• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.323-328
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• 2019

In order to construct 3D geospatial information about the terrain, current measurement using a total station, remote sensing, GNSS(Global Navigation Satellite System) have been used. However, ground survey and GNSS survey have time and economic disadvantages because they have to be surveyed directly in the field. In case of using aerial photographs and satellite images, these methods have the disadvantage that it is difficult to obtain the three-dimensional shape of the terrain. The terrestrial LiDAR can acquire 3D information of X, Y, Z coordinate and shape obtained by scanning innumerable laser pulses at densely spaced intervals on the surface of the object to be observed at high density, and the processing can also be automated. In this study, terrestrial LiDAR was used to analyze slope displacement. Study area slopes were selected and data were acquired using LiDAR in 2016 and 2017. Data processing has been used to generate slope cross section and slope data, and the overlay analysis of the generated data identifies slope displacements within 0.1 m and suggests the possibility of using slope LiDAR on land to manage slopes. If periodic data acquisition and analysis is performed in the future, the method using the terrestrial lidar will contribute to effective risk slope management.

• Journal of Ocean Engineering and Technology
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• v.31 no.5
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• pp.325-334
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• 2017

This paper reports the conceptual design process for a floating metocean data measurement system (FMDMS) for measuring wind information at sea. The FMDMS consists of three circular pontoons, columns, and a deck, which the LiDAR (lighting detection and ranging) is installed on. The dynamics of the mooring lines and motion responses of the FMDMS were analyzed using commercial codes such as WAMIT and OrcaFlex. One design criterion of the developed FMDMS was to maintain the motion responses as small as possible to enhance the LiDAR's accuracy. Starting with the preliminary design parameters such as the FMDMS's principal dimensions, weight, and important parameters of mooring system, we checked whether the FMDMS met the design requirements at each design stage, and then made modifications as necessary. The developed FMDMS showed a large pitch behavior for a small heave motion.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.3
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• pp.107-111
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• 2021

A 3D point cloud map is an essential elements in various fields, including precise autonomous navigation system. However, generating a 3D point cloud map using a single sensor has limitations due to the price of expensive sensor. In order to solve this problem, we propose a precise 3D mapping system using low-cost sensor fusion. Generating a point cloud map requires the process of estimating the current position and attitude, and describing the surrounding environment. In this paper, we utilized a commercial visual-inertial odometry sensor to estimate the current position and attitude states. Based on the state value, the 2D LiDAR measurement values describe the surrounding environment to create a point cloud map. To analyze the performance of the proposed algorithm, we compared the performance of the proposed algorithm and the 3D LiDAR-based SLAM (simultaneous localization and mapping) algorithm. As a result, it was confirmed that a precise 3D point cloud map can be generated with the low-cost sensor fusion system proposed in this paper.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.27-29
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• 2007

The visual implementation of 3-dimensional national environment is focused by the requirement and importance in the fields such as, national development plan, telecommunication facility deployment plan, railway construction, construction engineering, spatial city development, safety and disaster prevention engineering. The currently used DEM system using contour lines, which embodies national geographic information based on the 2-D digital maps and facility information has limitation in implementation in reproducing the 3-D spatial city. Moreover, this method often neglects the altitude of the rail way infrastructure which has narrow width and long length. There it is needed to apply laser measurement technique in the spatial target object to obtain accuracy. Currently, the LiDAR data which combines the laser measurement skill and GPS has been introduced to obtain high resolution accuracy in the altitude measurement. In this paper, we first investigate the LiDAR based researches in advanced foreign countries, then we propose data a generation scheme and an algorithm for the optimal manage and synthesis of railway facility system in our 3-D spatial terrain information. For this object, LiDAR based height data transformed to DEM, and the realtime unification of the vector via digital image mapping and raster via exactness evaluation is transformed to make it possible to trace the model of generated 3-dimensional railway model with long distance for 3D tract model generation.

• Spatial Information Research
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• v.16 no.3
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• pp.279-290
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• 2008

Landslide, one of the serious natural disasters, has Incurred a large loss of human and material resources. Recently, many forecasting or alarm systems based on various kinds of measuring equipment have been developed to reduce the damage of landslide. However, only a few of these equipments are guaranteed to evaluate the safety of whole side of land slope with their accessibility to the slope. In this study, we performed some experiments to evaluate the applicability of a terrestrial LiDAR as a surveying tool to measure the displacement of a land slope surface far a slope collapsing protection system. In the experiments, we had applied a slope stability method to a land slope and then forced to this slope with a load increasing step by step. In each step, we measured the slope surface with both a total station and a terrestrial LiDAR simultaneously. As the result of Slope Fracturing analysis using all targets, the LiDAR system showed that three was 1cm RMSE on X-axis, irregularity errors on Y-axis and few errors on Z-axis compare with Total Station. As the result of Slope Fracturing analysis using continuous targets, the pattern of Slope Fracturing was different according to the location of continuous targets and we could detect a continuous change which couldn't be found using Total station. The accuracy of the LiDAR data was evaluated to be comparable to that of the total station data. We found that a LiDAR system was appropriate to measuring the behaviour of land slope. The LiDAR data can cover the whole surface of the land slope, whereas the total station data are available on a small number of targets. Moreover, we extracted more detail information about the behavior of land slope such as the volume and profile changes using the LiDAR data.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.97-103
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• 2011

LiDAR system has become a popular tool for generating 3D surface data such as Digital Surface Model. Extraction of valuable information, such as digital building models, from LiDAR data has been an attractive research subject. This research addresses to extract planar patches from LiDAR data. Planar patches are important primitives consisting of man-made objects such as buildings. In order to determine the best fitted planes, this research proposed a method to reduce/eliminate the impact of the outliers and the intersection areas of two planes. After finishing plane fitting, planar patches are segmented by pseudo color values which are calculated by determined three plane parameters for each LiDAR point. In addition, a segmentation procedure is conducted using the pseudo color values to find planar patches. This paper evaluates the feasibility of the proposed method using both airborne and terrestrial LiDAR data.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.157-163
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• 2019

The LiDAR sensor, which is widely regarded as one of the most important sensors, has recently undergone active commercialization owing to the significant growth in the production of ADAS and autonomous vehicle components. The LiDAR sensor technology involves radiating a laser beam at a particular angle and acquiring a three-dimensional image by measuring the lapsed time of the laser beam that has returned after being reflected. The LiDAR sensor has been incorporated and utilized in various devices such as drones and robots. This study focuses on object detection and recognition by employing sensor fusion. Object detection and recognition can be executed as a single function by incorporating sensors capable of recognition, such as image sensors, optical sensors, and propagation sensors. However, a single sensor has limitations with respect to object detection and recognition, and such limitations can be overcome by employing multiple sensors. In this paper, the performance of an eight-channel scanning LiDAR was evaluated and an object detection algorithm based on it was implemented. Furthermore, object detection characteristics during daytime and nighttime in a real road environment were verified. Obtained experimental results corroborate that an excellent detection performance of 92.87% can be achieved.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.123-128
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• 2021

This paper present box feature estimation from LiDAR point cluster using maximum likelihood Method. Previous LiDAR tracking method for autonomous driving shows high accuracy about velocity and heading of point cluster. However, Assuming the average position of a point cluster as the vehicle position has a lower accuracy than ground truth. Therefore, the box feature estimation algorithm to improve position accuracy of autonomous driving perception consists of two procedures. Firstly, proposed algorithm calculates vehicle candidate position based on relative position of point cluster. Secondly, to reflect the features of the point cluster in estimation, the likelihood of the particle scattered around the candidate position is used. The proposed estimation method has been implemented in robot operating system (ROS) environment, and investigated via simulation and actual vehicle test. The test result show that proposed cluster position estimation enhances perception and path planning performance in autonomous driving.

• Journal of Sensor Science and Technology
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• v.33 no.4
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• pp.187-195
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• 2024

Light detection and ranging (LiDAR), a widely used sensor in mobile robots and autonomous vehicles, has its most important function as measuring the range of objects in three-dimensional space and generating point clouds. These point clouds consist of the coordinates of each reflection point and can be used for various tasks, such as obstacle detection and environment recognition. However, several processing steps are required, such as three-dimensional modeling, mesh generation, and rendering. Efficient data processing is crucial because LiDAR provides a large number of real-time measurements with high sampling frequencies. Despite the rapid development of controller computational power, simplifying the computational algorithm is still necessary. This paper presents a method for estimating the presence of curbs, humps, and ground tilt using range measurements from a single horizontal or vertical scan instead of point clouds. These features can be obtained by data segmentation based on linearization. The effectiveness of the proposed algorithm was verified by experiments in various environments.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.104-115
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• 2014

A levee is defined as an man-made structure protecting the areas from temporary flooding. This paper suggests a methodology for establishing the levee GIS database using the airborne topographic LiDAR(Light Detection and Ranging) data taken in the Nakdong river basins and the WAMIS(WAter Management Information System) information. First, the National Levee Database(NLD) established by the USACE(United States Army Corps Engineers) and the levee information tables established by the WAMIS are compared and analyzed. For extracting the levee information from the LiDAR data, the DSM(Digital Surface Model) is generated from the LiDAR point clouds by using the interpolation method. Then, the slope map is generated by calculating the maximum rates of elevation difference between each pixel of the DSM and its neighboring pixels. The slope classification method is employed to extract the levee component polygons such as the levee crown polygons and the levee slope polygons from the slope map. Then, the levee information database is established by integrating the attributes extracted from the identified levee crown and slope polygons with the information provided by the WAMIS. Finally, this paper discusses the advantages and limitations of the levee GIS database established by only using the LiDAR data and suggests a future work for improving the quality of the database.