• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.27-36
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• 2017

In almost industries, such as the logistics industry, marine fisheries, agriculture, industry, and services, small unmanned aerial vehicles are used for aerial photographing or closing flight in areas where human access is difficult or CCTV is not installed. Also, based on the information of small unmanned aerial photographing, application research is actively carried out to efficiently perform surveillance, control, or management. In order to carry out tasks in a mission-based manner in which the set tasks are assigned and the tasks are automatically performed, the small unmanned aerial vehicles must not only fly steadily but also be able to charge the energy periodically, In addition, the unmanned aircraft need to land automatically and precisely at certain points after the end of the mission. In order to accomplish this, an automatic precision landing method that leads landing by continuously detecting and recognizing a marker located at a landing point from a video shot of a small UAV is required. In this paper, it is shown that accurate and stable automatic landing is possible even if simple template matching technique is applied without using various recognition methods that require high specification in using low cost general purpose small unmanned aerial vehicle. Through simulation and actual experiments, the results show that the proposed method will be made good use of industrial fields.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.2
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• pp.12-17
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• 2017

Manned aircraft structural design is based on structural safety factor of 1.5, and this safety factor is equivalent to a probability of failure of between 10-2 and 10-3. The target failure probability of FARs is between 10-6 and 10-9 per flight according to aircraft type. NATO released STANAG 4703 to established the airworthiness requirements for small UAV which is less than 150kg. STANAG 4703 requires the Target Level of Safety according to MTOW. The requirements of failure probability for small UAV is between 10-4 and 10-5. In this paper, requirements of airworthiness certification for small UAV were investigated and the relationship of safety factors to the probability of structural failure is analyzed to reduce measure of safety factor and structural weight of unmanned aircraft.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.1
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• pp.45-58
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• 2020

According to the Ministry of Land, Infrastructure and Transport press release ('18.12.21.) The amendment of the Aviation Business Act will reduce the capital requirements for aviation leisure operators and make it easier to enter aviation leisure businesses by improving regulations on small air transportation business. In addition, as the scale of the UAV(Unmanned Aerial Vehicle) sector is expected to increase globally, the dramatic increase in low altitude operating aircraft, including this, must be taken into account. The low altitude aircraft category is divided into small airplanes, helicopters, light aircrafts and ultra-light aircrafts, and instructors include school instructor pilots and student pilots, military and national helicopter pilots, and aviation leisure operators. In case of low altitude aircraft, there are cases of canceling operations due to low visibility and low clouds, and aircraft accidents due to excessive operation and sudden weather phenomenon. Therefore, in order to prevent low-altitude aircraft accidents, a safe flight plan based on weather conditions and weather forecasts and more accurate and local weather forecasts and weather forecast data are needed to prepare for the rapidly changing weather conditions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.4
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• pp.511-523
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• 2023

Research on the integration of unmanned aerial vehicles and deep learning for reinforced concrete damage detection is actively underway. Convolutional neural networks have a high impact on the performance of image classification, detection, and segmentation as backbones. The MobileNet, a pre-trained convolutional neural network, is efficient as a backbone for an unmanned aerial vehicle-based damage detection model because it can achieve sufficient accuracy with low computational complexity. Analyzing vanilla convolutional neural networks and MobileNet under various conditions, MobileNet was evaluated to have a verification accuracy 6.0~9.0% higher than vanilla convolutional neural networks with 15.9~22.9% lower computational complexity. MobileNetV2, MobileNetV3Large and MobileNetV3Small showed almost identical maximum verification accuracy, and the optimal conditions for MobileNet's reinforced concrete damage image feature extraction were analyzed to be the optimizer RMSprop, no dropout, and average pooling. The maximum validation accuracy of 75.49% for 7 types of damage detection based on MobilenetV2 derived in this study can be improved by image accumulation and continuous learning.

• Tunnel and Underground Space
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• v.25 no.5
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• pp.462-469
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• 2015

This study carried out a topographic survey at a small-scale open-pit limestone mine in Korea (the Daesung MDI Seoggyo office) using a popular rotary-wing unmanned aerial vehicle (UAV, Drone, DJI Phantom2 Vision+). 89 sheets of aerial photos could be obtained as a result of performing an automatic flight for 30 minutes under conditions of 100m altitude and 3m/s speed. A total of 34 million cloud points with X, Y, Z-coordinates was extracted from the aerial photos after data processing for correction and matching, then an orthomosaic image and digital surface model with 5m grid spacing could be generated. A comparison of the X, Y, Z-coordinates of 5 ground control points measured by differential global positioning system and those determined by UAV photogrammetry revealed that the root mean squared errors of X, Y, Z-coordinates were around 10cm. Therefore, it is expected that the popular rotary-wing UAV photogrammetry can be effectively utilized in small-scale open-pit mines as a technology that is able to replace or supplement existing topographic surveying equipments.

• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.1-6
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• 2014

Power system of the tilt-duct VTOL aerial robot has been developed. This paper focuses on the power train with small liquid-type engine for the R/C boat and presents the test results with design procedures. The hardware aspects of the power system include details about the hardware configurations for the interfaces with the vehicle. The ground test and tether test for measuring the thrust performance of vehicle and evaluating the endurance of power train carried out.

• Convergence Security Journal
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• v.20 no.1
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• pp.77-84
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• 2020

Due to the lack of a system that can detect/identify and strike North Korea's small unmanned aerial vehicles, no immediate response was made. In order to solve the problem of response, we should prepare for threats by developing weapons systems that can be immediately hit when identifying small-sized unmanned aerial vehicle detection radar and creating specialized research organizations for research and development of equipment.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.7
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• pp.737-742
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• 2013

Recently, unmanned aircrafts for safe measurement in hazardous locations have been developed. In a method of operation of unmanned aircraft vehicles (UAV), there are two methods of manual control and automatic control. Small UAVs are used for low altitude surveillance flights where unknown obstacles can be encountered. Obstacle avoidance is one of the most challenging tasks which the UAV has to perform with high level of accuracy. In this study, we used a laser range finder as an obstacle detector in automatic navigation of unmanned aircraft to patrol the destination automatically. We proposed a system to avoid obstacles automatically by measuring the angle and distance of the obstacle using the laser range finder.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.87-97
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• 2023

Unmanned aerial vehicles (UAVs) can capture high-resolution imagery from a variety of viewing angles and altitudes; they are generally limited to collecting images of small scenes from larger regions. To improve the utility of UAV-appropriated datasetsfor use with deep learning applications, multiple datasets created from variousregions under different conditions are needed. To demonstrate a powerful new method for integrating heterogeneous UAV datasets, this paper applies a combined segmentation network (CSN) to share UAVid and semantic drone dataset encoding blocks to learn their general features, whereas its decoding blocks are trained separately on each dataset. Experimental results show that our CSN improves the accuracy of specific classes (e.g., cars), which currently comprise a low ratio in both datasets. From this result, it is expected that the range of UAV dataset utilization will increase.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.971-980
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• 2021

Recently popularized drone technologies have revealed that low-cost small unmanned aerial vehicles(UAVs) can be a significant threat to prevailing power by operating in group or in swarms. Researchers in many countries have tried to utilize integrated swarm unmanned aerial system(SUAS) in the battlefield. Agency for Defense Development also identified four core technologies in developing SUAS: swarm control, swarm network, swarm information, and swarm collaboration, and the authors started researches on swarm control and network technologies in order to be able to operate vehicle platforms as the first stage. This paper introduces design and integration of SUAS consisting of small fixed-wing UAVs, swarm control and network algorithms, a ground control system, and a launcher, with which swarm control and network technologies have been verified by flight tests. 19 fixed-wing UAVs succeeded in swarm flight in the final flight test for the first time as a domestic research.