• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.436-443
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• 2011

Recognition of structures in urban environments is a fundamental ability for unmanned ground vehicles. In this paper we propose the geometrical featured voxel which has not only 3-D coordinates but also the type of geometrical properties of point cloud. Instead of dealing with a huge amount of point cloud collected by range sensors in urban, the proposed voxel can efficiently represent and save 3-D urban structures without loss of geometrical properties. We also provide an urban structure classification algorithm by using the proposed voxel and machine learning techniques. The proposed method enables to recognize urban environments around unmanned ground vehicles quickly. In order to evaluate an ability of the proposed map representation and the urban structure classification algorithm, our vehicle equipped with the sensor system collected range data and pose data in campus and experimental results have been shown in this paper.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.43-53
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• 2007

In this study, two standard specifications such as GML (Geography Markup Language) from OGC (Open Geo-spatial Consortium, Inc.) and X3D (extensible 3D) from Web3D consortium were dealt with for a web-based 3D urban application without using commercialized tools. In the first step of this study, DEM (Digital Elevation Model) and 3D GIS data sets were converted to GML structure with attribute schema. Then, these GML elements were projected onto a common coordinate system, and they were converted to the X3D format for visualization on web browser. In this work, a 3D urban data model, as a simple framework model, is extended to a framework model having further detailed information, depending upon application levels. Conclusively, this study is to demonstrate for practical uses of GML and X3D in 3D urban application and this approach can be applied to other application domains regarding system integrators and data sharing communities on distributed environments.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.744-746
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• 2003

A 3D modeling of urban area can be composed the terrain modeling that can express specific and shape of the terrain and the object modeling such as buildings, trees and facilities which are found in urban areas. Especially in a 3D modeling of building, it is very important to make a unit model by simplifying 3D structure and to take a texture mapping, which can help visualize surface information. In this study, the texture mapping technique, based on library for 3D urban modeling, was used for building modeling. This technique applies the texture map in the form of library which is constructed as building types, and then take mapping to the 3D building frame. For effectively apply, this technique, we classified buildings automatically using LiDAR data and made 3D frame using LiDAR and digital map. To express the realistic building texture, we made the texture library using real building photograph.

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.115-126
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• 2016

This paper suggests the method of the spherical signature description of 3D point clouds taken from the laser range scanner on the ground vehicle. Based on the spherical signature description of each point, the extractor of significant environmental features is learned by the Deep Belief Nets for the urban structure classification. Arbitrary point among the 3D point cloud can represents its signature in its sky surface by using several neighborhood points. The unit spherical surface centered on that point can be considered to accumulate the evidence of each angular tessellation. According to a kind of point area such as wall, ground, tree, car, and so on, the results of spherical signature description look so different each other. These data can be applied into the Deep Belief Nets, which is one of the Deep Neural Networks, for learning the environmental feature extractor. With this learned feature extractor, 3D points can be classified due to its urban structures well. Experimental results prove that the proposed method based on the spherical signature description and the Deep Belief Nets is suitable for the mobile robots in terms of the classification accuracy.

• Earthquakes and Structures
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• v.16 no.1
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• pp.97-107
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• 2019

The frame structures investigated in this paper is composed of Concrete encased columns with L-shaped steel section and steel beams. The seismic behavior of this structural system is studied through experimental and numerical studies. A 2-bay, 3-story and 1/3 scaled frame specimen is tested under constant axial loading and cyclic lateral loading applied on the column top. The load-displacement hysteretic loops, ductility, energy dissipation, stiffness and strength degradation are investigated. A typical failure mode is observed in the test, and the experimental results show that this type of framed structure exhibit a high strength with good ductility and energy dissipation capacity. Furthermore, finite element analysis software Perform-3D was conducted to simulate the behavior of the frame. The calculating results agreed with the test ones well. Further analysis is conducted to investigate the effects of parameters including concrete strength, column axial compressive force and steel ratio on the seismic performance indexes, such as the elastic stiffness, the maximum strength, the ductility coefficient, the strength and stiffness degradation, and the equivalent viscous damping ratio. It can be concluded that with the axial compression ratio increasing, the load carrying capacity and ductility decreased. The load carrying capacity and ductility increased when increasing the steel ratio. Increasing the concrete grade can improve the ultimate bearing capacity of the structure, but the ductility of structure decreases slightly.

• Proceedings of the KSRS Conference
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• v.1
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• pp.409-412
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• 2006

Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Recognizing this potential use of high resolution satellite imagery, KARI is performing a project for developing Korea multipurpose satellite 3(KOMPSAT-3). Therefore, it is necessary to develop techniques for various GIS applications of KOMPSAT-3, using similar high resolution satellite imagery. As fundamental studies for this purpose, we focused on the extraction of 3D spatial information and the update of existing GIS data from QuickBird imagery. This paper examines the scheme for rectification of high resolution image, and suggests the convenient semi-automatic algorithm for extraction of 3D building information from a single image. The algorithm is based on triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and enhance the digitizing accuracy and the computation efficiency.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.268-274
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• 2007

Traditional two-dimensional (2D) interpretation of magnetotelluric (MT) data utilizes only transverse magnetic (TM)-mode data, because 2D inversion of transverse electric (TE)-mode data results in spurious features when 3D structures exist in the subsurface. The application of a 3D inversion algorithm to a single MT profile can reduce contamination due to off-profile anomalies and help us to incorporate TE-mode data in the interpretation. In this study, we conduct 2D and 3D inversions of MT data observed along two lines in Jeju Island. First, we invert apparent resistivities and phases in the TM and TE modes separately. Then, we perform 2D joint inversion of both TM- and TE-mode data and 3D inversion of both Zxy- and Zyx-mode data corresponding to TE- and TM-mode data in 2D. The resistivity images derived from all four data show that the geoelectrical structure in Jeju Island is a three-layered earth with the resistive-conductive-resistive stratigraphy within a depth of 5 km. The 3D inversion does not produce clear anomalies in the reconstructed profile image, while all of 2D do. This attributed to the possibility that 2D inversion results are distorted by exiting off-profile 3D anomalies in Jeju. With 3D inversion of 2D profile MT data, we can deduce more reliable results that are not seriously distorted by off-profile 3D anomalies.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.71-76
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• 2006

With the rapid development of spatial infrastructure in US, Europe, Japan, China and India, there is no doubt that the next generation Global Navigation Satellite System (GNSS) will improve the integrity, accuracy, reliability and availability of the position solution. GNSS is becoming an essential element of personal, commercial and public infrastructure and consequently part of our daily lives. However, the applicability of GPS in supporting a range of location-sensitive applications such as location based services in an urban environment is severely curtailed by the interference of the 3D urban settings. To characterize and gain in-depth understanding of such interferences and to be able to provide location-based optimization alternatives, a high-fidelity 3D urban model of Melbourne CBD built with ArcGIS and large scale high-resolution spatial data sets is used in this study to support a comprehensive simulation of current and future GNSS signal performance, in terms of signal continuity, availability, strength, geometry, positioning accuracy and reliability based on a number of scenarios. The design, structure and major components of the simulator are outlined. Useful time-stamped spatial patterns of the signal performance over the experimental urban area have been revealed which are valuable for supporting location based services applications, such as emergency responses, the optimization of wireless communication infrastructures and vehicle navigation services.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.66-71
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• 2003

This study investigates the spatial patterns of distributed population in terms of population density, age structure, sex structure and family structure in Chou (smallest political city boundaries) of seven cities of Kitakawachi region. This displays the population dynamics of those cities from 1955 to 1995. It demonstrates how the populations of the cities are distributed with topography and with respect to the train stations. The demographic characteristics of the cities are visualized utilizing Arc View GIS capabilities with new visualizing technique in 3D environment based on data from Pasco Digital Map 2000.

• Journal of Urban Science
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• v.6 no.2
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• pp.17-27
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• 2017

Recently, civil complaints have increased due to water pollution and bad smell in rivers. Therefore, attention is focused on improving the river environment. The purpose of this study is to acquire RGB and thermal infrared images using UAV for sewage outlet and to monitor the status of stream pollution and the applicability UAV based images for river embankment maintenance plan was examined. The accuracy of the 3D model was examination by SfM(Structure from Motion) based images analysis on river embankment maintenance area. Especially, The wastewater discharged from the factory near the river was detected as an thermal infrared images and the flow of wastewater was monitored. As a result of the study, we could monitor the cause and flows of wastewater pollution by detecting temperature change caused by wastewater inflow using UAV images. In addition, UAV based a high precision 3D model (DTM, Digital Topographic Map, Orthophoto Mosaic) was produced to obtain precise DSM(Digital Surface Model) and vegetation cover information for river embankment maintenance.