• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.1-6
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• 2020

UAV (Unmanned Aerial Vehicles) are used widely for military purposes because they are more economical than general manned aircraft and satellites, and have easy access to the object. Recently, owing to the development of IT technology, UAV equipped with various sensors have been released, and their use is increasing in a wide range of fields, such as surveying, agriculture, meteorological observation, communication, broadcasting, and sports. An increasing number of studies and attempts have made use of it. On the other hand, existing research was related mostly to photogrammetry, but there has been a lack of analytical research on LiDAR (Light Detection And Ranging). Therefore, this study examined the characteristics of a UAV LiDAR sensor for the application of a geospatial information field. In this study, the performance of commercialized LiDAR sensors, such as the acquisition speed and the number of echoes, was investigated, and data acquisition and analysis were conducted by selecting Surveyor Ultra and VX15 models with similar accuracy and data acquisition distances. As a result, a DSM of each study site was generated for each sensor, and the characteristics of data density, precision, and acquisition of ground data from vegetation areas were presented through comparison. In addition, the UAV LiDAR sensor showed an accuracy of 0.03m ~ 0.05m. Hence, it is necessary to select equipment considering the characteristics of data for effective use. In the future, the use of UAV LiDAR may be suggested if additional data can be obtained and analyzed for various areas, such as urban areas and forest areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.23-33
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• 2020

Recently, high-resolution images can be easily acquired using UAV (Unmanned Aerial Vehicle), so that it is possible to produce small area observation and spatial information at low cost. In particular, research on the generation of cover maps in crop production areas is being actively conducted for monitoring the agricultural environment. As a result of comparing classification performance by applying RF(Random Forest), SVM(Support Vector Machine) and CNN(Convolutional Neural Network), deep learning classification method has many advantages in image classification. In particular, land cover classification using satellite images has the advantage of accuracy and time of classification using satellite image data set and pre-trained parameters. However, UAV images have different characteristics such as satellite images and spatial resolution, which makes it difficult to apply them. In order to solve this problem, we conducted a study on the application of deep learning algorithms that can be used for analyzing agricultural lands where UAV data sets and small-scale composite cover exist in Korea. In this study, we applied DeepLab V3 +, FC-DenseNet (Fully Convolutional DenseNets) and FRRN-B (Full-Resolution Residual Networks), the semantic image classification of the state-of-art algorithm, to UAV data set. As a result, DeepLab V3 + and FC-DenseNet have an overall accuracy of 97% and a Kappa coefficient of 0.92, which is higher than the conventional classification. The applicability of the cover classification using UAV images of small areas is shown.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.1-14
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• 2019

In rural areas, composting is a source of non-point pollutants. However, as the quantitative distribution and loading have not been estimated, it is difficult to determine the effect of composting on stream water quality. In this study, composting datum acquired by unmanned aerial vehicle(UAV) was verified by using terrestrial LiDAR, and the management status and load change of the composting was investigated by UAV with manual control flight, thereby obtaining the basic data to determine the effect on the water system. As a result of the comparative accuracy assessment based on terrestrial LiDAR, the difference in the digital surface model(DSM) was within 0.21m and the accuracy of the volume was 93.24%. We expect that the accuracy is sufficient to calculate and utilize the composting load acquired by UAV. Thus, the management status of composting can be investigated by UAV. As the total load change of composting were determined to be $1,172.16m^3$, $1,461.66m^3$, and $1,350.53m^3$, respectively, the load change of composting could be confirmed. We expect that the results of this study can contribute to efficient management of non-point source pollution by UAV.

• Journal of Aerospace System Engineering
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• v.2 no.4
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• pp.38-43
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• 2008

Since UAV has been developed, the demand of uav is increasing because of the advantage which are no injury people and less cost. Also, it has easy maintenance and adaptation because it will carry out each mission by only change payload. So, in this study, we performed aircraft design and manufacturing which it could have maximum payload weight when consider each mission has different weight of payload

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.11-14
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• 2004

In this paper, we propose a method to target searching method that have unstable limit cycles in a chaos trajectory surface. We assume all targets in the chaos trajectory surface have a Van der Pol equation with an unstable limit cycle When a chaos UAV meet the target in the Arnold equation, Chua's equation trajectory, the target absorptive the UAV

• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.427-430
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• 2006

The ground effect on tilt-rotor UAV is analyzed by simulating the hovering UAV for various altitudes. Ground effect increases pressure beneath the UAV body and generates additional lifting force. The ground effect diminishes at altitude 3m and hovering UAV generates constant lifting force above 3m.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.141.3-141
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• 2001

Since 1990´s, there has been many researches for the development of the Unmanned Aerial Vehicle (UAV). Especially, for the development of digital electronics, the technologies of UAV toward to the miniaturization low-cost, and high reliability. Therefore, recent trends for the development of UAV are focused on the development modern Flight Control System (FCS). In this paper, focusing on the FCS, the development process for Sejong Unmanned Research Vehicle -1 (SURV-1) from design to flight test is presented.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.40.3-40
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• 2002

Unmanned Aerial Vehicle(UAV) needs autonomous flight capability to accomplish various mission objectives. For this objective, the autopilot is a key element in the UAV system design. The principal goal of autopilot is to guide the aircraft under varying external disturbances throughout the mission phases. The external disturbances include gravity effect, wind gust, and other unexpected obstacles. The gust affects the aircraft flight performance to a significant extent. UAV's low speed, light weight, and the absence of human judgment makes un predictable gust more dangerous. Autopilot design in general takes the gust effect into account to satisfy flight performance requirement. In this study..

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.251-252
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• 2019

본 논문에서는 소형 무인항공체 (UAV, Unmanded Aerial Vehicle)가 제한된 공역 (airspace)에서 발생할 수 있는 상황을 예측할 수 있는 시뮬레이터를 개발하여 테스트를 수행한 결과를 보인다. 많은 소형 UAV가 밀집해서 비행하는 상황을 가정하여 충돌의 발생 가능성을 줄이기 위해 공역을 고도에 따라 계층으로 나누었으며 시뮬레이터에 이를 반영하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.95-105
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• 2020

In order to promote efficient coastal management, it is important to continuously monitor the characteristics of the terrain, which are changed by various factors. In this study, time series UAV images were taken of Gyeokpo beach. And the standard deviation of ±11cm(X), ±10cm(Y), and ±15cm(Z) was obtained as a result of comparing with the VRS measurement performance for UAV position accuracy evaluation. Therefore, it was confirmed that the tolerance of the digital map work rule was satisfied. In addition, as a result of monitoring the erosion and sedimentation changes using the DSM(digital surface model) constructed through UAV images, an average of 0.01 m deposition occurred between June 2018 and December 2018, and in December 2018 and June 2019. It was analyzed that 0.03m of erosion occurred. Therefore, 0.02m of erosion occurred between June 2018 and June 2019. From the topographical change analysis results, the area of erosion and sediment height was analyzed, and the area of erosion and sedimentation was widely distributed in the ±0.5m section. If we continuously monitor the topographical changes in the coastal regions by using the 3D terrain modeling results using the time series UAV images presented in this study, we can support the coastal management tasks such as supplement or dredging of sand.