning system at a given point in time meets (or not) the accuracy requirements for each IHO order. The model was verified taking into account the historical and current test results of the DGPS and RTK systems. Tests have confirmed that the RTK system meets the requirements of all the IHO orders, even in situations where it is not functioning 100% properly. Moreover, it was proven that the DGPS system does not only meet the requirements provided for the most stringent IHO order, i.e., the Exclusive Order (horizontal position error ≤ 1 m (p = 0.95)). Statistical analyses showed that it was only a few centimetres away from meeting this criterion. Therefore, it can be expected that soon it will be used in all the IHO orders.

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“…However, only a small portion has been explored [1]. Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles reduce risks to which humans are exposed and give significant assistance in recognition tasks, playing an important role in underwater exploration [2], [3]. However, AUVs need accurate navigation for reliable operation [1], [4].…”

Section: Introductionmentioning

confidence: 99%

Sonar FoV Segmentation for Motion Estimation Using DL Networks

2022

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Accurate navigation of an autonomous underwater vehicle is important for its reliable operation. However, this task is challenging due to limitations of radio wave propagation and poor visibility in the aquatic environment. Underwater navigation techniques based on analysing sonar images facilitated by machine learning have shown promising results. However, previously proposed techniques are still complicated for real-time applications. This paper investigates low complexity techniques for the motion estimation based on the use of images obtained by a sonar looking down to the seafloor. The sonar can use multiple beams within a field of view (FoV). Various configurations of beams are considered according to portions of the FoV covered and two estimation approaches are investigated. In one approach, the sonar images are directly processed by a deep learning (DL) network, whereas in the other, the images are converted into (reduced size) vectors before applying them to a DL network. The vector approach shows a significantly lower computation time (about 10 times faster), which makes it suitable for realtime applications. Both the approaches show a similar estimation accuracy, about 10% of the maximum magnitude of the motion. The vector technique has been used to estimate a simulated trajectory and compare the estimate with the ground truth, which showed a good match. It has also been applied to estimate the trajectory of an imaging sonar from a real data set from a ship's hull inspection. The estimated trajectory has successfully been used to build a mosaic by merging the sonar images from the real data set.

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Concept of an Innovative Autonomous Unmanned System for Bathymetric Monitoring of Shallow Waterbodies (INNOBAT System)

Cited by 40 publications

References 76 publications

Methodology for Combining Data Acquired by Unmanned Surface and Aerial Vehicles to Create Digital Bathymetric Models in Shallow and Ultra-Shallow Waters

Methodology for Combining Data Acquired by Unmanned Surface and Aerial Vehicles to Create Digital Bathymetric Models in Shallow and Ultra-Shallow Waters

Study on the Positioning Accuracy of GNSS/INS Systems Supported by DGPS and RTK Receivers for Hydrographic Surveys

Sonar FoV Segmentation for Motion Estimation Using DL Networks

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