scholarly journals THE PREDICTION OF POSITION AND ORIENTATION PARAMETERS OF UAV FOR VIDEO IMAGING

2017 ◽  
Vol XLII-2/W6 ◽  
pp. 407-413 ◽  
Author(s):  
D. Wierzbicki
Keyword(s):  
Standard Deviation ◽  
Unmanned Aerial Vehicle ◽  
Prediction Models ◽  
Low Cost ◽  
Digital Camera ◽  
Unmanned Aircraft ◽  
Navigation Data ◽  
Aerial Vehicle ◽  
Position And Orientation ◽  
Trigonometric Model

The paper presents the results of the prediction for the parameters of the position and orientation of the unmanned aerial vehicle (UAV) equipped with compact digital camera. Issue focus in this paper is to achieve optimal accuracy and reliability of the geo-referenced video frames on the basis of data from the navigation sensors mounted on UAV. In experiments two mathematical models were used for the process of the prediction: the polynomial model and the trigonometric model. The forecast values of position and orientation of UAV were compared with readings low cost GPS and INS sensors mounted on the unmanned Trimble UX-5 platform. Research experiment was conducted on the preview of navigation data from 23 measuring epochs. The forecast coordinate values and angles of the turnover and the actual readings of the sensor Trimble UX-5 were compared in this paper. Based on the results of the comparison it was determined that: the best results of co-ordinate comparison of an unmanned aerial vehicle received for the storage with, whereas worst for the coordinate Y on the base of both prediction models, obtained value of standard deviation for the coordinate XYZ from both prediction models does not cross over a admissible criterion 10 m for the term of the exactitudes of the position of a unmanned aircraft. The best results of the comparison of the angles of the turn of a unmanned aircraft received for the angle Pitch, whereas worst for the angles Heading and Roll on the base of both prediction models. Obtained value of standard deviation for the angles of turn HPR from both prediction models does not exceed a admissible exactitude 5° only for the angle Pitch, however crosses over this value for the angles Heading and Roll.

scholarly journals Determining the Elements of Exterior Orientation in Aerial Triangulation Processing Using UAV Technology

2020 ◽  
Vol 22 (1) ◽  
pp. 15-24
Author(s):  
Damian Wierzbicki ◽  
Kamil Krasuski
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Measurement Data ◽  
Image Data ◽  
Research Topic ◽  
Mathematical Methods ◽  
Exterior Orientation ◽  
Navigation Data ◽  
Aerial Vehicle ◽  
Position And Orientation ◽  
Vehicle Platform

Unmanned Aerial Vehicles (UAVs) are still an interesting and current research topic in photogrammetry. An important issue in this area is determining the elements of exterior orientation of image data acquired at low altitudes. The article presents selected mathematical methods (TGC, TIC, TAD) of estimating elements of exterior orientation for image data obtained at low altitudes. The measurement data for the experimental test were recorded by the Unmanned Aerial Vehicle platform Trimble UX-5. In the framework of the test photogrammetric flight, the authors obtained 506 images and navigation data specifying the position and orientation of the Unmanned Aerial Vehicle. As a result of the research, it is proven possible to show the usefulness of the mathematical models (TGC, TIC, TAD) in estimation of elements of exterior orientation.

scholarly journals Utilization of UAV (Unmanned Aerial Vehicle) technology for mapping and identification of agroforestry land cover patterns in Namolandur Village, North Sumatra

2021 ◽  
Vol 912 (1) ◽  
pp. 012075
Author(s):  
H Arinah ◽  
A S Thoha ◽  
Z Mardiyadi ◽  
O A Lubis
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Unmanned Aerial Vehicle ◽  
Rural Areas ◽  
Human Life ◽  
Low Cost ◽  
Unmanned Aircraft ◽  
Fish Ponds ◽  
Land Utilization ◽  
Aerial Vehicle

Abstract Agroforestry-based land use is widely used in society, particularly in rural areas. With a combination of tree crops (annual) and crops (seasonal), agroforestry patterns can maximize land utilization. Unmanned aircraft, often known as drones, can map and detect land cover to optimise land usage based on agroforestry. Drones have various advantages, including low cost, ease of acquisition, and the ability to utilize them in high-risk situations without endangering human life or in difficult or inaccessible places. They can also fly at low altitudes, resulting in cloud-free shots and sharper images. This research focuses on using an unmanned aerial vehicle (UAV) to map agroforestry patterns in Namolandur Village and detect and determine the area of each agroforestry pattern land cover using aerial camera photos. Using the Mavic 2 pro drone and Pix4D Mapper software for aerial photo processing, Namolandur village became the research subject. The data analysis revealed that agrisilviculture, agrosilvofishery, and agrosilvopastoral were the forms of land use with agroforestry patterns in the village of Namolandur. In addition, water guava, duku fruit (Lansium domestika), oil palm, coconut, and a combination of fish ponds, cattle, and goats are among the geographical analysis of the area and each form of land use.

scholarly journals Use of Unmanned Aerial Vehicle Imagery and Deep Learning UNet to Extract Rice Lodging

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3859 ◽  
Author(s):  
Zhao ◽  
Yuan ◽  
Song ◽  
Ding ◽  
Lin ◽  
...  
Keyword(s):  
Deep Learning ◽  
Unmanned Aerial Vehicle ◽  
Optical Sensors ◽  
Network Architecture ◽  
High Efficiency ◽  
Low Cost ◽  
Digital Camera ◽  
Large Area ◽  
Image Test ◽  
Aerial Vehicle

Rice lodging severely affects harvest yield. Traditional evaluation methods and manual on-site measurement are found to be time-consuming, labor-intensive, and cost-intensive. In this study, a new method for rice lodging assessment based on a deep learning UNet (U-shaped Network) architecture was proposed. The UAV (unmanned aerial vehicle) equipped with a high-resolution digital camera and a three-band multispectral camera synchronously was used to collect lodged and non-lodged rice images at an altitude of 100 m. After splicing and cropping the original images, the datasets with the lodged and non-lodged rice image samples were established by augmenting for building a UNet model. The research results showed that the dice coefficients in RGB (Red, Green and Blue) image and multispectral image test set were 0.9442 and 0.9284, respectively. The rice lodging recognition effect using the RGB images without feature extraction is better than that of multispectral images. The findings of this study are useful for rice lodging investigations by different optical sensors, which can provide an important method for large-area, high-efficiency, and low-cost rice lodging monitoring research.

scholarly journals Symmetry Analysis of Oriental Polygonal Pagodas Using 3D Point Clouds for Cultural Heritage

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1228
Author(s):  
Ting On Chan ◽  
Linyuan Xia ◽  
Yimin Chen ◽  
Wei Lang ◽  
Tingting Chen ◽  
...  
Keyword(s):  
Cultural Heritage ◽  
Unmanned Aerial Vehicle ◽  
Point Cloud ◽  
Geometric Model ◽  
Digital Camera ◽  
Point Clouds ◽  
Symmetry Analysis ◽  
3D Point Clouds ◽  
Transmission Towers ◽  
Aerial Vehicle

Ancient pagodas are usually parts of hot tourist spots in many oriental countries due to their unique historical backgrounds. They are usually polygonal structures comprised by multiple floors, which are separated by eaves. In this paper, we propose a new method to investigate both the rotational and reflectional symmetry of such polygonal pagodas through developing novel geometric models to fit to the 3D point clouds obtained from photogrammetric reconstruction. The geometric model consists of multiple polygonal pyramid/prism models but has a common central axis. The method was verified by four datasets collected by an unmanned aerial vehicle (UAV) and a hand-held digital camera. The results indicate that the models fit accurately to the pagodas’ point clouds. The symmetry was realized by rotating and reflecting the pagodas’ point clouds after a complete leveling of the point cloud was achieved using the estimated central axes. The results show that there are RMSEs of 5.04 cm and 5.20 cm deviated from the perfect (theoretical) rotational and reflectional symmetries, respectively. This concludes that the examined pagodas are highly symmetric, both rotationally and reflectionally. The concept presented in the paper not only work for polygonal pagodas, but it can also be readily transformed and implemented for other applications for other pagoda-like objects such as transmission towers.

Illumination Correction of Multi-Time RGB Images Obtained with an Unmanned Aerial Vehicle

2021 ◽  
pp. 50-58
Author(s):  
Michael Yu. Kataev ◽  
Maria M. Dadonova ◽  
Dmitry S. Efremenko
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Vegetation Index ◽  
Digital Camera ◽  
Quantitative Result ◽  
Efficient Solutions ◽  
Acquisition Time ◽  
Time Interval ◽  
Agricultural Field ◽  
Aerial Vehicle ◽  
Rgb Images

The goal of this research was to study and optimize multi-temporal RGB images obtained by a UAV (unmanned aerial vehicle). A digital camera onboard the UAV allows obtaining data with a high temporal and spatial resolution of ground objects. In the case considered by us, the object of study is agricultural fields, for which, based on numerous images covering the agricultural field, image mosaics (orthomosaics) are constructed. The acquisition time for each orthomosaic takes at least several hours, which imposes a change in the illuminance of each image, when considered separately. Orthomosaics obtained in different periods of the year (several months) will also differ from each other in terms of illuminance. For a comparative analysis of different parts of the field (orthomosaic), obtained in the same time interval or comparison of areas for different periods of time, their alignment by illumination is required. Currently, the majority of alignment approaches rely rather on colour (RGB) methods, which cannot guarantee finding efficient solutions, especially when it is necessary to obtain a quantitative result. In the paper, a new method is proposed that takes into account the change in illuminance during the acquisition of each image. The general formulation of the problem of light correction of RGB images in terms of assessing the colour vegetation index Greenness is considered. The results of processing real measurements are presented.

scholarly journals Suitability of a Non-Dispersive Infrared Methane Sensor Package for Flux Quantification Using an Unmanned Aerial Vehicle

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4705 ◽  
Author(s):  
Adil Shah ◽  
Joseph Pitt ◽  
Khristopher Kabbabe ◽  
Grant Allen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Mole Fraction ◽  
Low Cost ◽  
Methane Flux ◽  
Gain Factor ◽  
Measured Signal ◽  
Allan Deviation ◽  
Methane Sensor ◽  
Aerial Vehicle ◽  
Flux Quantification

Point-source methane emission flux quantification is required to help constrain the global methane budget. Facility-scale fluxes can be derived using in situ methane mole fraction sampling, near-to-source, which may be acquired from an unmanned aerial vehicle (UAV) platform. We test a new non-dispersive infrared methane sensor by mounting it onto a small UAV, which flew downwind of a controlled methane release. Nine UAV flight surveys were conducted on a downwind vertical sampling plane, perpendicular to mean wind direction. The sensor was first packaged in an enclosure prior to sampling which contained a pump and a recording computer, with a total mass of 1.0 kg. The packaged sensor was then characterised to derive a gain factor of 0.92 ± 0.07, independent of water mole fraction, and an Allan deviation precision (at 1 Hz) of ±1.16 ppm. This poor instrumental precision and possible short-term drifts made it non-trivial to define a background mole fraction during UAV surveys, which may be important where any measured signal is small compared to sources of instrumental uncertainty and drift. This rendered the sensor incapable of deriving a meaningful flux from UAV sampling for emissions of the order of 1 g s−1. Nevertheless, the sensor may indeed be useful when sampling mole fraction enhancements of the order of at least 10 ppm (an order of magnitude above the 1 Hz Allan deviation), either from stationary ground-based sampling (in baseline studies) or from mobile sampling downwind of sources with greater source flux than those observed in this study. While many methods utilising low-cost sensors to determine methane flux are being developed, this study highlights the importance of adequately characterising and testing all new sensors before they are used in scientific research.

scholarly journals Simulation of UAV Systems

10.14311/754 ◽  
2005 ◽  
Vol 45 (4) ◽  
Author(s):  
P. Kaňovský ◽  
L. Smrcek ◽  
C. Goodchild
Keyword(s):  
Dynamical System ◽  
Unmanned Aerial Vehicle ◽  
Low Cost ◽  
Design Tool ◽  
Inertial System ◽  
Principal Function ◽  
Low Weight ◽  
High Bandwidth ◽  
Aerial Vehicle ◽  
Selection Of

The study described in this paper deals with the issue of a design tool for the autopilot of an Unmanned Aerial Vehicle (UAV) and the selection of the airdata and inertial system sensors. This project was processed in cooperation with VTUL a PVO o.z. [1]. The feature that distinguishes the autopilot requirements of a UAV (Figs. 1, 7, 8) from the flight systems of conventional manned aircraft is the paradox of controlling a high bandwidth dynamical system using sensors that are in harmony with the low cost low weight objectives that UAV designs are often expected to achieve. The principal function of the autopilot is flight stability, which establishes the UAV as a stable airborne platform that can operate at a precisely defined height. The main sensor for providing this height information is a barometric altimeter. The solution to the UAV autopilot design was realised with simulations using the facilities of Matlab® and in particular Simulink®[2]. 

scholarly journals Design of a Low-Cost Fixed Wing UAV

2018 ◽  
Vol 159 ◽  
pp. 02045
Author(s):  
Mochammad Ariyanto ◽  
Joga D. Setiawan ◽  
Teguh Prabowo ◽  
Ismoyo Haryanto ◽  
Munadi
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Low Cost ◽  
Flight Test ◽  
Body Part ◽  
Aerial Vehicle ◽  
Straight Wing

This research will try to design a low cost of fixed-wing unmanned aerial vehicle (UAV) using low-cost material that able to fly autonomously. Six parameters of UAV’s structure will be optimized based on basic airframe configuration, wing configuration, straight wing, tail configuration, fuselage material, and propeller location. The resulted and manufactured prototype of fixed-wing UAV will be tested in autonomous fight tests. Based on the flight test, the developed UAV can successfully fly autonomously following the trajectory command. The result shows that low-cost material can be used as a body part of fixed-wing UAV.

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