• 한국지형공간정보학회:학술대회논문집
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• 2004.10a
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• pp.123-128
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• 2004

최근 디지털 카메라(Digital camera), 다중/고분광 영상(Mumltispectral/Hyperspectral image), LiDAR(Light Detection and Ranging), InSAR(Interferometric SAR)와 같이 지상을 보다 상세하고 높은 정확도로 지상을 매핑할 수 있는 센서들이 출현하고 있다. 이러한 다양한 정보 취득 자료를 충분히 활용하여 통합하기 위해서는 영상에 대하여 정확한 기하보정 또는 정사영상의 제작과 LiDAR 자료와 같은 경우 평면위치의 오차를 조정하여 다중자료들 간의 정확한 지형보정(Coregistration)이 필요하다. 본 연구에서는 AIR-MS 자료를 이용하여 즉, 항공기로부터 취득한 LiDAR(Height와 강도(Intensity) 자료), digital camera을 통합하고, 기존의 컬러항공사진 및 1:1000 수치지도를 이용하여 3D GIS 자료의 생성을 시도하였다.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.559-567
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• 2022

The optimal shipping location is determined by measuring the volume and weights of cargo shipped to non-standard cargo carriers. Currently, workers manually measure cargo volume, but automate it to improve work inefficiency. In this paper, we proposed the method of a real-time volume calculation using LiDar sensor for automating cargo measurement of non-standard cargo. For this purpose, we utilized the statistical techniques for data preprocessing and volume calculation, also used Voxel Grid filter to light weighted of data which are appropriate in real-time calculation. We implemented the function of Normal vectors and Triangle Mesh to generate surfaces and Alpha Shapes algorithms to process 3D modeling.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.3
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• pp.480-488
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• 2019

In this paper, we propose an obstacle avoidance system for an unmanned ship to navigate safely in dynamic environments. Also, in this paper, one-dimensional low-cost lidar sensor is used, and a servo motor is used to implement the lidar sensor in a two-dimensional space. The distance and direction of an obstacle are measured through the two-dimensional lidar sensor. The unmanned ship is controlled by the application at a Tablet PC. The user inputs the coordinates of the destination in Google maps. Then the position of the unmanned ship is compared with the position of the destination through GPS and a geomagnetic sensor. If the unmanned ship finds obstacles while moving to its destination, it avoids obstacles through a fuzzy control-based algorithm. The paper shows that the experimental results can effectively construct an obstacle avoidance system for an unmanned ship with a low-cost LiDAR sensor using fuzzy control.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.111-112
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• 2022

모든 도시가 발전하고 번창하기 위해서는 핵심기반시설의 재난 및 안전이 선제적으로 확보되어야 한다. 본 논문에서는 환경핵심기반시설을 중심으로 지역사회가 지속 가능한 녹색도시로 거듭나기 위해 재난준비태세 증진에 실제 활용 가능한 위험지도를 드론에 장착한 LiDAR 센서를 통해 수집한 고도 데이터를 바탕으로 제작하였다. 나아가 지진과 같은 재난 발생 시 시설에서부터 확산하는 관리 오염물의 경로 및 범위를 시범 모의하여, 기능 연속성 계획 및 재난대응 가이드와 연계를 하는 방안을 제시함으로 지자체 중심의 통합적 지역사회의 노력이 발현될 수 있도록 기초적 연구를 진행하고, 전략적 활성화 방안을 제시하였다. 본 연구는 끊임없는 성장과 거듭되는 개발로 인해 변화하는 도시의 형상에 따라 리스크를 최신화하여 대응력을 높이고, 이해관계자들에게 시각화된 재난 범위 모의를 제시함으로써 지역사회와 지자체 역량에 따른 협력적 재난대응태세에 필요한 프레임워크 도출 및 계획수립을 가능하게 한다는 점에서 큰 의의를 지닌다. 또한, 각 영역별 전문가들의 자문을 통하여 본 논문에서 제시된 확산 모의의 방법론이 타당함을 확인하였다. 무엇보다 모호한 "가능한 신속한 자원관리"와 같은 추상적인 대응계획이 아닌, 객관적인 재난자원관리계획을 수립할 수 있게 함으로써 추후 국가적 재난 및 안전역량을 계량화시킬 수 있을 것으로 사료된다.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.2 s.40
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• pp.59-66
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• 2007

The digital working environment and its related technology have been rapidly expanding. In the surveying field, we have changed from using optical film cameras and plotters to digital cameras, multi sensors like GPS/INS etc,. The old analog work flow is replaced by a new digital work flow. Accurate data of the land is used in various fields, efficient utilization and management of land, urban planning, disaster and environment management. It is important because it is an essential infrastructure. For this study, LiDAR surveying was used to get points clouds in the study area. It has a high vegetation penetrating advantage and we used a digital process from planning to the final products. Contour lines were made from LiDAR data and compared with national digital base maps (scale 1/1,000 and 1/5,000). As a result, the accuracy and the economical efficiency were evaluated. The accuracy of LiDAR contour data was average $0.089m{\pm}0.062\;m$ and showed high ground detail in complex areas. Compared with 1/1,000 scale contour line production when surveying an area over $100\;km^2$, approximately 48% of the cost was reduced. Therefore we prepose LiDAR surveying as an alternative to modify and update national base maps.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.101-103
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• 2022

CCTV is mainly used as a real-time detection system for critical facilities. In the case of CCTV, although the accuracy is high, the viewing angle is narrow, so it is used in combination with a sensor such as a radar. LiDAR is a technology that acquires distance information by detecting the time it takes to reflect off an object using a high-power pulsed laser. In the case of lidar, there is a problem in that the utilization is not high in terms of cost and technology due to the limitation of the number of simultaneous processing sensors in the server due to the data throughput. The detection method by the optical mesh sensor is also vulnerable to strong winds and extreme cold, and there is a problem of maintenance due to damage to animals. In this paper, by using the 1550nm wavelength band instead of the 905nm wavelength band used in the existing lidar sensor, the effect on the weather environment is strong and we propose to develop a system that can integrate and control multiple sensors.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.865-870
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• 2023

Recently, accidents caused by black ice, a road freezing phenomenon caused by natural power, are increasing. Black ice is difficult to identify directly with the human eye and is more likely to misunderstand it as standing water, so there is a high accident rate caused by car sliding. To solve this problem, this paper presents a method of detecting black ice centered on LiDAR sensors. With a small, inexpensive, and high-accuracy light detection and ranging (LiDAR) sensor, the temperature and inclination angle are set differently to detect black ice and asphalt by setting different reflection angles of asphalt and black ice differently in temperatures and inclinations. The LIDARO carried out in the study points out that additional research and improvement are needed to increase accuracy, and through this, more reliable black ice detection methods can be suggested. This method suggests a method of detecting black ice through early system design research by preventing accidents caused by black ice in advance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.661-664
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• 2023

이 프로젝트의 목표는 공유 공간에서의 고객 이용 시간 관리를 향상하기 위해 라즈베리 파이와 센서 기술을 활용한 자동 시간 체크 시스템의 개발입니다. 이 시스템은 로드셀, 진동 감지 센서, 그리고 LiDAR 센서, 이 세 가지 센서를 활용해 의자에서 사용자의 존재 여부를 감지하고, 사람과 물건을 구별하며, 사용자가 의자에서 일어나는 시점을 파악합니다. 특히, 고객이 의자에 앉게 되면 시스템이 자동으로 시간을 체크하여 실시간으로 이용 시간을 측정하게 됩니다. 이렇게 수집된 정보는 웹 기반의 사용자 인터페이스를 통해 제공되어, 이용 시간 관리가 보다 편리해집니다.

• Journal of Aerospace System Engineering
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• v.15 no.1
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• pp.102-110
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• 2021

Recently, multi-copters equipped with various collision avoidance sensors have been introduced to improve flight stability. LiDAR is used to recognize a three-dimensional position. Multiple cameras and real-time SLAM technology are also used to calculate the relative position to obstacles. A three-dimensional depth sensor with a small process and camera is also used. In this study, a small collision-avoidance multi-copter system capable of in-door flight was developed as a platform for the development of collision avoidance software technology. The multi-copter system was equipped with LiDAR, 3D depth sensor, and small image processing board. Object recognition and collision avoidance functions based on the YOLO algorithm were verified through flight tests. This paper deals with recent trends in drone collision avoidance technology, system design/manufacturing process, and flight test results.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.329-332
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• 2023

3D Object Detection using deep neural network has been developed a lot for obstacle detection in autonomous vehicles because it can recognize not only the class of target object but also the distance from the object. But in the case of 3D Object Detection models, the detection performance for distant objects is lower than that for nearby objects, which is a critical issue for autonomous vehicles. In this paper, we introduce a technique that increases the performance of 3D object detection models, particularly in recognizing distant objects, by generating virtual 3D vehicle data and adding it to the dataset used for model training. We used a spherical point tracing method that leverages the characteristics of 3D LiDAR sensor data to create virtual vehicles that closely resemble real ones, and we demonstrated the validity of the virtual data by using it to improve recognition performance for objects at all distances in model training.