• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.37-38
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• 2017

최근 방제 및 예찰과 같은 농작업에 단일 UAV(Unmanned Aerial Vehicle)시스템이 적용되고 있지만, 가반하중과 체공시간 등 기존시스템의 문제가 점차 대두되면서 작업 시간을 보다 단축시키고 작업 효율을 극대화 할 수 있는 농업용 멀티 UAV시스템의 필요성이 증대되고 있다. 본 논문에서는 작업자가 다수의 농업용 UAV를 효과적으로 제어할 수 있는 분산군집제어 알고리즘을 제안하며 알고리즘 검증 및 평가를 위한 시뮬레이터를 소개한다. 분산군집제어는 UAV 제어 계층, VP(Virtual Point) 제어 계층, 원격제어 계층으로 이루어진 3계층 제어구조를 가진다. UAV 제어 계층에서 각 UAV는 point mass로 모델링 되는 VP의 이상적인 경로를 추종하도록 제어한다. VP 제어 계층에서 각 VP는 입력 $p_i(t)=u^c_i+u^o_i+u^{co}_i+u^h_i$-(1)을 받아 제어되는데 여기서, $u^c_i{\in}{\mathbb{R}}^3$는 VP 사이의 충돌방지제어, $u^o_i{\in}{\mathbb{R}}^3$는 장애물과의 충돌방지제어, $u^{co}_i{\in}{\mathbb{R}}^3$는 UAV 상호간의 협조제어, $u^h_i{\in}{\mathbb{R}}^3$는 작업자로부터의 원격제어명령이다. (1)의 제어입력에서 충돌방지제어는 각 $u^i_c:=-{\sum\limits_{j{\in}{\eta}_i}}{\frac {{\partial}{\phi}_{ij}^c({\parallel}p_i-p_j{\parallel})^T}{{\partial}p_i}}$-(2), $u^o_c:=-{\sum\limits_{r{\in}O_i}}{\frac {{\partial}{\phi}_{ir}^o({\parallel}p_i-p^o_r{\parallel})^T}{{\partial}p_i}}$-(3)로 정의되면 ${\phi}^c_{ij}$와 ${\phi}^o_{ir}$는 포텐셜 함수를 나타낸다. 원격제어 계층에서 작업자는 햅틱 인터페이스를 통해 VP의 속도를 제어하게 된다. 이때 스케일변수 ${\lambda}$에 대하여 VP의 원격제어명령은 $u^t_i(t)={\lambda}q(t)$로 정의한다. UAV 시뮬레이터는 리눅스 환경에서 ROS(Robot Operating Systems)를 기반한 3차원 시뮬레이터인 Gazebo상에 구축하였으며, 마스터와 슬레이브 간의 제어 명령은 TCPROS를 통해 서로 주고받는다. UAV는 PX4 기반의 3DR Solo 모델을 사용하였으며 MAVROS를 통해 MAVLink 통신 프로토콜에 접속하여 UAV의 고도, 속도 및 가속도 등의 상태정보를 받을 수 있다. 현재 멀티 드론 시스템을 Gazebo 환경에 구축하였으며, 추후 시뮬레이터 상에 분산군집제어 알고리즘을 구현하여 검증 및 평가를 진행하고자 한다.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1092-1097
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• 2014

It is difficult to perform automatic formation flight of UAV (Unmanned Aerial vehicle) when GPS (Global Positionig System) is out of order or has a system error, since the relative position estimation in the flight group is impossible in that case. In this paper, we design a relative localization system for the automatic formation flight of UAV. For this purpose, we adopt digital beam forming (DBF) to estimate the angle with the central controller of the flight group and Particle Filtering scheme to compensate the estimation error of ToA (time of arrival) method. Computer simulation results present a proper distance between the central controller and a following unit to maintain the automatic formation flight.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.459-466
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• 2020

The sound collected through the multi-rotor unmanned aerial vehicle (UAV) includes the ego noise generated by the motor or propeller, or the wind noise generated during the flight, and thus the quality is greatly impaired. In a multi-rotor UAV environment, both the magnitude and phase of the target sound are greatly corrupted, so it is necessary to enhance the sound in consideration of both the magnitude and phase. However, it is difficult to improve the phase because it does not show the structural characteristics. in this study, we propose a CNN-based complex spectrogram enhancement method that removes noise based on complex spectrogram that can represent both magnitude and phase. Experimental results reveal that the proposed method improves enhancement performance by considering both the magnitude and phase of the complex spectrogram.

• Journal of Korea Multimedia Society
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• v.20 no.4
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• pp.593-605
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• 2017

In applications which are covered wide range, it is possible that one or more number of Unmanned Aerial Vehicle(UAV) squadrons are used to perform a mission. In this case, it is most important to communicate seamlessly between the UAV squadrons. In this paper, we applied the modified OLSR(OSLR-Pds) which can prediction for state of the link for the communication in UAV squadron, and applied the modified AOMDV which can build multi-path for the communication between UAV Squadrons. The mobility of nodes are modeled using Gauss-Markov algorithm, and relative speed between nodes were calculated by derive equation of movement, and thereby we can predict link state for in a squadron and between squadrons. An experiment for comparing AODV, AOMDV and the proposed routing protocol was conducted by three factors such as packet delivery ratio, end to end delay, and routing overhead. In experiment result, we make sure that the proposed protocol performance are superior in these three factors. However, if the density of the nodes constituting FANET are too low, and if the moving speed of node is very slow, there is no difference to others protocols.

• Journal of Aerospace System Engineering
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• v.14 no.5
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• pp.83-90
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• 2020

Disasters are causing significant damage to the lives and property of our society and are recognized as social problems that need to be solved nationally and globally. The 4th industrial revolution technologies affecting society as a whole such as the Internet of Things(IoT), Artificial Intelligence(AI), Drones(Unmanned Aerial Vehicles), and Big Data are continuously absorbed into the disaster and safety industries as scientific and technological tools for solving social problems. Very soon, twenty-nine domestic UAV-related organizations/companies will complete the construction of a multicopter type small UAV integrated system ('17~'20) that can be operated at disaster and security sites. The current work considers and proposes the mid-to-long term R&D direction of disaster UAV as a strategic asset of the national disaster response system. First, the trends of disaster and safety industry and policy are analyzed. Subsequently, the development status and future plans of small UAV, securing shortage technology, and strengthening competitiveness are analyzed. Finally, step-by-step R&D direction of disaster UAV in terms of development strategy, specialized mission, platform, communication, and control and operation is proposed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.31-38
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• 2012

The geo-referencing accuracy of the images acquired by a UAV based multi-sensor system is affected by the accuracy of the mounting parameters involving the relationship between a camera and a GPS/INS system as well as the performance of a GPS/INS system. Therefore, the estimation of the accurate mounting parameters of a multi-sensor system is important. Currently, we are developing a low altitude multi-sensor system based on a UAV, which can monitor target areas in real time for rapid responses for emergency situations such as natural disasters and accidents. In this study, we suggest a system calibration method for the estimation of the mounting parameters of a multi-sensor system like our system. We also generate simulation data with the sensor specifications of our system, and derive an effective flight configuration and the number of ground control points for accurate and efficient system calibration by applying the proposed method to the simulated data. The experimental results indicate that the proposed method can estimate accurate mounting parameters using over five ground control points and flight configuration composed of six strips. In the near future, we plan to estimate mounting parameters of our system using the proposed method and evaluate the geo-referencing accuracy of the acquired sensory data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1645-1653
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• 2014

In general, RGB, NIR, and thermal images are used for obtaining geospatial data. Such multiband images are collected via devices mounted on satellites or manned flights, but do not always meet users' expectations, due to issues associated with temporal resolution, costs, spatial resolution, and effects of clouds. We believe high-resolution, multiband images can be obtained at desired time points and intervals, by developing a payload suitable for a low-altitude, auto-piloted UAV. To achieve this, this study first established a low-cost, high-resolution multiband image collection system through developing a sensor and a payload, and collected geo-referencing data, as well as RGB, NIR and thermal images by using the system. We were able to obtain a 0.181m horizontal deviation and 0.203m vertical deviation, after analyzing the positional accuracy of points based on ortho mosaic images using the collected RGB images. Since this meets the required level of spatial accuracy that allows production of maps at a scale of 1:1,000~5,000 and also remote sensing over small areas, we successfully validated that the payload was highly utilizable.

• Proceedings of the Korean Information Science Society Conference
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• 2010.11a
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• pp.159-160
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• 2010

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.155-161
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• 2021

Recently, researches for military purposes such as precision tracking and mission completion using UAVs have been actively conducted. In particular, if the posture information of the leading UAV is estimated and the mission UAV uses this information to follow in stealth and complete its mission, the speed of the posture information estimation of the guide UAV must be processed in real time. Until recently, research has been conducted to accurately estimate the posture information of the leading UAV using image processing and Kalman filters, but there has been a problem in processing speed due to the sequential processing of the processing process. Therefore, in this study we propose a way to improve processing speed by applying methods that the image processing area is limited to the ROI area including the object, not the entire area, and the continuous processing is distributed to OpenMP-based multi-threads and processed in parallel with thread synchronization to estimate attitude information. Based on the experimental results, it was confirmed that real-time processing is possible by improving the processing speed by more than 45% compared to the basic processing, and thus the possibility of completing the mission can be increased by improving the tracking and estimating speed of the mission UAV.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1506-1513
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• 2019

Recently, as the industrial scope of multi-rotor unmanned aerial vehicles(UAV) is greatly expanded, the demands for data collection, processing, and analysis using UAV are also increasing. However, the acoustic data collected by using the UAV is greatly corrupted by the UAV's motor noise and wind noise, which makes it difficult to process and analyze the acoustic data. Therefore, we have studied a method to enhance the target sound from the acoustic signal received through microphones connected to UAV. In this paper, we have extended the densely connected dilated convolutional network, one of the existing single channel acoustic enhancement technique, to consider the inter-channel characteristics of the acoustic signal. As a result, the extended model performed better than the existed model in all evaluation measures such as SDR, PESQ, and STOI.