• Aerospace Engineering and Technology
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• v.4 no.2
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• pp.7-14
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• 2005

This paper describes development of automatic flight control system for an unmanned target drone. Current target drone is operated by pilot control of on-board servo motor via remote control system. Automatic flight control system for the target drone greatly reduces work load of ground pilot and can increase application area of the drone. Most UAVs being operated nowdays use high-priced sensors as AHRS and IMU to measure the attitude, but those are costly. This paper introduces the development of low-cost automatic flight control system with low-cost sensors. The integrated automatic flight control system has been developed. The performance of automatic flight control system is verified by flight test.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1189-1195
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• 2014

This paper addresses a Moving Target Indication (MTI) algorithm which can be used for small Unmanned Aerial Vehicles (UAVs) equipped with image sensors. MTI is a system (or an algorithm) which detects moving objects. The principle of the MTI algorithm is to analyze the difference between successive image data. It is difficult to detect moving objects in the images recorded from dynamic cameras attached to moving platforms such as UAVs flying at low altitudes over a variety of terrain, since the acquired images have two motion components: 'camera motion' and 'object motion'. Therefore, the motion of independent objects can be obtained after the camera motion is compensated thoroughly via proper manipulations. In this study, the camera motion effects are removed by using wiener filter-based image registration, one of the non-parametric methods. In addition, an image pyramid structure is adopted to reduce the computational complexity for UAVs. We demonstrate the effectiveness of our method with experimental results on outdoor video sequences.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.11
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• pp.1013-1020
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• 2011

This paper deals with the tracking problem of a moving target using multiple unmanned aerial vehicles. A decentralized extended information filter is designed to cooperatively estimate the position and the velocity of the moving target. The extended information filter is adopted to consider the range and the line-of-sight angle as measurement data. The decentralized scheme is applied to enhance the estimation performance using the information provided by other vehicles. Numerical simulation is performed to verify the tracking performance of the proposed decentralized filters.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.158-163
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• 2013

The fusion of the GPS (Global Positioning System) and DR (Dead Reckoning) is widely used for position and latitude estimation of vehicles such as a mobile robot, aerial vehicle and marine vehicle. Among the many types of aerial vehicles, grater focus is given on the quad-rotor and accuracy of the position information is becoming more important. In order to exactly estimate the position information, we propose the fusion method of GPS and Gyroscope sensor using the DEKF (Dual Extended Kalman Filter). The DEKF has an advantage of simultaneously estimating state value and a parameter of dynamical system. It can also be used even if state value is not available. In order to analyze the performance of DEKF, the computer simulation for estimating the position, the velocity and the angle in a circle trajectory of quad-rotor was done. As it can be seen from the simulation results using own proposed DEKF instead of EKF on own fusion method in the navigation of a quad-rotor gave better performance values.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.5
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• pp.466-474
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• 2020

Semi-active laser missile systems with high accuracy are necessary to asymmetric threats, such as UAV(Unmanned Aerial Vehicle). They are usually used to attack stationary or slow moving targets, therefore we should study on the laser designator which can detect and track fast moving targets in order to deal with UAV. In this study, design specifications are came up through performance analysis of existing laser designators, and laser designation method for fast moving target is developed. The detection and tracking performance of developed laser designator are verified through inside/outside tests on ground/aerial stationary/moving targets. Through this study, we obtain laser designator techniques that could be applied to actual semi-active laser missile systems.

• Natural Product Sciences
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• v.9 no.4
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• pp.299-303
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• 2003

For the screening of inhibitors of sterol biosynthesis from natural products, a simple and rapid assay method was developed using recombinant yeast carrying human lanosterol synthase, main target of this assay method. Sterol biosynthesis inhibition activity was monitored only by the inhibition of growth of the recombinant yeast. By changing the substrate, this assay method can figure out which step is inhibited in the sterol biosynthesis by the test material. With this assay method total 102 plant samples were screened for their inhibitory activity of sterol biosynthesis. Among plant water extracts screened, 11 plant samples showed inhibitory activity on sterol biosynthesis in ergosterol (-) medium. For selection of the specific inhibitory materials, 11 plant samples were reassayed in ergosterol (+) medium. After all 5 plant samples, Abutilon avicennae Gaertn. (stem), Alnus japonica Steud. (stem), Amaranthus mangostanus L. (aerial part), Philadelphus schrenckii Pupr. (leaf) and Pimpinelia brachycarpa Nakai (aerial part), showed specific inhibitory activity.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.101-106
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• 2010

Researches on air-ground robot cooperating system has been made recently. The cooperation among homogeneous robots focused on the architecture of the system, quality and influence of the communication. In contrast, the cooperation among heterogeneous robots such as aerial vehicle and ground vehicle robots has not been much handled. There are a couple of main points for those air-ground cooperating robots. One is using UAV (Unmanned Aerial Vehicle) as an extra sensor of UGV (Unmanned Ground Vehicle). This kind of application is usually used in situations such as guiding UGV to an appropriate path which could be better determined from the eye in the sky as UAV. The other main application of air-ground cooperating robot system is the localization. By combining sensor information from both UAV and UGV, the robot system as a whole can localize a target object or find features in the environment with better performance than UGV or UAV alone. Although these applications are recently studied in many different ways and devices, there are still a lot of possibilities in the field of air-ground cooperating robot systems. We introduce those research fields in this paper.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_1
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• pp.125-137
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• 2020

Tracking micro-sized insects is one of the challenges of protecting ecosystems and biodiversity. In this study, we propose an approach for the autonomous tracking of micro-sized flying insects, and develop an unmanned aerial vehicle (UAV)-based robotic system. The Kalman filter is applied to the received signal strength emitted from radio telemetry to estimate the position while reducing the measurement error and noise. The autonomous tracking strategy is a method in which the UAV rotates at one point to measure the signal strength and control its position in the strongest direction of the signal. We also design a system architecture comprising a tracking sensor system and a UAV system for micro-sized insects. The estimation and autonomous tracking of the target position by the proposed system are verified and evaluated through dynamic simulation. Therefore, in this study, we propose and validate a UAV-based tracking system for micro-sized flying insects, which has not been proposed in studies conducted thus far.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.4
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• pp.266-273
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• 2019

The efficiency and effectiveness of mission performance can be greatly changed according to the operating conditions such as the number of manned aircraft, flight altitude, and so on, in performing search and reconnaissance missions using a large number of small reconnaissance unmanned aerial vehicles. However, it is not easy to determine which operating conditions are most reasonable. Therefore, in this study, we developed an unmanned airplane flight simulation that can detect and identify the target while avoiding collision according to autonomous flight, suggesting a way to derive operating conditions when operating a large number of unmanned aerial vehicles.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.89-96
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• 2021

In this study, a deep-learning image analysis model was established and validated for AI-based monitoring of the tidal flat ecosystem for marine protected creatures Ocypode stimpsoni and their habitat. The data in the study was constructed using an unmanned aerial vehicle, and the U-net model was applied for the deep learning model. The accuracy of deep learning model learning results was about 0.76 and about 0.8 each for the Ocypode stimpsoni and their burrow whose accuracy was higher. Analyzing the distribution of crabs and burrows by putting orthomosaic images of the entire study area to the learned deep learning model, it was confirmed that 1,943 Ocypode stimpsoni and 2,807 burrow were distributed in the study area. Through this study, the possibility of using the deep learning image analysis technology for monitoring the tidal ecosystem was confirmed. And it is expected that it can be used in the tidal ecosystem monitoring field by expanding the monitoring sites and target species in the future.