TWO-LEVEL TECHNOLOGY OF INTELLIGENT APPLICATION OF ON-BOARD VIDEO CAMERA OF UNMANNED AERIAL VEHICLE FOR MONITORING OF GEOSPATIAL DATA

This paper presents a real-time optical flow algorithm for a vision-based guidance of an unmanned aerial vehicle (UAV). The optical flow algorithm detects a moving target, and obtains the optical position and optical flow vectors of the target from the image sequence. Then, a vision-based guidance of the UAV is designed to follow the moving target. Additionally, the control law of the imaging seeker uses visual information from the image sequence for target tracking. The method was tested on a 3 degree of freedom (3DOF) dual-rotor UAV with a video camera and the result proved the effectiveness of this method.

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Use of an Unmanned Aerial Vehicle−Mounted Video Camera to Assess Feeding Behavior of Raramuri Criollo Cows

Rangeland Ecology & Management ◽

10.1016/j.rama.2016.04.005 ◽

2016 ◽

Vol 69 (5) ◽

pp. 386-389 ◽

Cited By ~ 15

Author(s):

Shelemia Nyamuryekung’e ◽

Andrés F. Cibils ◽

Richard E. Estell ◽

Alfredo L. Gonzalez

Keyword(s):

Feeding Behavior ◽

Unmanned Aerial Vehicle ◽

Video Camera ◽

Aerial Vehicle

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Using Video Acquired from an Unmanned Aerial Vehicle (UAV) to Measure Fracture Orientation in an Open-Pit Mine

GEOMATICA ◽

10.5623/cig2013-036 ◽

2013 ◽

Vol 67 (3) ◽

pp. 173-180 ◽

Cited By ~ 21

Author(s):

T. McLeod ◽

C. Samson ◽

M. Labrie ◽

K. Shehata ◽

J. Mah ◽

...

Keyword(s):

Unmanned Aerial Vehicle ◽

Three Dimensional ◽

Mining Industry ◽

Point Clouds ◽

Video Camera ◽

Open Pit ◽

Original Video ◽

3D Point Clouds ◽

Video Images ◽

Aerial Vehicle

This project explored the feasibility of using video images acquired with an unmanned aerial vehicle (UAV) to obtain three-dimensional (3D) point clouds using structure from motion (SfM) software. Missions were flown using an Aeryon Scout: a lightweight, vertical take-off and landing quadrotor micro UAV with a miniature video camera. The initial mission captured urban scene images that were used to assess system performance while the main mission focused on rock walls where 3D images were used to successfully measure fracture orientations. Point clouds generated from this combination of technologies were sparse, but in the future, improvements in the resolution of original video images would cascade through the processing and improve the overall results. Such a system could have a multitude of applications in the mining industry, contributing to both safety and financial considerations.

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Geomorphology and typing of the Lake Ladoga shores with the use of dron

Geomorphology RAS ◽

10.31857/s0435-42812019125-37 ◽

2019 ◽

pp. 25-37

Author(s):

V. M. Anokhin ◽

D. S. Dudakova ◽

M. O. Dudakov

Keyword(s):

Survey Data ◽

Unmanned Aerial Vehicle ◽

High Efficiency ◽

Video Camera ◽

Lake Ladoga ◽

Fracture Systems ◽

Ladoga Lake ◽

Main Fracture ◽

Aerial Vehicle ◽

Northern Shore

The use of an unmanned aerial vehicle (UAV) with a photo-video camera in the shore of Lake Ladoga in 2015 showed its high efficiency for studying the geomorphology of the shores. A number of features of the morphology of the Ladoga shores in several areas have been revealed, including: the structure of the submerged coastal slope on shallow banks has been refined; the main fracture systems for a number of crystalline massifs on the northern shore of the lake have been determined. A new map of the Ladoga Lake shores types was created. The integration of the method of terrestrial and aerial geomorphological surveys with subsequent generalization of the results to space survey data is an effective addition to the method of geomorphological studies of the coasts.

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PENGGUNAAN DRONE UNTUK MENDAPATKAN DATA KECELAKAAN LALU LINTAS

Journal of Indonesia Road Safety ◽

10.19184/korlantas-jirs.v1i3.14788 ◽

2018 ◽

Vol 1 (3) ◽

pp. 147

Author(s):

Erika Buchari ◽

Decky Octaviansyah ◽

Muhammad Taslim Chairuddin ◽

Lisbeth Dolok Saribu

Keyword(s):

Unmanned Aerial Vehicle ◽

Travel Behavior ◽

Geospatial Data ◽

Reconstruction Method ◽

Aerial Photo ◽

Geometric Characteristics ◽

Aerial Vehicle ◽

Location Type ◽

The Impact ◽

The Way

The awareness of using helmet is still far from the expectation. Often, the motorcycle riders and passengers do not use helmet. It is very dangerous for them and other travelers. However, it is not easy to find and analyze the riders that use or do not use helmet, furthermore to get data of the impact of using or not using helmet in the accident. One of the way to get such data is from “Zebra Operation”. Nowadays, the development of technology of Aerial Photo and geospatial data can be obtained from small format aerial photo. It can be obtained by the means of Unmanned Aerial Vehicle (UAV) with the attached camera on the UAV so that the geospatial data and motor riders without using helmet can be detected. Rider’s behavior can be observed by using UAV or Drone. The aim of this paper is to(1) find the method of observation the travel behavior of riders without using helmet which can endanger other traveler’s safety by using drone (2) find the method of finding the location of accident, type and cause of the accident as quick as possible by using drone. Finding of this paper is a reconstruction method of accident, geometric characteristics of the location, type and cause of the accident as quick as possible. Kesadaran penggunaan helm saat ini masih jauh dari harapan. Seringkali terlihat pengendara sepeda motor dan penumpang yang diboncengnya tidak menggunakan helm. Hal ini sangat membahayakan keselamatannya dan keselamatan banyak orang disekitarnya.Tidak mudah untuk menganalisis jumlah pengguna helm dan pelanggaran lalu lintas, apalagi untuk mengetahui dampak tidak menggunakan helm terhadap korban kecelakaan lalu lintas. Suatu cara termudah untuk mendapatkan data adalah memanfaatkan data dari operasi Zebra. Dengan perkembangan teknologi foto udara, perolehan data permukaan bumi dapat dilakukan dengan menggunakan foto udara format kecil. Foto udara format kecil diperoleh dengan bantuan wahana pesawat udara tanpa awak atau Unmanned Aerial Vehicle dengan meletakkan kamera pada pesawat tersebut sehingga dapat diperoleh data permukaan bumi sesuai dengan yang direncanakan. Perilaku pengendara yang tidak menggunakan helm dan mengabaikan keselamatan diamati dengan menggunakan drone.Tujuan kajian ini adalah untuk:(1) menghasilkan metode pengamatan perilaku pengendara yang tidak menggunakan helm dan yang menyebabkan kecelakaan atau mengabaikan keselamatandengan menggunakan drone,dan (2) menghasilkan metode untuk mendapatkan data kecelakaan, lokasi jenis, dan penyebab kecelakaan secepat mungkin dengan menggunakan drone. Temuan dari paper ini adalah metoda rekonstruksi kecelakaan, karakteristik geometris lokasi, jenis dan penyebab kecelakaan sesegera mungkin.

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DETERMINING THE LOCATION OF AN UNMANNED AERIAL VEHICLE BASED ON VIDEO CAMERA IMAGES

Advanced Information Systems ◽

10.20998/2522-9052.2021.1.20 ◽

2021 ◽

Vol 5 (1) ◽

pp. 136-139

Author(s):

Elkhan Sabziev

Keyword(s):

Unmanned Aerial Vehicle ◽

Video Camera ◽

Bijective Mapping ◽

Observation Area ◽

Mercator Projection ◽

Surveillance Cameras ◽

Aerial Vehicle

The paper deals with the problem of determining the location of an unmanned aerial vehicle from video and photo images taken by surveillance cameras. As the observation area is considered to be sufficiently limited, the area under consideration can be taken as part of a plane. The solution to the problem is based on the construction of a bijective mapping between the known geographic coordinates of three different objects recognized in the images and their coordinates relative to the monitor plane. To this end, the geographical coordinates of the objects (latitude and longitude) are first converted to the Mercator projection, and a bijective mapping is built between the coordinates of the objects calculated in the Mercator projection and the coordinates relative to the camera monitor plane. Then, based on the current orientation angles of the unmanned aerial vehicle, the coordinates of the projection of its position on the monitor plane are calculated, and the geographical coordinates are found by applying the inverse of the constructed bijective mapping.

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Cooperative Navigation between a Ground Vehicle and an Unmanned Aerial Vehicle in GNSS-Challenged Environments

Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016) ◽

10.33012/2016.14623 ◽

2016 ◽

Author(s):

Victor O. Sivaneri ◽

Jason N. Gross

Keyword(s):

Unmanned Aerial Vehicle ◽

Ground Vehicle ◽

Cooperative Navigation ◽

Aerial Vehicle

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Study on Fault Diagnosis of Planetary Gearbox in Unmanned Aerial Vehicle Using Multi sensor Data

Journal of Applied Reliability ◽

10.33162/jar.2020.12.20.4.332 ◽

2020 ◽

Vol 20 (4) ◽

pp. 332-342

Author(s):

Hyung Jun Park ◽

Seong Hee Cho ◽

Kyung-Hwan Jang ◽

Jin-Woon Seol ◽

Byung-Gi Kwon ◽

...

Keyword(s):

Fault Diagnosis ◽

Unmanned Aerial Vehicle ◽

Sensor Data ◽

Planetary Gearbox ◽

Aerial Vehicle

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Results of Spatial Structure of Atmosphere Radiation in a Spectral Range (1.5–2) µm Research

Light & Engineering ◽

10.33383/2017-061 ◽

2018 ◽

pp. 7-13

Author(s):

Anton M. Mishchenko ◽

Sergei S. Rachkovsky ◽

Vladimir A. Smolin ◽

Igor V . Yakimenko

Keyword(s):

Spatial Structure ◽

Unmanned Aerial Vehicle ◽

Wavelength Range ◽

Spectral Range ◽

Near Ir ◽

Optoelectronic Systems ◽

Aerial Vehicle

Results of experimental studying radiation spatial structure of atmosphere background nonuniformities and of an unmanned aerial vehicle being the detection object are presented. The question on a possibility of its detection using optoelectronic systems against the background of a cloudy field in the near IR wavelength range is also considered.

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