• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.189-198
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• 2021

In this paper, we introduce the software/hardware system that can reliably calculate the distance from sensor to the model regardless of point cloud density. As the 3d point cloud map is widely adopted for SLAM and computer vision, the accuracy of point cloud map is of great importance. However, the 3D point cloud map obtained from Lidar may reveal different point cloud density depending on the choice of sensor, measurement distance and the object shape. Currently, when measuring map accuracy, high reflective bands are used to generate specific points in point cloud map where distances are measured manually. This manual process is time and labor consuming being highly affected by Lidar sparsity level. To overcome these problems, this paper presents a hardware design that leverage high intensity point from three planar surface. Furthermore, by calculating distance from sensor to the device, we verified that the automated method is much faster than the manual procedure and robust to sparsity by testing with RGB-D camera and Lidar. As will be shown, the system performance is not limited to indoor environment by progressing the experiment using Lidar sensor at outdoor environment.

• Smart Structures and Systems
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• v.30 no.5
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• pp.501-511
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• 2022

Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.123-130
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• 2018

Triangulation is one of the fundamental problems in computational geometry and computer graphics community, and it has huge application areas such as 3D printing, computer-aided engineering, surface reconstruction, surface visualization, and so on. The Delaunay refinement algorithm is a well-known method to generate quality triangular meshes when point cloud and/or constrained edges are given in two- or three-dimensional space. In this paper, we propose a simple but efficient algorithm to triangulate Voronoi surfaces of Voronoi diagram of spheres in 3-dimensional Euclidean space. The proposed algorithm is based on the Ruppert's Delaunay refinement algorithm, and we modified the algorithm to be applied to the triangulation of Voronoi surfaces in two ways. First, a new method to deciding the location of a newly added vertex on the surface in 3-dimensional space is proposed. Second, a new efficient but effective way of estimating approximation error between Voronoi surface and triangulation. Because the proposed algorithm generates a triangular mesh for Voronoi surfaces with guaranteed quality, users can control the level of quality of the resulting triangulation that their application problems require. We have implemented and tested the proposed algorithm for random non-intersecting spheres, and the experimental result shows the proposed algorithm produces quality triangulations on Voronoi surfaces satisfying the quality criterion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.16-22
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• 2019

Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1951-1972
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• 2018

Wi-Fi Access Point (AP) optimization approaches are used in indoor positioning systems for signal coverage enhancement, as well as positioning precision improvement. Although the huge power consumption of the AP optimization forms a serious problem due to the signal coverage requirement for large-scale indoor environment, the conventional approaches treat the problem of power consumption independent from the design of indoor positioning systems. This paper proposes a new Fast Water-filling algorithm Group Power Constraint (FWA-GPC) based Wi-Fi AP optimization approach for indoor positioning in which the power consumed by the AP optimization is significantly considered. This paper has three contributions. First, it is not restricted to conventional concept of one AP for one candidate AP location, but considered spare APs once the active APs break off. Second, it utilizes the concept of water-filling model from adaptive channel power allocation to calculate the number of APs for each candidate AP location by maximizing the location fingerprint discrimination. Third, it uses a fast version, namely Fast Water-filling algorithm, to search for the optimal solution efficiently. The experimental results conducted in two typical indoor Wi-Fi environments prove that the proposed FWA-GPC performs better than the conventional AP optimization approaches.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.765-774
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• 2019

In this paper, we propose a point cloud matching algorithm for multiple RGB-D cameras. In general, computer vision is concerned with the problem of precisely estimating camera position. Existing 3D model generation methods require a large number of cameras or expensive 3D cameras. In addition, the conventional method of obtaining the camera external parameters through the two-dimensional image has a large estimation error. In this paper, we propose a method to obtain coordinate transformation parameters with an error within a valid range by using depth image and function optimization method to generate omni-directional three-dimensional model using 8 low-cost RGB-D cameras.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.12
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• pp.1883-1890
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• 2013

Location detection technology (LDT) is one of the core techniques for location based service (LBS) in wireless communication for improving resource management and quality of services. The location of a mobile station (MS) is estimated using the time of arrival (TOA) technique based on three circles with centers corresponding to coordinates of three base stations (BSs) and radius corresponding to distances between MS and BSs. For accurately estimating the location of MS, three circles should meet at a point for the trilateration method, but they generally do not meet a point because the radius is increased depending on the number of time delay for estimating the distance between MS and BS and the carrier frequency. The increased three circles intersect at six points and the three intersection points among them should be generally placed close to coordinate of the location for the specific MS. In this paper, we propose the shortest distance algorithm for TOA trilateration method, to select three interior intersection points from entire six points. The proposed approach selects three intersection points with the shortest distances between coordinates of MS and intersection points and determines the averaged coordinate of the selected three points, as the location of the specific MS. We demonstrate the performance of the proposed algorithm using a typical computer simulation example.

• Industrial Engineering and Management Systems
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• v.3 no.2
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• pp.123-128
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• 2004

A tree structure model has been proposed for representing the unequal-area facility layout. Each facility has a different rectangular shape specified by its area and aspect ratio. In this layout problem, based on the assumption that the shop floor has enough space for laying out the facilities, no constraint is considered for a shop floor. Objectives are minimizing total part movement between facilities and total rectangular layout area where all facilities and dead spaces are enclosed. Using the genetic code corresponding to two kinds of information, facility sequence and branching positions in the tree structure model, a genetic algorithm has been applied for finding non-dominated solutions in the two-objective layout problem. We use three kinds of crossover (PMX, OX, CX) for the former part of the chromosome and one-point crossover for the latter part. Two kinds of layout problems have been tested by the proposed method. The results demonstrate that the presented algorithm is able to find good solutions in enough short time.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.1
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• pp.36-50
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• 1989

The purpose of this study is to design effective working systems which adapt to changes in human needs by developing an algorithm which forms workers into optimal groups using the meausre of cohesion. Three major results can be derived from the study. Firstly, the algorithm developed here provides an optimal point at which to stop clustering. Secondely, the entropic measure of cohesion having an internal probabilistic structure is superior with respect to any other methods proposed before as far as the design of workgroup is concerned. Thirdly, the r $C_{n}$ clustering algorithm is better than the dichotonomic one.e.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2414-2433
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• 2019

The aim of this paper is to design a 3D laser radar prototype based on laser triangulation. The mathematical model of distance sensitivity is deduced; a pixel-distance conversion formula is discussed and used to complete 3D scanning. The center position extraction algorithm of the spot is proposed, and the error of the linear laser, camera distortion and installation are corrected by using the proposed weighted average algorithm. Finally, the three-dimensional analytic computational algorithm is given to transform the measured distance into point cloud data. The experimental results show that this 3D laser radar can accomplish the 3D object scanning and the environment 3D reconstruction task. In addition, the experiment result proves that the product of the camera focal length and the baseline length is the key factor to influence measurement accuracy.