• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1245-1248
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• 2004

This paper presents a new technique to analyze data on the coordinate x, y, z and apply these data to design the motion control to improve the efficiency of the engraving machine so that it can engrave accordingly in 3 dimensions. First, the tool path on the x-y plane is analyzed to be synchronized with the z-axis. The digital data is then sent to the motion control to guide the movement of the engrave point on the x-y plane. Tool path moves along the x-axis with zero degree and different values of the y-axis according to the coordinate of the digital data and the analysis along z-axis to determine the depth for engraving. The depth can be specified from the gray level with the 256 levels of resolution. The data obtained includes the distances on x-axis, y-axis, and z-axis, the acceleration of the engrave point's movement, and the speed of the engrave point's movement. These data is then transfered to the motion control to guide the movement of the engrave point along the z-axis associated with the x-y plane. The results indicate that engraving using this technique is fast and continuous. The specimen obtained looks perfect in 3D view.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.739-740
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• 2008

Method for 3D reconstruction from image points and geometric clues can be roughly classified as "model-based" and "constraint-based". We present a new method to reconstruct from one image a scene using depth-point. The our method is benchmarked synthetic data and its effectiveness is shown on photograph data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.99-100
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• 2011

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.481-487
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• 2023

Recently, interest in UAM (Urban Air Mobility) has surged as a critical solution to urban traffic congestion and air pollution issues. However, efficient UAM operation requires accurate 3D Point Cloud data processing, particularly in separating the ground and objects. This paper proposes and validates a method for effectively separating ground and objects in a UAM environment, taking into account its dynamic and complex characteristics. Our approach combines attitude information from MEMS sensors with ground plane estimation using RANSAC, allowing for ground/object separation that isless affected by GPS errors. Simulation results demonstrate that this method effectively operates in UAM settings, marking a significant step toward enhancing safety and efficiency in urban air mobility. Future research will focus on improving the accuracy of this algorithm, evaluating its performance in various UAM scenarios, and proceeding with actual drone tests.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.229-240
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• 2019

3D geo-spatial model have been widely used in the field of Civil Engineering, Medical, Computer Graphics, Urban Management and many other. Especially, the demand for high quality 3D spatial information such as precise road map construction has explosively increased, MMS and UAV techniques have been actively used to acquire them more easily and conveniently in surveying and geo-spatial field. However, in order to perform 3D modeling by integrating the two data set from MMS and UAV, its so needed an proper registration method is required to efficiently correct the difference between the raw data acquisition sensor, the point cloud data generation method, and the observation accuracy occurred when the two techniques are applied. In this study, we obtained UAV point colud data in Yeouido area as the study area in order to determine the automatic registration performance between MMS and UAV point cloud data using ICP(Iterative Closet Point) method. MMS observations was then performed in the study area by dividing 4 zones according to the level of overlap ratio and observation noise with based on UAV data. After we manually registered the MMS data to the UAV data, then compared the results which automatic registered using ICP method. In conclusion, the higher the overlap ratio and the lower the noise level, can bring the more accurate results in the automatic registration using ICP method.

• Journal of KIBIM
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• v.10 no.4
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• pp.32-39
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• 2020

In recent years, the construction industry is getting bigger and more complex, so it is becoming difficult to acquire point cloud data for construction equipments and workers. Point cloud data is measured using a drone and MMS(Mobile Mapping System), and the collected point cloud data is used to create a 3D digital map. In particular, the construction site is located at outdoors and there are many irregular terrains, making it difficult to collect point cloud data. For these reasons, adopting a noise reduction algorithm suitable for the characteristics of the construction industry can affect the improvement of the analysis accuracy of digital maps. This is related to various environments and variables of the construction site. Therefore, this study reviewed and analyzed the existing research and techniques on the noise reduction algorithm. And based on the results of literature review, performance evaluation of major noise reduction algorithms was conducted for digital maps of construction sites. As a result of the performance evaluation in this study, the voxel grid algorithm showed relatively less execution time than the statistical outlier removal algorithm. In addition, analysis results in slope, space, and earth walls of the construction site digital map showed that the voxel grid algorithm was relatively superior to the statistical outlier removal algorithm and that the noise removal performance of voxel grid algorithm was superior and the object preservation ability was also superior. In the future, based on the results reviewed through the performance evaluation of the noise reduction algorithm of this study, we will develop a noise reduction algorithm for 3D point cloud data that reflects the characteristics of the construction site.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.923-929
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• 2008

Due to the increasing need for 3D spatial data, modeling of topography and artificial structures plays an important role in three-dimensional Urban Analysis. This study suggests a methodology for solving the problem of calculation for the extraction of building boundary, minimizing the user's intervention, and automatically extracting building boundary, using the LIDAR data. The methodology suggested in this study is characterized by combining the merits of the point-based process and the image-based process. The procedures for extracting building boundary are three steps: 1) LIDAR point data are interpolated to extract approximately building region. 2) LIDAR point data are triangulated in each individual building area. 3) Extracted boundary of each building is then simplified in consideration of its area, minimum length of building.The performance of the developed methodology is evaluated using real LIDAR data. Through the experiment, the extracted building boundaries are compared with digital map.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.663-666
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• 2008

For a fill dam, when a long time has passed since its completion, it is very hard to judge its safety and to maintain effectively it due to limitation and restriction in data showing safety status. Conventional method based on a specific point data by surface settlement gauge is commonly used to define deformation characteristic of dam. However, point data-based deformation analysis cannot provide deformation data of the entire dam. In this study a state-of-the-art terrestrial laser scanning technology is introduced to analyze the entire deformation of dam. As a result, it is known that 3D scanning technique can also be effectively used in evaluating dam safety and then establishing adequate maintain plan.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.157-159
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• 2019

Hologram technology has been actively developed in terms of generation, transmission, and reproduction of 3D objects, but it is currently in a state of rest because of various limitations. Beyond VR and AR, the pseudo-hologram market is growing at an intermediate stage to meet the needs of new technologies. The key to the technology of hologram is to generate vast 3 dimensional data in the form of a point cloud, transmit the vast amount of data through the communication network in real time, and reproduce it like the original at the destination. In this paper, we propose a method to transmit massive 3 - D data in real - time and transmit the minutiae points of 3 - dimensional object information to reproduce the object as similar to original.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3
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• pp.452-458
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• 2013

Over the past several years, many studies have been carried out in the field of 3D data inspection systems. Several attempts have been made to improve the quality of manufactured parts. The introduction of laser sensors for inspection has made it possible to acquire data at a remarkably high speed. In this paper, a robust inspection technique for detecting defects in 3D pressed parts using laser-scanned data is proposed. Point cloud data are segmented for the extraction of features. These segmented features are used for shape matching during the localization process. An iterative closest point (ICP) algorithm is used for the localization of the scanned model and CAD model. To achieve a higher accuracy rate, the ICP algorithm is modified and then used for matching. To enhance the speed of the matching process, aKd-tree algorithm is used. Then, the deviation of the scanned points from the CAD model is computed.