• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1291-1302
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• 2020

To verify the field-effectiveness of Terrestrial Laser Scanner (TLS), a terrestrial LiDAR was deployed to examine the damage properties of woods in forest fire area, then the data was compared with the results surveyed by a forestry expert. Four sample plots (30 m × 50 m, 0.15 ha) were set from the foot to the top of the mountain, and DBH, height, clear length, burned height, and crown length were investigated. Next, TLS collected information on damage characteristics found in the sample plots. This information was then compared with that amassed by the expert. The expert and the TLS survey results showed 30.8 cm and 29.9 cm for DBH, 15.8 m and 17.5 m for tree height, 8.4 m and 8.4 m for clear length, 4.0 m, 3.5 m for burned height, and 7.4 cm and 9.1 cm for crown length. With the exceptions of height and clear length, no notable discrepancy was observed between two methods. H/D ratio, CL/H ratio, and BH/CL ratio, all of which contribute to stability and decay rate of the stand, from the two methods were also compared. The human survey rated each ratio (H/D, CL/H, BH/CL in order) 51.3%, 47.1%, and 53.6%, while the TLS presented the results of 58.8%, 52.0%, and 38.7%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.311-318
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• 2009

Interactive terrain visualization is an important research area with applications in GIS, games, virtual reality, scientific visualization and flight simulators, besides having military use. This is a complex and challenging problem considering that some applications require precise visualizations of huge data sets at real-time rates. In general, the size of data sets makes rendering at real-time difficult since the terrain data cannot fit entirely in memory. In this paper, we suggest the effective Real-time LOD(level-of-detail) algorithm for displaying the huge terrain data and processing mass geometry. We used a hierarchy structure with $4{\times}4$ and $2{\times}2$ tiles for real-time rendering of mass volume DEM which acquired from Digital map, LiDAR, DTM and DSM. Moreover, texture mapping is performed to visualize realistically while displaying height data of normalized Giga Byte level with user oriented terrain information and creating hill shade map using height data to hierarchy tile structure of file type. Large volume of terrain data was transformed to LOD data for real time visualization. This paper show the new LOD algorithm for seamless visualization, high quality, minimize the data loss and maximize the frame speed.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.1-14
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• 2024

An image-reconstruction technology, involving the deployment of an unmanned mobility equipped with high-speed LiDAR (Light Detection And Ranging) has been proposed to reconstruct the shape of abandoned mine. Unmanned mobility operation is remarkably useful in abandoned mines fraught with operational difficulties including, but not limited to, obstacles, sludge, underwater and narrow tunnel with the diameter of 1.5 m or more. For cases of real abandoned mines, quadruped robots, quadcopter drones and underwater drones are respectively deployed on land, air, and water-filled sites. In addition to the advantage of scanning the abandoned mines with 2D solid-state lidar sensors, rotation of radiation at an inclination angle offers an increased efficiency for simultaneous reconstruction of mineshaft shapes and detecting obstacles. Sensor and robot posture were used for computing rotation matrices that helped compute geographical coordinates of the solid-state lidar data. Next, the quadruped robot scanned the actual site to reconstruct tunnel shape. Lastly, the optimal elements necessary to increase utility in actual fields were found and proposed.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.848-849
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• 2023

본 논문은 로봇의 실내 환경에서의 자율성을 높이기 위한 SLAM과 내비게이션 방법을 제시한다. 2D LiDAR와 카메라를 이용하여 위치를 인식하고 사람과 장애물을 의미론적으로 검출하며, ICP와 RTAB-map, YOLOv3를 통합하여 Semantic Map을 생성하고 실내 환경에서 자율성을 유지한다. 이 연구를 통해 로봇이 복잡한 환경에서도 높은 수준의 자율성을 유지할 수 있는지 확인하고자 한다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.459-469
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• 2011

There are various factors for determining object shape, such as size, slope and its direction, curvature, length, surface, angles between lines or planes, distribution of the model key points, and so on. Most of the object description and recognition methods are for the 2D space not for the 3D object space where the objects actually exist. In this study, 3D chain code operator, which is basically extension of 2D chain code, was proposed for object description and analysis in 3D space. Results show that the sequence of the 3D chain codes could be basis of a top-down approach for object recognition and modeling. In addition, the proposed method could be applicable to segment point cloud data such as LiDAR data.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.149-158
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• 2024

This paper presents a robust autonomous navigation and reconnaissance system for tracked robots, designed to handle complex multi-floor indoor environments with stairs. We introduce a localization algorithm that adjusts scan matching parameters to robustly estimate positions and create maps in environments with scarce features, such as narrow rooms and staircases. Our system also features a path planning algorithm that calculates distance costs from surrounding obstacles, integrated with a specialized PID controller tuned to the robot's differential kinematics for collision-free navigation in confined spaces. The perception module leverages multi-image fusion and camera-LiDAR fusion to accurately detect and map the 3D positions of objects around the robot in real time. Through practical tests in real settings, we have verified that our system performs reliably. Based on this reliability, we expect that our research team's autonomous reconnaissance system will be practically utilized in actual disaster situations and environments that are difficult for humans to access, thereby making a significant contribution.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.242-242
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• 2022

실제 자연하천은 하천의 만곡, 사행 정도와 교각 및 암거와 같은 구조물로 인하여 발생하는 복잡한 흐름현상이 빈번하게 발생하며, 이를 반영하기 위해서는 2차원 흐름해석 모형의 적용이 필요하다. 이러한 필요성이 있음에도 현재 하천흐름해석 분야 실무에서 사용되는 모형은 1차원 모형이 주를 이루고 있으며, 그 이유는 현재 제공되고 있는 하천 단면 자료와의 높은 적용성 때문이라고 할 수 있다. 현행 제공되고 있는 하천 단면 자료는 인력 위주의 측량 자료로서 하천 연장의 일정구간 간격으로 단면 자료를 제공하고 있기 때문에 2차원 흐름해석 모형에 적용하기 위해서는 보간 작업이 필수적이며, 정확성 또한 낮아 적용성이 떨어지는 문제점이 있다. 하지만 최근 드론을 이용한 측량 기술의 발전으로 LiDAR, 초분광을 활용한 양질의 2차원 하천 하상 자료를 산출하기 시작하였으며, 하천흐름해석 분야에서 2차원 흐름해석 모형의 적용성이 높아지고 있다. 본 연구에서는 기존에 적용하기 어려웠던 사행도가 높은 하천에 대하여 드론 측량 자료를 활용한 2차원 흐름해석 모형 결과와 기존의 측량 방식을 적용한 2차원 흐름해석 모형 결과 비교를 통하여 드론 측량 자료를 활용한 2차원 흐름해석 모형의 적용성 평가를 수행하고자 한다.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.136-145
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• 2009

The objective of the Intelligent Excavation System (IES) is to recognize the work environment and produce work plan and automatically control the excavator through integrating sensor and robot technologies. This paper discusses one of the core technologies of IES development project, development of 3D work environment modeling. 3D laser scanner is used for 3-dimensional mathematical model that can be visualized in virtual space in 3D. This paper describes (1) how the most appropriate 3D imaging system has been chosen; (2) the development of user interface and customization of the s/w to control the scanner for IES project; (3) the development of the mobile station for the scanner; (4) and the algorithm for the automatic registration of laser scan segments for IES project. The development system has been tested on the construction field and lessons learned and future development requirements are suggested.

• Journal of the Korean Society of Safety
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• v.33 no.1
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• pp.128-134
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• 2018

With the increase in frequency of typhoons and heavy rains following the climate change, the scale of damage from the calamities in the mountainous areas has been growing larger and larger, which is different from the past. For the case of Korea where 64% of land is consisted of the mountainous areas, establishment of the check dams has been drastically increased after 2000 in order to reduce the damages from the debris flow. However, due to the lack of data on scale, location and kind of check dams established for reducing the damages in debris flow, the measures to prevent damages based on experience and subjective basis have to be relied on. Under this study, the high-precision DEM data was structured by using the terrestrial LiDAR in the Jecheon area where the debris flow damage occurred in July 2009. And, from the numerical models of the debris flow, Kanako-2D that is available to reflect the erosion and deposition action was applied to install the erosion control facilities (water channel, check dam) and analyzed the effect of reducing the debris flow shown in the downstream.After installing the erosion control facilities, most of debris flow moves along the water channel to reduce the area to expand the debris flow, and after installing the check dam, the flow depth and flux of the debris flow were reduced along with the erosion. However, as a result of analyzing the diffusion area, flow depth, erosion and deposition volume of the debris flow generated from the deposition part after modifying the location of the check dams with the damages occurring on private residences and agricultural land located on the upstream area, the highest reduction effect was shown when the check dam is installed in the maximal discharge points.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.