• Transactions of the Korean hydrogen and new energy society
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• v.23 no.3
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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.

• Composites Research
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• v.32 no.1
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• pp.45-49
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• 2019

Fiber reinforced composites fabricated by the resin film infusion (RFI) process, which is one of the outof-autoclave process, have the advantage of significantly reducing the processing cost in large structures while having excellent mechanical properties and uniform impregnation of the resin. In this study, we applied RFI carbon fiber composites to unmanned aerial vehicle structures to improve structural safety and achieve weight reduction. The tensile test results showed that the strength was 46% higher than that of generic T300 grade plain weave carbon fiber composites. As a result of the layup design and finite element analysis of the composite wing structure using the above material properties, the wing tip deflection is decreased by 31%, the structural safety factor is increased by 28% and the weight of the entire structure can be reduced by more than 10% compared to the reference model using glass fiber composite material.

• 한국정보통신설비학회:학술대회논문집
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• 2003.08a
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• pp.376-378
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• 2003

본 논문에서는 2002년도에 KT에서 개발한 내경 1,000mm의 무인통신구를 건설 할 수 있는 마이크로터널링 장비에 대해 소개하고자 한다. 개발된 장비는 3D 기법을 이용한 최첨단 기법을 통하여 개발되었으며, 소형 굴진기의 취약점인 장애물 돌파능력을 보완하기 위하여 막장으로 진입이 가능한 구조로 되어있다. 따라서 굴진 중 장애물에 직면했을 경우 막장을 통하여 장애물을 효과적으로 제거할 수 있으며, 이 막장 진입통로를 이용하여 면판의 비트와 롤러커터를 교체할 수 있으므로 장거리 굴진이 가능하다. 그리고 굴진작업 시 필요한 원압잭과 후방설비인 Desander, 송 배니펌프등의 주변설비를 Operating Room에서 통합관리 할 수 있는 터널링 관리시스템을 개발하여 적용함으로써 보다. 효율적인 굴진관리를 수행할 수 있는 특징을 갖고 있다. 이렇게 개발된 장비와 시스템은 시험 시공을 통해 그 성능을 확인하였으며, 여기서 그 개발 과정 및 시험 시공 결과에 대해 기술하고자 한다.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.87-99
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• 2005

We present in this paper the stabilization (tracking) with motion planning of the six independent configurations of a mini unmanned areal vehicle equipped with four streamlined rotors. Naturally, the yaw-dynamic can be stabilized without difficulties and independently of other motions. The remaining dynamics are linearly approximated around a small roll and pitch angles. It will be shown that the system presents a flat output that is likely to be useful in the motion generation problem. The tracking feedback controller is based on receding horizon point to point steering. The resulting controller involves the lift (collective) time derivative for what flatness and feedback linearization are used. Simulation tests are performed to progress in a region with approximatively ten-meter-buildings.

• ETRI Journal
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• v.36 no.6
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• pp.968-978
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• 2014

Autonomous vehicle technology based on information technology and software will lead the automotive industry in the near future. Vehicle localization technology is a core expertise geared toward developing autonomous vehicles and will provide location information for control and decision. This paper proposes an effective vision-based localization technology to be applied to autonomous vehicles. In particular, the proposed technology makes use of numerical maps that are widely used in the field of geographic information systems and that have already been built in advance. Optimum vehicle ego-motion estimation and road marking feature extraction techniques are adopted and then combined by an extended Kalman filter and particle filter to make up the localization technology. The implementation results of this paper show remarkable results; namely, an 18 ms mean processing time and 10 cm location error. In addition, autonomous driving and parking are successfully completed with an unmanned vehicle within a $300m{\times}500m$ space.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.160-167
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• 2023

This study focuses on the development of a Last-Mile delivery service using unmanned vehicles to deliver goods directly to the end consumer utilizing drones to perform autonomous delivery missions and an image-based precision landing algorithm for handoff to a robot in an intermediate facility. As the logistics market continues to grow rapidly, parcel volumes increase exponentially each year. However, due to low delivery fees, the workload of delivery personnel is increasing, resulting in a decrease in the quality of delivery services. To address this issue, the research team conducted a study on a Last-Mile delivery service using unmanned vehicles and conducted research on the necessary technologies for drone-based goods transportation in this paper. The flight scenario begins with the drone carrying the goods from a pickup location to the rooftop of a building where the final delivery destination is located. There is a handoff facility on the rooftop of the building, and a marker on the roof must be accurately landed upon. The mission is complete once the goods are delivered and the drone returns to its original location. The research team developed a mission planning algorithm to perform the above scenario automatically and constructed an algorithm to recognize the marker through a camera sensor and achieve a precision landing. The performance of the developed system has been verified through multiple trial operations within ETRI.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.829-846
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• 2018

Crop monitoring can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. But, traditional monitoring has used field measurements involving destructive sampling and laboratory analysis, which is costly and time consuming. Unmanned Aerial vehicle (UAV) could be effectively applied in a field of crop monitoring for estimation of cultivated area, growth parameters, growth disorder and yield, because it can acquire high-resolution images quickly and repeatedly. And lower flight altitude compared with satellite, UAV can obtain high quality images even in cloudy weather. This study examined the possibility of utilizing UAV in the field of crop monitoring and was to suggest the application method for production of crop status information from UAV.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.172-177
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• 2004

This paper presents the results of the structural analysis and optimal design of frames of the UUV(Unmanned Underwater vehicle) to be operated at 6000m depth in the ocean. The structure of the UUV system can be classified into two structure, Launcher ana ROV. Frame of the launcher will be made by Galvanized Steel which has high strength and corrosion-resistant but this material has high specific gravity for tile object to be weight in the water Similarly, ROV will be made by AI6061-T6, and frame of the ROV will be fix many instruments and syntactic buoyancy materials. Before fabrication of tile frame, we performed sensitivity analysis - change in weight due to $\pm1\%$ change in design variables, for easy choice by change of dimension of the frame.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.547-553
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• 2021

Dynamic object recognition is an important task for autonomous vehicles. Since dynamic objects exhibit a higher collision risk than static objects, our own trajectories should be planned to match the future state of moving elements in the scene. Time information such as optical flow can be used to recognize movement. Existing optical flow calculations are based only on camera sensors and are prone to misunderstanding in low light conditions. In this regard, to improve recognition performance in low-light environments, we applied a normalization filter and a correction function for Gamma Value to the input images. The low light quality improvement algorithm can be applied to confirm the more accurate detection of Object's Bounding Box for the vehicle. It was confirmed that there is an important in object recognition through image prepocessing and deep learning using YOLO.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.614-630
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• 2023

Dead trees significantly impact forest production and the ecological environment and pose constraints to the sustainable development of forests. A lightweight YOLOv4 dead tree detection algorithm based on unmanned aerial vehicle images is proposed to address current limitations in dead tree detection that rely mainly on inefficient, unsafe and easy-to-miss manual inspections. An improved logarithmic transformation method was developed in data pre-processing to display tree features in the shadows. For the model structure, the original CSPDarkNet-53 backbone feature extraction network was replaced by MobileNetV3. Some of the standard convolutional blocks in the original extraction network were replaced by depthwise separable convolution blocks. The new ReLU6 activation function replaced the original LeakyReLU activation function to make the network more robust for low-precision computations. The K-means++ clustering method was also integrated to generate anchor boxes that are more suitable for the dataset. The experimental results show that the improved algorithm achieved an accuracy of 97.33%, higher than other methods. The detection speed of the proposed approach is higher than that of YOLOv4, improving the efficiency and accuracy of the detection process.