scholarly journals Control System Architecture for Automatic Recovery of Fixed-Wing Unmanned Aerial Vehicles in a Moving Arrest System

2021 ◽  
Vol 103 (4) ◽  
Author(s):  
Kristoffer Gryte ◽  
Martin L. Sollie ◽  
Tor Arne Johansen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Low Cost ◽  
Field Testing ◽  
Satellite System ◽  
Base Station ◽  
Research Literature ◽  
Aerial Vehicles ◽  
Global Navigation Satellite ◽  
The Right ◽  
Automatic Recovery

AbstractAutomatic recovery is an important step in enabling fully autonomous missions using fixed-wing unmanned aerial vehicles (UAVs) operating from ships or other moving platforms. However, automatic recovery in moving arrest systems is only briefly studied in the research literature, and is not yet an option when using low-cost, commercial off-the-shelf (COTS) autopilots. Acknowledging the reliability and low cost of COTS avionics, this paper adds recovery functionality as a modular extension based on non-intrusive additions to an autopilot with very general assumptions on its interface. This is achieved by line-of-sight guidance, which sends an augmented desired position to the autopilot, to ensure line-following along a virtual runway that guides the UAV into the arrest system. The translation and rotation of this line is determined by the pose of the arrest system, determined using two Global Navigation Satellite System (GNSS) receivers, where one is configured as a Real-Time Kinematic (RTK) base station. The relative position of the UAV and arrest system is also precisely estimated using RTK GNSS. Through extensive field testing, on two different fixed-wing UAVs, the system has shown its performance and reliability; 43 recovery attempts in a stationary net hit 0.01 ± 0.25m to the right and 0.07 ± 0.20m below the target in calm conditions. Further, 15 recoveries in a barge-mounted, ship-towed net hit 0.06 ± 0.53m to the right and 0.98 ± 0.27m below the target in winds up to 4 m/s. The remaining error is largely systematic, caused by communication delays, and could be reduced with more integral effect or through direct compensation.

Low-cost, high accuracy Global Navigation Satellite System positioning for understanding floods

2020 ◽  
Author(s):  
Hessel Winsemius ◽  
Andreas Krietemeyer ◽  
Kirsten Van Dongen ◽  
Ivan Gayton ◽  
Frank Annor ◽  
...  
Keyword(s):  
Global Navigation Satellite System ◽  
Low Cost ◽  
Smart Phone ◽  
Satellite System ◽  
Base Station ◽  
Navigation Satellite ◽  
Low Resource Settings ◽  
Low Resource ◽  
Global Navigation ◽  
Global Navigation Satellite

<p>Detailed elevation is a prerequisite for many hydrological applications. To name a few, understanding of urban and rural flood hazard and risk; understanding floodplain geometries and conveyance; and monitoring morphological changes. The accuracy of traditional Global Navigation Satellite System (GNSS) chipsets in smart phones is typically in the order of several meters, too low to be useful for such applications. Structure from Motion photogrammetry methods or Light Detection and Ranging (LIDAR), may be used to establish 3D point clouds from drone photos or lidar instrumentation, but even these require very accurate Ground Control Point (GCP) observations for a satisfactory result. These can be acquired through specialised GNSS rover equipment, combined with a multi-frequency GNSS base station or base station network, providing a Real-Time (RTK) or Post-Processing Kinematics (PPK) solution. These techniques are too expensive and too difficult to maintain for use within low resource settings and are usually deployed by experts or specialised firms.</p><p>Here we investigate if accurate positioning (horizontal and vertical) can be acquired using a very recently released low-cost multi-constellation dual-frequency receiver (ublox ZED-F9P), connected with a simple antenna and a smart phone. The setup is remarkably small and easy to carry into the field. Using a geodetic (high-grade) GNSS antenna and receiver as base station, initial results over baselines in the order of a few km with the low-cost receiver revealed a positioning performance in the centimeter domain. Currently, we are testing the solution using a smart phone setup as base station within Dar es Salaam, to improve elevation mapping within the community mapping project “Ramani Huria”. We will also test the equipment for use in GCP observations within the ZAMSECUR project in Zambia and TWIGA project in Ghana. This new technology opens doors to affordable and robust observations of positions and elevation in low resource settings.</p>

scholarly journals Relative Navigation in UAV Applications

2020 ◽  
Vol vm01 (is02) ◽  
pp. 52-65
Author(s):  
Tuncay Yunus Erkec ◽  
Chingiz Hajiyev
Keyword(s):  
State Estimation ◽  
Unmanned Aerial Vehicles ◽  
Satellite System ◽  
Formation Flight ◽  
Navigation Systems ◽  
Relative Navigation ◽  
Inertial Navigation Systems ◽  
Estimation Algorithms ◽  
Aerial Vehicles ◽  
Global Navigation Satellite

This paper is committed to the relative navigation of Unmanned Aerial Vehicles (UAVs) flying in formation flight. The concept and methods of swarm UAVs technology and architecture have been explained. The relative state estimation models of unmanned aerial vehicles which are based on separate systems as Inertial Navigation Systems (INS)&Global Navigation Satellite System (GNSS), Laser&INS and Vision based techniques have been compared via various approaches. The sensors are used individually or integrated each other via sensor integration for solving relative navigation problems. The UAV relative navigation models are varied as stated in operation area, type of platform and environment. The aim of this article is to understand the correlation between relative navigation systems and potency of state estimation algorithms as well during formation flight of UAV.

scholarly journals Investigation of Unmanned Aerial Vehicles-Based Photogrammetry for Large Mine Subsidence Monitoring

Minerals ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 196 ◽  
Author(s):  
Danijela Ignjatović Stupar ◽  
Janez Rošer ◽  
Milivoj Vulić
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Coal Mine ◽  
Negative Impact ◽  
Local Environment ◽  
Satellite System ◽  
Reference Points ◽  
Coal Extraction ◽  
Observation Data ◽  
Aerial Vehicles ◽  
Global Navigation Satellite

With the exploitation of underground sources, nature receives a huge negative impact on the local environment introducing surface subsidence. A mining region needs to be observed in sequences before, during, and after coal extraction from the coal mine. Different measuring methods exist to monitor subsidence, and all of them apply various instrumentation. A choice of methodology depends on access to a field of observation and requested accuracy. Obviously, the most accurate results provide geometric leveling, but, many times, the terrain does not allow surveyors to walk over the dangerous outfields. Looking for the most adequate and feasible method, this research did a comparison between observation of the same points, applying statistical analysis of differences between the reference points heights, and tested methods. Monitoring procedure comprised utilization of total stations (TS), global navigation satellite system (GNSS), and unmanned aerial vehicles (UAV). In this paper, the Velenje coal mine was taken as a case study, and observation data were collected during 2017.

scholarly journals A Low-Cost Global Navigation Satellite System Positioning Accuracy Assessment Method for Agricultural Machinery

2022 ◽  
Vol 12 (2) ◽  
pp. 693
Author(s):  
Dorijan Radočaj ◽  
Ivan Plaščak ◽  
Goran Heffer ◽  
Mladen Jurišić
Keyword(s):  
Global Navigation Satellite System ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Satellite System ◽  
Base Station ◽  
Navigation Satellite ◽  
Agricultural Machinery ◽  
Positioning Accuracy ◽  
Global Navigation ◽  
Global Navigation Satellite

The high-precision positioning and navigation of agricultural machinery represent a backbone for precision agriculture, while its worldwide implementation is in rapid growth. Previous studies improved low-cost global navigation satellite system (GNSS) hardware solutions and fused GNSS data with complementary sources, but there is still no affordable and flexible framework for positioning accuracy assessment of agricultural machinery. Such a low-cost method was proposed in this study, simulating the actual movement of the agricultural machinery during agrotechnical operations. Four of the most commonly used GNSS corrections in Croatia were evaluated in two repetitions: Croatian Positioning System (CROPOS), individual base station, Satellite-based Augmentation Systems (SBASs), and an absolute positioning method using a smartphone. CROPOS and base station produced the highest mean GNSS positioning accuracy of 2.4 and 2.9 cm, respectively, but both of these corrections produced lower accuracy than declared. All evaluated corrections produced significantly different median values in two repetitions, representing inconsistency of the positioning accuracy regarding field conditions. While the proposed method allowed flexible and effective application in the field, future studies will be directed towards the reduction of the operator’s subjective impact, mainly by implementing autosteering solutions in agricultural machinery.

scholarly journals SQUEEZEPOSENET: IMAGE BASED POSE REGRESSION WITH SMALL CONVOLUTIONAL NEURAL NETWORKS FOR REAL TIME UAS NAVIGATION

2017 ◽  
Vol IV-2/W3 ◽  
pp. 49-57 ◽  
Author(s):  
M. S. Müller ◽  
S. Urban ◽  
B. Jutzi
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Low Cost ◽  
Satellite System ◽  
Trajectory Estimation ◽  
Localization And Mapping ◽  
Wide Range ◽  
Novel Method ◽  
Computationally Expensive ◽  
Global Navigation Satellite ◽  
Local Image

The number of unmanned aerial vehicles (UAVs) is increasing since low-cost airborne systems are available for a wide range of users. The outdoor navigation of such vehicles is mostly based on global navigation satellite system (GNSS) methods to gain the vehicles trajectory. The drawback of satellite-based navigation are failures caused by occlusions and multi-path interferences. Beside this, local image-based solutions like Simultaneous Localization and Mapping (SLAM) and Visual Odometry (VO) can e.g. be used to support the GNSS solution by closing trajectory gaps but are computationally expensive. However, if the trajectory estimation is interrupted or not available a re-localization is mandatory. In this paper we will provide a novel method for a GNSS-free and fast image-based pose regression in a known area by utilizing a small convolutional neural network (CNN). With on-board processing in mind, we employ a lightweight CNN called SqueezeNet and use transfer learning to adapt the network to pose regression. Our experiments show promising results for GNSS-free and fast localization.

scholarly journals Algorithm for Control of Unmanned Aerial Vehicles in the Process of Visual Tracking of Objects with a Variable Movement’s Trajectory

2021 ◽  
Vol 12 (1) ◽  
pp. 46-57
Author(s):  
A. A. Adnastarontsau ◽  
D. A. Adnastarontsava ◽  
R. V. Fiodortsev ◽  
D. V. Katser ◽  
A. Y. Liavonau ◽  
...  
Keyword(s):  
Coordinate System ◽  
Unmanned Aerial Vehicles ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
Optoelectronic System ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Stabilized Platform ◽  
Global Navigation Satellite

The purpose of the research was to create an algorithm for determining and correcting the output parameters of the navigation module and the flight-navigation complex of unmanned aerial vehicles which provides control of an aviation gyro-stabilized platform with a multispectral optoelectronic system during flight and tracking various objects of observation.Principles of control of an aviation technical vision system located on an unmanned aerial vehicle on a two-degree gyro-stabilized platform with the possibility of full turn around two perpendicular axes along the course and pitch are considered. Stability of tracking of observation objects at a distance of up to 10000 m is ensured by the use of a multispectral optoelectronic system including a rangefinder, thermal imaging and two visual channels.Analysis of the object of observation and the method of its support are carried out. An algorithm is proposed for integrating a Global Navigation Satellite System and a strapdown inertial navigation system based on the extended Kalman filter which includes two stages of calculations, extrapolation (prediction) and correction. Specialized software in the FreeRTOS v9.0 environment has been developed to obtain a navigation solution: latitude, longitude and altitude of the unmanned aerial vehicle in the WGS-84 coordinate system, as well as the pitch, heading and roll angles; north, east and vertical components of velocities in the navigation coordinate system; longitudinal, vertical and transverse components of free accelerations and angular velocities in the associated coordinate system based on data from the receiving and measuring module of the Global Navigation Satellite System and data from the 6-axis MEMS sensor STIM300.

scholarly journals Automatic Object Detection, Labelling, and Localization by Camera’s Drone System

2021 ◽  
pp. 5008-5023
Author(s):  
Rasool D. Haameid ◽  
Bushra Q. Al-Abudi ◽  
Raaid N. Hassan
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Video Transmission ◽  
Low Cost ◽  
Base Station ◽  
Trigonometric Functions ◽  
One Dimensional ◽  
Camera Angle ◽  
Aerial Vehicles ◽  
Gps Devices ◽  
Objects Detection

This work explores the designing a system of an automated unmanned aerial vehicles (UAV( for objects detection, labelling, and localization using deep learning. This system takes pictures with a low-cost camera and uses a GPS unit to specify the positions. The data is sent to the base station via Wi-Fi connection. The proposed system consists of four main parts. First, the drone, which was assembled and installed, while a Raspberry Pi4 was added and the flight path was controlled. Second, various programs that were installed and downloaded to define the parts of the drone and its preparation for flight. In addition, this part included programs for both Raspberry Pi4 and servo, along with protocols for communication, video transmission, and sending and receiving signals between the drone and the computer. Third, a real-time, modified, one dimensional convolutional neural network (1D-CNN) algorithm, which was applied to detect and determine the type of the discovered objects (labelling). Fourth, GPS devices, which were used to determine the location of the drone starting and ending points . Trigonometric functions were then used for adjusting the camera angle and the drone altitude to calculate the direction of the detected object automatically. According to the performance evaluation conducted, the implemented system is capable of meeting the targeted requirements.

scholarly journals Localization System for Lightweight Unmanned Aerial Vehicles in Inspection Tasks

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5937
Author(s):  
Diego Benjumea ◽  
Alfonso Alcántara ◽  
Agustin Ramos ◽  
Arturo Torres-Gonzalez ◽  
Pedro Sánchez-Cuevas ◽  
...  
Keyword(s):  
High Altitude ◽  
Unmanned Aerial Vehicles ◽  
Satellite System ◽  
Localization System ◽  
Aerial Vehicles ◽  
System Defect ◽  
Angular Velocities ◽  
Infrastructure Inspection ◽  
Inspection Tasks ◽  
Global Navigation Satellite

This paper presents a localization system for Unmanned Aerial Vehicles (UAVs) especially designed to be used in infrastructure inspection, where the UAVs have to fly in challenging conditions, such as relatively high altitude (e.g., 15 m), eventually with poor or absent GNSS (Global Navigation Satellite System) signal reception, or the need for a BVLOS (Beyond Visual Line of Sight) operation in some periods. In addition, these infrastructure inspection applications impose the following requirements for the localization system: defect traceability, accuracy, reliability, and fault tolerance. Our system proposes a lightweight solution combining multiple stereo cameras with a robotic total station to comply with these requirements, providing full-state estimation (i.e., position, orientation, and linear and angular velocities) in a fixed and time-persistent reference frame. Moreover, the system can align and fuse all sensor measurements in real-time at high frequency. We have integrated this localization system in our aerial platform, and we have tested its performance for inspection in a real-world viaduct scenario, where the UAV has to operate with poor or absent GNSS signal at high altitude.

scholarly journals APPLICATION OF UNMANNED AERIAL VEHICLES FOR GLACIER RESEARCH IN THE ARCTIC AND ANTARCTIC

2019 ◽  
Vol 1 ◽  
pp. 131
Author(s):  
Kristaps Lamsters ◽  
Jānis Karušs ◽  
Māris Krievāns ◽  
Jurijs Ješkins
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Satellite System ◽  
Aerial Photographs ◽  
The Arctic ◽  
Polar Regions ◽  
Flight Duration ◽  
Aerial Vehicles ◽  
Surface Models ◽  
Global Navigation Satellite ◽  
Glacier Mapping

Unmanned aerial vehicles or drones are nowadays widely used in a broad field of scientific and commercial applications. Despite this, it is quite a new method for glacier mapping in polar regions and has a lot of advantages, as well as disadvantages over more classical remote sensing instruments. Here we examine the main issues associated with the application of drones for glacier research from our experience in Iceland, Greenland and the Antarctic. We use DJI Phantom series drones for the obtaining of aerial photographs and produce digital surface models (resolution of 8 – 16 cm) and orthomosaics (resolution of 2 – 4 cm) for glacier mapping. Several issues related to the ground control points, geolocation using Global Navigation Satellite System receiers and creation of final products are addressed as well. We recommend the further use of drones in remote polar areas because it allows obtaining very high-resolution orthomosaics and digital surface models that are not achieved by other methods. Short summer season, raw weather with precipitation and winds, limited drone flight duration and problems with connection cables are the main issues everyone can encounter working in polar regions but all issues can be restricted with careful planning and readiness to gather data whenever it is possible during all field campaign.

scholarly journals THE POTENTIAL OF LIGHT LASER SCANNERS DEVELOPED FOR UNMANNED AERIAL VEHICLES – THE REVIEW AND ACCURACY

2016 ◽  
Vol XLII-2/W2 ◽  
pp. 87-95 ◽  
Author(s):  
M. Pilarska ◽  
W. Ostrowski ◽  
K. Bakuła ◽  
K. Górski ◽  
Z. Kurczyński
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Laser Scanning ◽  
Measurement Accuracy ◽  
Laser Scanner ◽  
Satellite System ◽  
Measurement Unit ◽  
Aerial Vehicles ◽  
Laser Scanners ◽  
Final Measurement ◽  
Global Navigation Satellite

Modern photogrammetry and remote sensing have found small Unmanned Aerial Vehicles (UAVs) to be a valuable source of data in various branches of science and industry (e.g., agriculture, cultural heritage). Recently, the growing role of laser scanning in the application of UAVs has also been observed. Laser scanners dedicated to UAVs consist of four basic components: a laser scanner (LiDAR), an Inertial Measurement Unit (IMU), a Global Navigation Satellite System (GNSS) receiver and an on-board computer. The producers of the system provide users with detailed descriptions of the accuracies separately for each component. However, the final measurement accuracy is not given. This paper reviews state-of-the-art of laser scanners developed specifically for use on a UAV, presenting an overview of several constructions that are available nowadays. The second part of the paper is focussed on analysing the influence of the sensor accuracies on the final measurement accuracy. Mathematical models developed for Airborne Laser Scanning (ALS) accuracy analyses are used to estimate the theoretical accuracies of different scanners with conditions typical for UAV missions. Finally, the theoretical results derived from the mathematical simulations are compared with an experimental use case.

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