• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.99-100
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• 2016

드론이나 이동형 촬영장비에 장착된 카메라로부터 깨끗하고 안정된 영상을 획득하기 위해서는 짐벌시스템의 안정화기 설계가 필요하다. 짐벌시스템은 카메라 모듈을 지지하는 구조와 외부로 부터의 진동을 차단하면서 정확한 각도를 추종하는 안정화기로 구성된다. 이동형 촬영장비나, 비행중인 드론에는 매우 다양한 주파수 성분의 진동이 발생되는데, 이러한 진동을 제어하기 위하여 6자유도 운동방정식을 유도하고, 이 중에서 본 논문에서는 일반적으로 rolling, pitching, yawing 운동에 대해서는 PID 제어기를 사용하여 안정화를 제어하기만, 카메라종류나 짐벌시스템 구조가 바뀔 때 마다 PID 파라미터를 변경해야 되는 경우가 빈번하다. 본 논문에서는 이런 문제점을 개선하기 새로이 제기된 제어 기법인 지적 PID(intelligent PID) 제어를 통하여 진동제어를 수행하여 짐벌시스템의 안정화를 위한 제어기법을 제안하고자 한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.8
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• pp.767-772
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• 2016

The purpose of this paper is to develop a gimbal system installed in the UFV(unmanned flight vehicles) for 360 degree VR video. In particular, even if the UFV rotated any direction the camera position is fiexd to minimize the shaking using the gyro sensor and the camera system is stable for taking $360^{\circ}$ panorama VR images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.890-896
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• 2022

In this paper, gimbal camera control through smart gloves was implemented to increase convenience and accessibility to the control of drones used in various fields. Smart gloves identify human gestures and transmit signals through Bluetooth. The received signal is converted into a signal suitable for the drone through a GCS (Gound Control Station). Signals from smart gloves are expressed in a quaternion method to prevent gimbal locks, but for gimbal cameras, conversion is required to use Roll, Pitch, and Yaw methods. The data conversion mission is performed in the GCS. The GCS transmits an input signal to the control board of the drone through Wi-Fi. The control board generates and outputs the transmitted signal in a PWM manner. The output signal is input to the gimbal camera through the SBUS method and controlled. The input signal of the smart glove averaged 0.093 s and up to 0.099 s to output to the gimbal camera, showing that there was no problem in real-time use.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.190-190
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• 2004

목표물이 시선의 중심에서 벗어났을 때 모터를 구동시켜 목표물을 시선의 중심에 고정시킴과 동시에 외란으로 인한 카메라의 시선이 흔들리는 것을 막아주는 것을 시선 안정화 시스템이라 한다. 이러한 시스템은 능동 서스펜션 역할출 하는 서보제어기 설계기술이 요구된다. 이론 위하여 본 연구에서는 3축의 회전운동이 가능하고 회전운동에 따른 카메라의 시선의 회전축이 일체화가 되도록 하는 짐벌(gimbals) 구조를 설계한다.(중략)

• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.149-156
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• 2019

In the field of maintenance of power transmission lines, drones have been used for their patrol and inspection by KEPCO since 2017. This drone technology was originally developed by KEPCO Research Institute, and now workers from four regional offices of KEPCO have directly applied this technology to the drone patrol and inspection tasks. In the drone inspection system, a drone with an optical zooming camera and a thermal camera can fly automatically along the transmission lines by the ground control system developed by KEPCO Research Institute, but its camera gimbal has been remotely controlled by a field worker. Especially the drone patrol and inspection has been mainly applied for the transmission lines in the inaccessible areas such as regions with river-crossings, sea-crossings and mountains. There are often communication disruptions between the drone and its remote controller in such extreme fields of mountain areas with many barriers. This problem may cause the camera gimbal be out of control, even though the inspection drone flies along the flight path well. In addition, interference with the reception of real-time transmitted videos makes the field worker unable to operate it. To solve these problems, we have developed the auto-tracking camera gimbal system with deep learning method. The camera gimbal can track the transmission line automatically, even when the transmitted video on a remote controller is intermittently unavailable. To show the effectiveness of our camera gimbal system, its field test results will be presented in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2107-2112
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• 2016

This paper is designed to develop a Gimbal control stabilizer for drones Gimbal system control for drone for 3D image to make sure clean image in the shaking and wavering environments of drone system. The stabilizer is made of tools which support camera modules and IMU(Inertial Measurement Unit) sensor modules follow exact angles, which can brock vibrations outside of the camera modules. It is difficult for the camera modules to get clean image, because of irregular movements and various vibrations produced by flying drones. Moreover, a general PID controller used for the movements of rolling, pitching and yawing in order to control the various vibrations of various frequencies needs often to readjust PID control parameters. Therefore, this paper aims to conduct the Intelligent-PID controller as well as design the Gimbal control stabilizer to get clean images and to improve irregular movements and various vibrations problems referenced above.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.9-12
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• 2021

드론 Photogrammetry는 높은 기술적 활용가치가 있는 기술로서, 결과물로 생성하는 3D 디지털 공간정보 모델이 시설물의 비육안 안전점검 및 진단에 활용될 수 있을 뿐만 아니라 디지털 트윈 구축을 위한 가장 기초적이고 핵심적인 수치 데이터를 제공하기 때문이다. 본 연구에서는 드론 Photogrammetry의 적정 품질을 구현하기 위한 임무비행의 다양한 영향인자에 대해 고찰하였다. K-water연구원 누수탐사실습장을 대상으로 드론 사진 촬영 시 비행고도, 비행속도, 중첩도, 카메라 Pitch각의 영향에 대해 연구를 수행하였다. 본 연구에서 비행시간에 영향을 미치는 인자로서 비행고도, 중첩도, 비행속도의 순으로 중요도가 있음을 알 수 있었다. 드론 임무 비행 시 후처리 결과에 가장 큰 영향을 미치는 인자는 중첩도로 나타났다. 중첩도 60% 임무비행은 3D 모델의 geometry 왜곡이 큰 편으로 나타났다. 비행 고도는 GSD (Ground Sampling Distance)와 직접 연계되므로 중요하며, 낮은 고도일수록 높은 품질의 모델링이 가능하다. April Tag를 통한 지상기준점 자동 패턴 인식 기능은 후처리 과정에서 시간 절약이 가능하여 유용하였다. 비행속도에 의한 결과물의 품질은 큰 차이가 없었으나, 수직 구조물의 모서리 부분에 다소 차이가 있었다. 짐벌 Pitch각도에 의한 정사영상 품질의 차이는 크지 않았으나 수직구조물과 평면적 구조물에 따라 각기 다른 촬영각도를 적용하는 것이 바람직하다. 본 연구성과는 향후 보다 다양한 환경에서의 데이터 수집을 통해 최적 디지털 현실 모델링에 기여할 것으로 판단된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.5215-5220
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• 2013

Recent construction in the field of 3D aversion is increasing interest in automation. This study is results about survey of the coastal landfill using automatic VRS-GPS surveying system. GPS is made with GRXI and SHC250 controller. Automatic surveying system is composed of DPS module, geomagnetism sensor, bluetooth, gimbals, IMU, etc and enables an automatic driving via entered into a route of position. The developed auto surveying system has installed the front and camera for vertical axis and can grasp situation of surveying with smartphone in real time. The comparative result between surveyed result with repetition method auto VRS-GPS surveying system observed surveyed result with VRS-RTK has shown that average error of x-axis is 0.009m, average error of y-axis, 0.010m and average error of height, 0.002m. This possibility was confirmed that field application.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.93-98
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• 2019

On today, optical system are the next generation weapon systems being studied in many countries, starting from USA. One of the most important technologies in optical system is a high-speed automatic target tracking system that can continuously track high-speed moving small targets. This paper designs an automatic target tracking system based on a correlated trekker that is robust against rapid shape changes for fast moving targets and small targets at a distance. The proposed system showed about 98% success rate in response to the targets that are under a complex background such as drone, ranger, etc.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.663-670
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• 2020

In the present study, we assessed the accuracy of aerial triangulation using a UAV (Unmanned Aerial Vehicle) capable of network RTK (Real-Time Kinematic) survey in a disaster situation that may occur in a semi-urban area mixed with buildings. For a reliable survey of check points, they were installed on the roofs of buildings, and static GNSS (Global Navigation Satellite System) survey was conducted for more than four hours. For objective accuracy assessment, coded aerial targets were installed on the check points to be automatically recognized by software. At the instance of image acquisition, the 3D coordinates of the UAV camera were measured using VRS (Virtual Reference Station) method, as a kind of network RTK survey, and the 3-axial angles were achieved using IMU (Inertial Measurement Unit) and gimbal rotation measurement. As a result of estimation and update of the interior and exterior orientation parameters using Agisoft Metashape, the 3D RMSE (Root Mean Square Error) of aerial triangulation ranged from 0.153 m to 0.102 m according to the combination of the image overlap and the angle of the image acquisition. To get higher aerial triangulation accuracy, it was proved to be effective to incorporate oblique images, though it is common to increase the overlap of vertical images. Therefore, to conduct a UAV mapping in an urgent disaster site, it is necessary to acquire oblique images together rather than improving image overlap.