• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1928-1929
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• 2011

무인항공기란(Unmanned Aerial Vehicle : UAV)란 일반적으로 조종사 없이 사전에 입력된 프로그램에 따라 또는 비행체 스스로 주위환경(장애물, 항로)을 인식하고 판단하여 자율 비행(Autonomous Flying)하는 비행체를 말한다. 본 논문에서는 항법센서(Attitude Heading Referance System: AHRS)를 비행제어 시스템과 통합한 시스템에 관하여 다루었다.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.2
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• pp.344-351
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• 2017

This paper presents a method to estimate steady wind and airspeed bias error using an aircraft with GPS and airspeed sensor. The estimation uses the vector relation between the inertial, air, and wind velocities through a novel design of an extended Kalman filter. The observability analysis is also presented to show that the aircraft is required to keep changing its flight direction for the desired observability. The feasibility and performance of the proposed algorithm is demonstrated through simulations and flight experiments.

• Journal of Ecology and Environment
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• v.41 no.3
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• pp.72-77
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• 2017

The world of technology is pleasantly evolving to a stage where small robotic aid may be used to ease the work of researchers, and to one day bring more accurate results than the current human abilities allow. In the research field of species monitoring in biology, unmanned aerial vehicles (UAVs) have begun to play an important role in how research is approached, analyzed, and then applied for further investigation, particularly by focusing on a single species. This paper uses data that has been collected from June to October 2015, to demonstrate how the innovative idea of using UAVs to monitor a particular species will bring a positive development in conservation research, and what it was able to achieve in this research field so far. More precisely, we examine the potential of UAVs to take center stage in future research, as well as their current accuracy. This paper describes the use of the commercially available Phantom 2 Vision+ for the detection, assessment, and monitoring of the butterfly species Libythea celtis, demonstrating how it can help the monitoring of butterflies and how it could be developed for even more adventurous and detailed research in the future.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.784-791
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• 2022

Tack coat is a thin layer of asphalt between the existing pavement and asphalt overlay. During construction, insufficient tack coat layering can later cause surface defects such as slippage, shoving, and rutting. This paper proposed a method for tack coat inspection improvement using an unmanned aerial vehicle (UAV) and deep learning neural network for automatic non-uniform assessment of the applied tack coat area. In this method, the drone-captured images are exploited for assessment using a combination of Mask R-CNN and Grey Level Co-occurrence Matrix (GLCM). Mask R-CNN is utilized to detect the tack coat region and segment the region of interest from the surroundings. GLCM is used to analyze the texture of the segmented region and measure the uniformity and non-uniformity of the tack coat on the existing pavements. The results of the field experiment showed both the intersection over union of Mask R-CNN and the non-uniformity measured by GLCM were promising with respect to their accuracy. The proposed method is automatic and cost-efficient, which would be of value to state Departments of Transportation for better management of their work in pavement construction and rehabilitation.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.387-393
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• 2021

This paper proposes a system to synchronize the time of computers over an unmanned aerial vehicle (UAV) network. With the proposed system, the UAVs can perform missions that require precise relative time. Also, data collected by UAVs can be fused precisely with synchronized time. In the system, to synchronize the time of all computers over the UAV network, two-step synchronization is performed. In the first step, the mission computers of the UAVs are synchronized through the server of the system. After the first step, the mission computers measure time offset between the time of the mission computers and the flight computers. The offset values are delivered to the server. In the second step, virtual time is determined by the server from the collected time offset. The measured offset is compensated by moving the synchronized time of mission computers to the reasonable virtual time. Since only the time of mission computers are controlled, any flight computers that use micro air vehicle link (MAVLink) protocol can be synchronized in the proposed system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.303-312
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• 2017

This paper indirectly created high density point cloud data using unmanned aerial vehicle image. Then, we tried to suggest new concept of classification technique where particular objects from point cloud data can be selectively classified. For this, we established the classification technique that can be used as search factor in classifying color information in point cloud data. Then, using suggested classification technique, we implemented object classification and analyzed classification accuracy by relative comparison with self-created proof resource. As a result, the possibility of point cloud data classification was observable using the image's information. Furthermore, it was possible to classify particular object's point cloud data in high classification accuracy.

• Proceedings of KOSOMES biannual meeting
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• 2018.06a
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• pp.40-40
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• 2018

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.10
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• pp.20-27
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• 2004

In this study, CFD analysis for 2D ellipse and 3D CRW UAV are performed. Furthermore, flow analysis around a hub connecting body and rotor is analyzed and a strategy to reduce the drag caused by the hub is sought. Also, the idea of fairing installation is confirmed by a wind tunnel test.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.26-33
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• 2014

This study addresses the control problem of an unmanned aerial vehicle (UAV) during the transition period when the flying mode changes from hovering to translational motion in the horizontal plane. First, we introduce a compensation algorithm that improves height stabilization and reduces altitude drop. The main principle is to incorporate pitch and roll measurements into the feedforward term of the altitude controller to provide a larger thrust force. To further improve altitude control, we propose the fuzzy logic controller that improves system behavior. Simulation results presented in the paper highlight the effectiveness of the proposed controllers.

• Aerospace Engineering and Technology
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• v.10 no.2
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• pp.11-19
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• 2011

A localization development of Composite rotor blade for Smart Unmanned Aerial Vehicle(SUAV) has been conducted. Overall localization development encompassed selection of domestic composite material having similar properties to that of original one at its best, coupon tests for data base of new material properties, re-calculation of blade sectional properties, and validation of structural/dynamic design requirements such as isolation of rotor natural frequency from excitation, static and fatigue strength, aeroelastic stability. The results of all these activities are described. This paper briefly discusses the improved manufacturing process for the localization of SUAV blade.