• 한국항공운항학회지
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• 제21권1호
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• pp.23-29
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• 2013

This paper presents a tracking filter of radar beacon system (RBS) for automatic takeoff and landing of an unmanned aerial vehicle. The proposed tracking filter is designed as the decoupled tracking filter to reduce the computational burden. Also, an adaptive estimation method of the measurement error covariance is proposed to provide an improved tracking performance compared to the conventional decoupled tracking filter whenever the accuracy of RBS observations is degraded. 100 times Monte Carlo runs performed to analyze the performance of the proposed tracking filter in case of normal operation and degraded operations, respectively. The simulation results show that the proposed tracking filter provides the improved tracking accuracy in comparison with the conventional decoupled tracking filter.

• 대한조선학회논문집
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• 제59권2호
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• pp.125-133
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• 2022

This paper proposes a fault detection method for a Unmanned Surface Vehicle (USV) with overactuated system. Current status information for fault detection is expressed as a scalogram image. The scalogram image is obtained by wavelet-transforming the USV's control input and sensor information. The fault detection scheme is based on Convolutional Neural Network (CNN) algorithm. The previously generated scalogram data was transferred learning to GoogLeNet algorithm. The data are generated as scalogram images in real time, and fault is detected through a learning model. The result of fault detection is very robust and highly accurate.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 춘계학술대회 논문집
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• pp.727-728
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• 2007

• 한국항행학회논문지
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• 제25권3호
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• pp.256-266
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• 2021

국내외 연구들은 무인항공기 사고의 주원인으로 인적요인을 지목하고 있고, 이러한 인적요인을 효과적으로 분석하는 기법으로 HFACS를 소개하고 있다. 현재까지는 HFACS를 이용해 무인항공기 사고의 인적요인을 분석했던 국내외 사례는 주로 군용 무인항공기가 대상이었는데, 항공사고를 유발하는 인적요인 정보를 분석하여 객관적 원인 규명과 유사 사고 예방 도구로 사용할 수 있는 HFACS가 국내 민간 무인항공기 분야에서도 활용이 필요한 시점이다. 특히, 국내 민간 무인항공기의 성능과 운용 여건을 고려한 HFACS 적용중점을 식별한다면 사고 발생 시 원인 규명과 재발 방지에 큰 도움이 될 것으로 예상된다. 본 연구는 HFACS version 7.0을 근간으로 우리나라 항공철도사고조사위원회가 수행했던 사고조사 결과보고서 자료를 분석하여 국내 민간 무인항공기 사고조사에 활용할 수 있는 HFACS 적용중점을 식별하였다.

• 한국군사과학기술학회지
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• 제16권2호
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• pp.95-100
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• 2013

Localization is very important for the autonomous navigation of Unmanned Ground Vehicles; however, it is difficult that they have a precise Inertial Navigation System(INS) sensor, especially Small Unmanned Ground Vehicle(SUGV). Moreover, there are some condition such as denial of global position system(GPS), GPS/INS integrated system is not robust. This paper proposes the estimation algorithm with optical flow sensor and INS. Being compared with previous researches, the proposed algorithm is suitable for skid steering vehicles. We revised the measurement model of previous research for the accuracy of side direction position. Experimental results were performed to verify the algorithm, and the result showed an excellent performance.

• International Journal of Aeronautical and Space Sciences
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• 제11권2호
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• pp.69-79
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• 2010

This paper describes the experimental framework for the control system design and validation of a rotorcraft unmanned aerial vehicle (UAV). Our approach follows the general procedure of nonlinear modeling, linear controller design, nonlinear simulation and flight test but uses an indoor-installed multi-camera system, which can provide full 6-degree of freedom (DOF) navigation information with high accuracy, to overcome the limitation of an outdoor flight experiment. In addition, a 3-DOF flying mill is used for the performance validation of the attitude control, which considers the characteristics of the multi-rotor type rotorcraft UAV. Our framework is applied to the design and mathematical modeling of the control system for a quad-rotor UAV, which was selected as the test-bed vehicle, and the controller design using the classical proportional-integral-derivative control method is explained. The experimental results showed that the proposed approach can be viewed as a successful tool in developing the controller of new rotorcraft UAVs with reduced cost and time.

• International Journal of Aeronautical and Space Sciences
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• 제11권2호
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• pp.98-109
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• 2010

This paper deals with a new method of unmanned aerial vehicle (UAV) recovery when a UAV fails to get a global positioning system (GPS) signal at an unprepared site. The proposed method is based on the simultaneous localization and mapping (SLAM) algorithm. It is a process by which a vehicle can build a map of an unknown environment and simultaneously use this map to determine its position. Extensive research on SLAM algorithms proves that the error in the map reaches a lower limit, which is a function of the error that existed when the first observation was made. For this reason, the proposed method can help an inertial navigation system to prevent its error of divergence with regard to the vehicle position. In other words, it is possible that a UAV can navigate with reasonable positional accuracy in an unknown environment without the aid of GPS. This is the main idea of the present paper. Especially, this paper focuses on path planning that maximizes the discussed ability of a SLAM algorithm. In this work, a SLAM algorithm based on extended Kalman filter is used. For simplicity's sake, a blimp-type of UAV model is discussed and three-dimensional pointed-shape landmarks are considered. Finally, the proposed method is evaluated by a number of simulations.

• 한국수소및신에너지학회논문집
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• 제23권3호
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• pp.250-255
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• 2012

In this paper, the development and performance analysis of a fuel cell-powered unmanned aerial vehicle is described. A fuel cell system featuring 1 kW proton exchange membrane fuel cell combined with a highly pressurized fuel supply system is proposed. For the higher fuel consumption efficiency and simplification of overall system, dead-end type operation is chosen and each individual system such as purge system, fuel supply system, cooling system is developed. Considering that fluctuation of exterior load makes it hard to stabilize fuel cell performance, the power management system is designed using a fuel cell and lithium-ion battery hybrid system. After integration of individual system, the performance of unmanned aerial vehicle is analyzed using data from flight and laboratory test. In the result, overall system was properly operated but for more duration of flight, research on weight lighting and improvement of fuel efficiency is needed to be progressed.

• 대한임베디드공학회논문지
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• 제3권4호
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• pp.244-250
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• 2008

This paper describes the design and implementation of an unmanned ground vehicle (UGV) and also estimates how well autonomous navigation and remote control of UGV can be performed through the optimized arbitration of several sensor data, which are acquired from vision, obstacle detection, positioning system, etc. For the autonomous navigation, lane detection and tracing, global positioning, and obstacle avoidance are necessarily required. In addition, for the remote control, two types of experimental environments are established. One is to use a commercial racing wheel module, and the other is to use a haptic device that is useful for a user application based on virtual reality. Experimental results show that autonomous navigation and remote control of the designed UGV can be achieved with more effectiveness and accuracy using the proper arbitration of sensor data and navigation plan.

• 한국군사과학기술학회지
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• 제12권5호
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• pp.549-556
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• 2009

One of the basic technology for implementing the autonomy of UGV(Unmanned Ground Vehicle) is a path planning algorithm using obstacle and raw terrain information which are gathered from perception sensors such as stereo camera and laser scanner. In this paper, we propose a generation method of DVGM(Directional Velocity Grid Map) which have traverse speed of UGV for the five heading directions except the rear one. The fuzzy system is designed to generate a resonable traveling speed for DVGM from current patch to the next one by using terrain slope, roughness and obstacle information extracted from raw world model data. A simulation is conducted with world model data sampled from real terrain so as to verify the performance of proposed fuzzy inference system.