• 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 Solar Energy Society
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• v.32 no.spc3
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• pp.262-268
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• 2012

In the recent research technical solutions have been studied to integrate renewable energy into unmanned aerial vehicles to use it as the main power source. As the weight of the aerial vehicle body is essential for its performance, we consider to use light-weight solar cell technology. Furthermore fuel cells are also integrated create a highly energy-efficient aerial robot. In this paper, construction concept and software design of the tilt-rotor aerial vehicle GAORI is introduced which uses solar cells and fuel cells as power source. The future work direction and prognosis are discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.1
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• pp.78-84
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• 2006

This paper describes UAV (Unmanned Aerial Vehicle) control system which employs PC104 modules. It is controlled by application program based on Linux OS. This application consists of both Linux device driver in kernel-space and user application in user-space. In order to get data required in the unmanned flight, external devices are connected to PC104 modules. We explain how Linux device drivers deal with data transmitted by external devices and we account for how the user application controls UAV on the basis of data processed in the device driver as well. Furthermore we look into the role of GCS (Ground Control Station) which is to monitor the state of UAV.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.727-728
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• 2007

• International Journal of Aeronautical and Space Sciences
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• v.15 no.3
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• pp.258-266
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• 2014

We present a system for the real-time visual relative navigation of a fixed-wing unmanned aerial vehicle in a GPS-denied environment. An extended Kalman filter is used to construct a vision-aided navigation system by fusing the image processing results with barometer and inertial sensor measurements. Using a mean-shift object tracking algorithm, an onboard vision system provides pixel measurements to the navigation filter. The filter is slightly modified to deal with delayed measurements from the vision system. The image processing algorithm and the navigation filter are verified by flight tests. The results show that the proposed aerial system is able to maintain circling around a target without using GPS data.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.216-222
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• 2021

Recently, various robots are being used for the purpose of structural inspection or safety diagnosis, and their needs are also rising rapidly. Among the structural inspection using robots, a lot of researches has recently been conducted on inspection of various facilities and structures using an unmanned aerial vehicle (UAV). However, since GNSS (Global Navigation Satellite System) signals cannot be received in an environment near or below structures, the operation of UAVs has been done manually. For a stable autonomous flight without GNSS signals, additional technologies are required. This paper proposes the autonomous flight system for structural inspection consisting of simultaneous localization and mapping (SLAM), path planning, and controls. The experiments were conducted on an actual large bridge to verify the feasibility of the system, and especially the performance of the proposed SLAM algorithm was compared through comparative analysis with the state-of-the-art algorithms.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2D
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• pp.129-136
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• 2012

In the US, Japan and Germany the Aerial-Based Vehicle Detection System, which collects real-time traffic data using the Unmanned Aerial Vehicle (UAV), helicopters or fixed-wing aircraft has been developed for the last several years. Therefore, this study was done to find out whether the Aerial-Based Vehicle Detection System could be used for real-time traffic data collection. For this purpose the study was divided into two parts. In the first part the possibility of retrieving real-time traffic data such as travel speed from the aerial photographic image using the image processing technique was examined. In the second part the quality of the retrieved real-time traffic data was examined to find out whether the data are good enough to be used as traffic information source. Based on the results of examinations we could conclude that it would not be easy for the Aerial- Based Vehicle Detection System to replace the present Vehicle Detection System due to technological difficulties and high cost. However, the system could be effectively used to make the emergency traffic management plan in case of incidents such as abrupt heavy rain, heavy snow, multiple pile-up, etc.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.1
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1181-1188
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• 2014

In this paper, we propose a novel concept foran unmanned delivery service using a cooperative heterogeneous unmanned system consisting of a self-driving car and an unmanned aerial vehicle (UAV). The proposed concept is suitable to deliver parcels in high-density and high-rise urban or residential areas. In order to achieve the proposed concept, we will develop acooperative heterogeneous unmanned system. Customers can order goods using a smartphone application and the order information, including the position of the customer and the order time, and the package is transported automatically by the unmanned systems. The system assigns the tasks suitable for each unmanned vehicle by analyzing it based on map information. Performance is validated by experiments consisting of autonomous driving and flight tests in a real environment. For more evaluation, the landing position error analysis is performed using circular error probability (CEP).