• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.83-86
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• 2020

본 논문에서는 해군의 향후 군사용 드론 활용 가능방안을 제안한다. AI, 자율주행 등의 4차 산업혁명 기술들과 함께 상용분야에서는 이미 다양한 드론 활용방안들이 제시되고 있으며, 육군은 이에 발맞춰 2018년 10월 드론봇 전투단을 창설하여 운용 중에 있다. 하지만 아직 해군의 군사용 드론 운용 및 활용방안 등에 관한 연구는 미진하며, 따라서 현재 해군의 군용 드론 활용현황을 살펴보고 객체인식, 자율주행 등의 최신기술과 상용활용 사례 등을 군에 접목시켜 앞으로의 활용 가능방안에 대해서 제안하고자 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1294-1299
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• 2018

'SMART Police' means collecting, analyzing and utilizing the police database such as crime statistics, reflecting 'strategic management', 'analysis and research', 'science technology' do. In recent years, the number of sex offenses has more than doubled based on the 'crime analysis' of the Supreme Prosecutors' In this trend, we started to build a sex crime prevention program for women 's relief special 3.0 which is suitable for regional characteristics. However, it was not enough for the women to have low publicity and utilization results, and to show the practical effect. In the future, we propose a crime prevention system which can safely take home safeguarding with autonomous driving car or drone by applying ICT to the future police system. Although it is difficult to operate autonomous vehicles and drones in the surrounding environment such as narrow alleys and power lines for application to this system, it is thought that the artificial intelligence technology can be sufficiently overcome to operate.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.931-941
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• 2020

There is a growing interest this paper for ocean sensing where autonomous vehicles can play an essential role in assisting engineers, researchers, and scientists with environmental monitoring and collecting oceanographic data. This study was conducted to develop a rigid sail for the autonomous sailing drone. Our study aims to numerically analyze the aerodynamic characteristics of curvy twin sail and compare it with wing sail. Because racing regulations limit the sail shape, only the two-dimensional geometry (2D) was open for an optimization. Therefore, the first objective was to identify the aerodynamic performance of such curvy twin sails. The secondary objective was to estimate the effect of the sail's spacing and shapes. A viscous Navier-Stokes flow solver was used for the numerical aerodynamic analysis. The 2D aerodynamic investigation is a preliminary evaluation. The results indicated that the curvy twin sail designs have improved lift, drag, and driving force coefficient compared to the wing sails. The spacing between the port and starboard sails of curvy twin sail was an important parameter. The spacing is 0.035 L, 0.07 L, and 0.14 L shows the lift coefficient reduction because of dramatically stall effect, while flow separation is improved with spacing is 0.21 L, 0.28 L, and 0.35 L. Significantly, the spacing 0.28 L shows the maximum high pressure at the lower area and the small low pressure area at leading edges. Therefore, the highest lift was generated.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1007-1021
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• 2022

Autonomous driving of unmanned aerial vehicles may have to pay expensive cost to create and switch new routes if unexpected obstacles exist or local map updates occured by the control system due to incorrect route information. Integrating digital twins into the path-following process requires more computing resources to quickly switch the wrong path to an alternative path, but it can quickly update the path during flight. In this study, we design a DEVS-based simulation environment which can modify optimized paths through short-term simulation of multi-virtual UAVs for applying digital twin concepts to path follow. Through simulation, we confirmed the possibility of increasing the mission stability of UAV.

• Journal of Information Technology Services
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• v.22 no.2
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• pp.57-70
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• 2023

In order to establish an autonomous driving environment, it is necessary to study traffic safety and demand prediction by analyzing information generated from the transportation infrastructure beyond relying on sensors by the vehicle itself. In this paper, we propose a real-time traffic information generation method using sensor convergence technology of transportation infrastructure. The proposed method uses sensors such as cameras and radars installed in the transportation infrastructure to generate information such as crosswalk pedestrian presence or absence, crosswalk pause judgment, distance to stop line, queue, head distance, and car distance according to each characteristic. create information An experiment was conducted by comparing the proposed method with the drone measurement result by establishing a demonstration environment. As a result of the experiment, it was confirmed that it was possible to recognize pedestrians at crosswalks and the judgment of a pause in front of a crosswalk, and most data such as distance to the stop line and queues showed more than 95% accuracy, so it was judged to be usable.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.375-383
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• 2021

Due to COVID-19, people are building new lifestyles such as online shopping, online travel, and video conferencing by limiting going out and gatherings. Such rapid social change is causing new problems and deepening existing problems at the same time. In particular, as online consumption increases significantly, traffic congestion, air pollution, and the heavy workload of delivery drivers are deepening in the daily logistics industry, and face-to-face delivery is emerging as a new problem. With the advent of the 4th industrial revolution, unmanned delivery using drones, artificial intelligence, and autonomous driving is emerging as an alternative to the existing logistics industry. However, space for logistics facilities and securing additional logistics sites due to drone flight are emerging as new problems to be solved. Therefore, it is intended to link additional services such as logistics movement, storage, and delivery by utilizing the existing transportation business, the subway, as a space for a logistics facility for drones that can solve existing problems and new problems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.224-226
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• 2016

With the technical development and rapid increase of private demand, the new market for unmanned vehicle combined with the characteristics of 'unmanned automation' and 'vehicle' is rapidly growing. Even though the pilot driving is currently allowed in some countries, there is no country that has institutionalized the formal driving of self-driving cars. In case of the existing vehicles, safety incidents are frequently happening due to the frequent malfunction of the rear sensor, blind spot of the rear camera, or drivers' carelessness. Once such minor flaws are complemented, the relevant regulations for the commercialization of self-driving car and small drone could be relieved. Contrary to the ultrasonic and laser sensors used for the existing vehicles, this paper aims to attempt the distance measurement by using the depth sensor. A depth camera calculates the distance data based on the TOF method calculating the time difference by lighting laser or infrared light onto an object or area and then receiving the beam coming back. As this camera can obtain the depth data in the pixel unit of CCD camera, it can be used for collecting depth data in real-time. This paper suggests to solve problems mentioned above by using depth data in real-time and also to design the obstacle avoidance system through distance measurement.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.2
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• pp.89-96
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• 2019

360 degree 3-dimensional lidar sensors and vision cameras are commonly used in the development of autonomous driving techniques for automobile, drone, etc. By the way, existing calibration techniques for obtaining th e external transformation of the lidar and the camera sensors have disadvantages in that special calibration objects are used or the object size is too large. In this paper, we introduce a simple calibration method between two sensors using a spherical object. We calculated the sphere center coordinates using four 3-D points selected by RANSAC of the range data of the sphere. The 2-dimensional coordinates of the object center in the camera image are also detected to calibrate the two sensors. Even when the range data is acquired from various angles, the image of the spherical object always maintains a circular shape. The proposed method results in about 2 pixel reprojection error, and the performance of the proposed technique is analyzed by comparing with the existing methods.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.67-77
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• 2021

Spatial data is becoming very important as a medium that connects various data produced in smart cities, digital twins, autonomous driving, smart construction, and other applications. In addition, the rapid construction and update of spatial information is becoming a hot topic to satisfy the diverse needs of consumers in this field. This study developed a software prototype that can match the position of an image-based 3D building model produced without Ground Control Points using existing spatial data. As a result of applying this software to the test area, the 3D building model produced based on the image and the existing spatial data show a high positional matching rate, so that it can be widely used in applications requiring the latest 3D spatial data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.