• Journal of the Semiconductor & Display Technology
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• v.17 no.1
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• pp.88-92
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• 2018

Currently drone industry has become one of the fast growing markets and the technology for unmanned aerial vehicles are expected to continue to develop at a rapid rate. Especially small unmanned aerial vehicle systems have been designed and utilized for the various field with their own specific purposes. In these fields the path planning problem to find the shortest path between two oriented points is important. In this paper we introduce a path planning strategy for an autonomous flight of unmanned aerial vehicles through reinforcement learning with self-positioning technique. We perform Q-learning algorithm, a kind of reinforcement learning algorithm. At the same time, multi sensors of acceleraion sensor, gyro sensor, and magnetic are used to estimate the position. For the functional evaluation, the proposed method was simulated with virtual UAV environment and visualized the results. The flight history was based on a PX4 based drones system equipped with a smartphone.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.4
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• pp.73-79
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• 2010

Flight test is the final and a mandatory process for the development of unmanned aerial vehicles(UAVs) as well as manned. Since most UAVs fly in a low speed and are prone to adverse weather conditions such as air turbulence, atmospheric weather environment around flight test regions will be a critical item to be considered for a flight test planning for UAVs. In this paper, we suggest a decision method for a UAV flight test schedule based on weather conditions of surface and upper atmospheres and also introduce a program for an effective flight test planning through weather forecasts.

• Proceedings of the Korea Society for Simulation Conference
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• 2004.05a
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• pp.142-147
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• 2004

It is very difficult to acquire high-fidelity flight test data for small airplanes such as typical unmanned aerial vehicles because MEMS-type small sensors used in the tests do not present reliable data in general. Besides, it is not practical to conduct expensive flight tests for low-cost small airplanes in order to simulate their flight characteristics. A practical approach to obtain acceptable flight data, including stability and control derivatives and data of weight and balance, is proposed in this study. Aircraft design software such as Darcorp's AAA is used to generate aerodynamic data for small airplanes, and moments of inertia are calculated using CATIA, structural design software. These flight data from simulation software are evaluated subjectively and tailored using simulation flight by experienced pilots, based on the certified procedures in FAA AC 120-45A and 40B, which are used for manned airplane simulators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.595-609
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• 2020

In this study, we propose a decentralized mathematical model for predictive control of a system of multi-autonomous unmanned aerial vehicles (UAVs), also known as drones. Being decentralized and autonomous implies that all members make their own decisions and fly depending on the dynamic information received from other unmanned aircraft in the area. We consider a variety of realistic characteristics, including time delay and communication locality. For this flocking flight, we do not possess control for central data processing or control over each UAV, as each UAV runs its collision avoidance algorithm by itself. The main contribution of this work is a mathematical model for stable group flight even in adverse weather conditions (e.g., heavy wind, rain, etc.) by adding Gaussian noise. Two of our proposed variance control algorithms are presented in this work. One is based on a simple biological imitation from statistical physical modeling, which mimics animal group behavior; the other is an algorithm for cooperatively tracking an object, which aligns the velocities of neighboring agents corresponding to each other. We demonstrate the stability of the control algorithm and its applicability in autonomous multi-drone systems using numerical simulations.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.2
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• pp.212-217
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• 2014

Micro Aerial Vehicles (MAVs) are useful devices to assess new features that may be utilized in a full size aircraft to enhance performance or to increase endurance. In this article, sources for energy saving in the micro air vehicles are initially addressed. Then, by specifying the important parameters on energy consumption of an aircraft, a feasibility study is conducted to assess the benefit of using solar cells to increase flight endurance. Next, a new solar cell has been designed and optimized for MAVs. This cell consists of a multiple quantum wells for which the quantum factor and the absorption coefficient are calculated by solving the Shrodinger equation using MATLAB software. Then, the manner and influence of MAVs parameters using the solar cells are examined to suggest optimal planform for different purposes. In order to increase flight endurance, it is noted that by using appropriate planform and the optimized solar cells, flight endurance can be increased by more than 30 percent.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.97-107
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• 2011

This paper describes efficient flight control algorithms for building a reconfigurable ad-hoc wireless sensor networks between nodes on the ground and airborne nodes mounted on autonomous vehicles to increase the operational range of an aerial robot or the communication connectivity. Two autonomous flight control algorithms based on adaptive gradient climbing approach are developed to steer the aerial vehicles to reach optimal locations for the maximum communication throughputs in the airborne sensor networks. The first autonomous vehicle control algorithm is presented for seeking the source of a scalar signal by directly using the extremum-seeking based forward surge control approach with no position information of the aerial vehicle. The second flight control algorithm is developed with the angular rate command by integrating an adaptive gradient climbing technique which uses an on-line gradient estimator to identify the derivative of a performance cost function. They incorporate the network performance into the feedback path to mitigate interference and noise. A communication propagation model is used to predict the link quality of the communication connectivity between distributed nodes. Simulation study is conducted to evaluate the effectiveness of the proposed reconfigurable airborne wireless networking control algorithms.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.1021-1031
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• 2020

With the advent of industry 4.0 technologies like the artificial intelligence and the autonomous flight, 'Urban Air Mobility (UAM)' is being considered as an effective alternative to resolve the ground urban traffic congestion. Accordingly, many companies in the world including Korea are investigating on the development of UAM vehicles and operation systems. In this study, after identifying and classifying the essential elements of the UAM operation, the UAM system operational concept has been derived, then detailed analyses for each element has been performed. Based on the conceptual analysis of the UAM operation system, UAM flight routes in Seoul and Gyeong-In area have been established and confirmed to be operable through the performance analysis of UAM vehicles. The flight route analysis in this study is expected to be applied to UAM flight routes establishment in various cities in the future.

• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.19-29
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• 2002

Decentralized filtering for a formation flight instrumentation system by INS/GPS integration is considered in this paper. An elaborate tuning method of the measurement noise covariance is suggested to compensate modeling errors caused by decentralizing the extended Kalman filter. It does not require large data transfer between formation vehicles. Covariance analysis exhibits the superior performance of the proposed approach when compared with the existent decentralized filter and the global filter, which has the target-filter performance.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.139-144
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• 2004

The flight control system designed for an unmanned airship, which is under development by KARI, is in reduced. First, the dynamic characteristics of the airship are addressed, which are fairly different from those of the nominal aircraft. In order to implement autonomous flight for the unmanned airship, flight control logic is designed including autopilot and guidance law. The autopilot is designed under consideration of the velocity region of the unmanned airship. The guidance laws are implemented in main operational modes such as point navigation, station keeping and spiral up/down for emergency return. Their simulation results are also presented in order to validate performances of the flight control system.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.4
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• pp.81-86
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• 2016

Unmanned aerial vehicles(UAVs) are increasingly used in civilian areas as well as in military areas due to the technological advancement of UAVs. In response to the increasing demand in UAVs, many studies are under way to integrate the airspace between manned aircraft and UAV. The development of flight test can secure the performance and flight characteristics of the designed aircraft. And the capability of research and development can be expanded through the accumulation of technical data. It is also essential to verify the correct performance and characteristics of development aircraft themselves. In this paper, we propose development flight test procedures and items for civilian UAVs.