• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.279-287
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• 2007

The increased availability of portable, low-cost, high resolution video equipments have resulted in a rapid growth of the applications for video sequences. These video devices can be mounted in handhold unit, mobile unit and airborne platforms like maned or unmaned helicopter, plane, airship, etc. This paper describes the feasibility fur generating image map from the experimental results we designed to track the interested points extracted by KLT operator in the neighboring frames and implement image matching for each frames taken from UAV (Unmaned Aerial Vehicle). In the image registration for neighbourhood frames of aerial video, the results demonstrate the successful rate of matching slightly decreases as the drift between frames increases, and also that the stable photographing is more important matching condition than the pixel shift.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.355-358
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• 2009

Due to growth of electronics and control devices, automation and situational awareness systems have been applied by automobile. Vision systems with the introduction of unmanned system being actively developed, but are still high price and visual information is passed through the cable, because of cars are difficult to install. In this paper, can be installed inside the car at low-cost, simple image processing device through a wireless communication know the obstacles and the alarm system based on Zigbee wireless communication, infrared and ultrasonic sensors to monitor the situation through with easy parking cars outside the system design was implemented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.211-217
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• 2019

In an complicated battlefield environment, information from enemy's camp is an important factor in carrying out military operations. For obtaining this information, the number of UAVs that can be deployed to the mission without our forces' loss and at low cost is increasing. Because the mission environment has anti-aircraft weapons, mission space is needed for UAV to guarantee survivability without being killed. The concept of Configuration Space is used to define the mission space considering with range of weapons and detect range of UAV. UAV must visit whole given area to obtain the information and perform Coverage Path Planning for this. Based on threats to UAV and importance of information that will be obtained, area that UAV should visit first is defined. Grid Map is generated and mapping threat information to each grid for UAV path planning. On this study, coverage conditions and path planning procedures are presented based on the threat information on Grid Map, and mission space is expanded to improve detection efficiency. Finally, simulations are performed, and results are presented using the suggested UAV path planning method in this study.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.971-980
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• 2021

Recently popularized drone technologies have revealed that low-cost small unmanned aerial vehicles(UAVs) can be a significant threat to prevailing power by operating in group or in swarms. Researchers in many countries have tried to utilize integrated swarm unmanned aerial system(SUAS) in the battlefield. Agency for Defense Development also identified four core technologies in developing SUAS: swarm control, swarm network, swarm information, and swarm collaboration, and the authors started researches on swarm control and network technologies in order to be able to operate vehicle platforms as the first stage. This paper introduces design and integration of SUAS consisting of small fixed-wing UAVs, swarm control and network algorithms, a ground control system, and a launcher, with which swarm control and network technologies have been verified by flight tests. 19 fixed-wing UAVs succeeded in swarm flight in the final flight test for the first time as a domestic research.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.2
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• pp.119-143
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• 2021

Selecting liquid methane as fuel is a prevailing trend for recent rocket engine developments around the world, triggered by its affordability, reusability, storability for deep space exploration, and prospect for in-situ resource utilization. Given years of time required for acquiring a new rocket engine, a national-level R&D program to develop a methane engine is highly desirable at the earliest opportunity in order to catch up with this worldwide trend towards reusing launch vehicles for competitiveness and mission flexibility. In light of the monumental cost associated with development, fabrication, and testing of a booster stage engine, it is strategically a prudent choice to start with a low-thrust engine and build up space application cases.

• Transactions of Materials Processing
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• v.32 no.2
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• pp.81-86
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• 2023

The hot stamping process is widely used for high strength of vehicle parts, with heating 900 ℃ or higher in a furnace and in-die quenching to achieve strength above 1.5 GPa of the quenchable boron alloyed steel 22MnB5. First of all, the hot stamping process consisted of heating, forming, quenching and trimming. In the trimming process case, the laser method has been conventionally adopted. For laser trimming process, it has the problems pertaining to low productivity and high cost while the hot stamping process, accordingly the trimming process need to investigate the research for alternative method. In order to overcome these issues, many research groups have studied the mechanical trim solution on the hot stamped parts at high temperature. In this study, the mechanical piercing was performed during the hot stamping process at the high temperature for overcome the disadvantages of laser cutting. Also, the process parameters such as piercing time after die closing, clearances of between die and punch were controlled for obtaining the reasonable shear characteristics.

• Journal of Environmental Impact Assessment
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• v.27 no.5
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• pp.475-488
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• 2018

Surveying urban tributary vegetation is based mainly on field sampling at present. The tributary vegetation survey integrating UAV NIR(Unmanned Aerial Vehicle Near Infrared Radiance) imagery and in-situ point photo has received only limited attentions from the field ecologist. The reason for this could be the largely undemonstrated applicability of UAV NIR imagery by the field ecologist as a monitoring tool for urban tributary vegetation. The principal advantage of UAV NIR imagery as a remote sensor is to provide, in a cost-effective manner, information required for a very narrow swath target such as urban tributary (10m width or so), utilizing very low altitude flight, real-time geo-referencing and stereo imaging. An exhaustive and realistic comparison of the two techniques was conducted, based on operational customer requirement of urban tributary vegetation survey: synoptic information, ground detail and quantitative data collection. UAV NIR imagery made it possible to identify area-wide patterns of the major plant communities subject to many different influences (e.g. artificial land use pattern), which cannot be acquired by traditional field sampling. Although field survey has already gained worldwide recognition by plant ecologists as a typical method of urban tributary vegetation monitoring, this approach did not provide a level of information that is either scientifically reliable or economically feasible in terms of urban tributary vegetation (e.g. remedial field works). It is anticipated that this research output could be used as a valuable reference for area-wide information obtained by UAV NIR imagery in urban tributary vegetation survey.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.4
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• pp.53-64
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• 2009

Inter-vehicular communication that propagates information without infrastructures has drawn a lot of interest. However, it is difficult to apply conventional ad-hoc routing protocols directly in inter-vehicular communication due to frequent changes in the network topology caused by high mobility of the vehicles. MMFP(Multi-hop MAC Forwarding) is a unicast forwarding protocol that transport packets based on the reachability information instead of path selection or position information. However, delivering public safety messages informing road conditions such as collision, obstacles and fog through inter-vehicular communication requires broadcast rather than unicast since these messages contain information valuable to most drivers within a close proximity. Flooding is one of the simplest methods for multi-hop broadcast, but it suffers from reduced packet delivery-ratio and high transmission delay due to an excessive number of duplicated packets. This paper presents two multi-hop broadcast protocols for inter-vehicular communication that extend the MMFP. UMHB(Unreliable Multi-Hop Broadcast) mitigates the duplicated packets of MMFP by limiting the number of nodes to rebroadcast packets. UMHB, however, still suffers from low delivery ratio. RMHB(Reliable Multi-Hop Broadcast) uses acknowledgement and retransmission in order to improve the reliability of UMHB at the cost of increase in transmission delay, which we show through simulation is within an acceptable range for collision avoidance application.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.23-33
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• 2020

Recently, high-resolution images can be easily acquired using UAV (Unmanned Aerial Vehicle), so that it is possible to produce small area observation and spatial information at low cost. In particular, research on the generation of cover maps in crop production areas is being actively conducted for monitoring the agricultural environment. As a result of comparing classification performance by applying RF(Random Forest), SVM(Support Vector Machine) and CNN(Convolutional Neural Network), deep learning classification method has many advantages in image classification. In particular, land cover classification using satellite images has the advantage of accuracy and time of classification using satellite image data set and pre-trained parameters. However, UAV images have different characteristics such as satellite images and spatial resolution, which makes it difficult to apply them. In order to solve this problem, we conducted a study on the application of deep learning algorithms that can be used for analyzing agricultural lands where UAV data sets and small-scale composite cover exist in Korea. In this study, we applied DeepLab V3 +, FC-DenseNet (Fully Convolutional DenseNets) and FRRN-B (Full-Resolution Residual Networks), the semantic image classification of the state-of-art algorithm, to UAV data set. As a result, DeepLab V3 + and FC-DenseNet have an overall accuracy of 97% and a Kappa coefficient of 0.92, which is higher than the conventional classification. The applicability of the cover classification using UAV images of small areas is shown.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.279-286
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• 2018

In the civil works, the measurement of earth-volume is one of the important elements in the estimation of the reasonable construction cost. Related studies mainly used GPS (Global Positioning System) or total station to obtain information on civil work areas. However, these methods are difficult to implement in inaccessible areas. Therefore, the aim of this paper is to use the UAV (Unmanned Aerial Vehicle) to measure the earth-volume. The study area is located in a reservoir construction site in Sangju-si, Gyeongsangbuk-do, Republic of Korea. We compared the earth-volume amounts acquired by UAV-based surveying to ones acquired by total station-based and GPS-based surveying, respectively. In the site, the amount of earth-volume acquired by GPS was $147,286.79m^3$. The amount of earth-volume acquired by total station was $147,286.79m^3$, which is the 96.13% accuracy compared to the GPS-based surveying. The earth-volume obtained by UAV was $143,997.05m^3$ when measured without GCPs (Ground Control Points), $147,251.71m^3$ with 4 GCPs measurement, and $146,963.81m^3$ with 7 GCPs measurement. Compared to the GPS-based surveying, 97.77%, 99.98%, and 99.78% accuracies were obtained from the UAV-based surveying without GCP, 4 GCPs, and 7 GCPs, respectively. Therefore, it can be confirmed that the UAV-based surveying can be used for the earth-volume measurement.