• 제목/요약/키워드: Three-Point Algorithm

검색결과 538건 처리시간 0.023초

라이다 점군 밀도에 강인한 맵 오차 측정 기구 설계 및 알고리즘 (Map Error Measuring Mechanism Design and Algorithm Robust to Lidar Sparsity)

  • 정상우;정민우;김아영
    • 로봇학회논문지
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    • 제16권3호
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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.

Deep learning approach to generate 3D civil infrastructure models using drone images

  • Kwon, Ji-Hye;Khudoyarov, Shekhroz;Kim, Namgyu;Heo, Jun-Haeng
    • Smart Structures and Systems
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    • 제30권5호
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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.

딜러니 개선 알고리듬을 이용한 삼차원 구의 보로노이 곡면 삼각화 (Triangulation of Voronoi Faces of Sphere Voronoi Diagram using Delaunay Refinement Algorithm)

  • 김동욱
    • 산업경영시스템학회지
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    • 제41권4호
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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.

오프라인 프로그래밍을 위한 3차원 레이저 스캐닝 시스템 기반의 로봇 캘리브레이션 방법 개발 (Development of robot calibration method based on 3D laser scanning system for Off-Line Programming)

  • 김현수
    • 한국산학기술학회논문지
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    • 제20권3호
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    • pp.16-22
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    • 2019
  • 로봇을 적용한 자동화 생산 라인에서 로봇 셋업 시 시뮬레이션을 통한 Off-Line Programming(OLP)과 로봇 캘리브레이션은 작업 시간을 단축하고 양산 전부터 생산 품질을 관리하기 위해 필수적이다. 본 연구에서는 상용 3D 스캐너를 사용하여 생산 라인의 CAD 데이터와 현장의 3차원 측정 스캔 데이터를 정합하는 로봇 캘리브레이션 방법을 개발하였다. 제안한 방법은 Iterative Closest Point(ICP) 알고리즘을 통해 두 개의 3차원 점군 데이터를 정합하여 로봇을 교정한다. 정합은 3단계로 수행한다. 먼저 CAD 데이터로부터 3개의 평면으로 연결된 꼭짓점을 특징점으로 추출한다. 추출한 특징점 주변에 위치한 스캔 점군데이터로부터 평면을 재구성하여 대응하는 특징점을 생성한다. 마지막으로 ICP 알고리즘을 통해 추출한 특징점들 간의 거리를 최소화하여 위치 변환 행렬을 계산한다. 자동차 차체 조립라인의 스팟용접 로봇 설치에 제안한 방법을 적용한 결과 스팟용접에서 일반적으로 요구하는 정밀도 1.5mm 수준으로 로봇의 위치 및 자세를 캘리브레이션 할 수 있었으며, 기존에 레이저 트래커를 사용하면 로봇 한 대당 5시간 이상 소요되던 셋업 시간은 40분 이내로 단축할 수 있었다. 개발한 시스템을 사용하면 차체 스팟 용접에 필요한 정밀도를 유지하면서 자동차 차체 조립 라인의 OLP 작업시간을 단축하여, 로봇 정밀 티칭 시간을 단축하여, 생산제품의 품질 향상 및 불량률을 최소화할 수 있다.

Group Power Constraint Based Wi-Fi Access Point Optimization for Indoor Positioning

  • Pu, Qiaolin;Zhou, Mu;Zhang, Fawen;Tian, Zengshan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권5호
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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.

체적형 객체 촬영을 위한 RGB-D 카메라 기반의 포인트 클라우드 정합 알고리즘 (Point Cloud Registration Algorithm Based on RGB-D Camera for Shooting Volumetric Objects)

  • 김경진;박병서;김동욱;서영호
    • 방송공학회논문지
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    • 제24권5호
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    • pp.765-774
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    • 2019
  • 본 논문에서는 다중 RGB-D 카메라의 포인트 클라우드 정합 알고리즘을 제안한다. 일반적으로 컴퓨터 비전 분야에서는 카메라의 위치를 정밀하게 추정하는 문제에 많은 관심을 두고 있다. 기존의 3D 모델 생성 방식들은 많은 카메라 대수나 고가의 3D Camera를 필요로 한다. 또한 2차원 이미지를 통해 카메라 외부 파라미터를 얻는 기존의 방식은 큰 오차를 가지고 있다. 본 논문에서는 저가의 RGB-D 카메라 8대를 사용하여 전방위 3차원 모델을 생성하기 위해 깊이 이미지와 함수 최적화 방식을 이용하여 유효한 범위 내의 오차를 갖는 좌표 변환 파라미터를 구하는 방식을 제안한다.

모바일 위치추정을 위한 TOA 최단거리 알고리즘 (A TOA Shortest Distance Algorithm for Estimating Mobile Location)

  • 프라드한 사지나;황석승
    • 한국전자통신학회논문지
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    • 제8권12호
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    • pp.1883-1890
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    • 2013
  • 위치 추정 기술 (LDT, Location Detection Technology)은 자원관리 및 통신 서비스의 품질을 향상시키기 위한 무선통신 분야에서 사용되고 있는 LBS(Location Based Service)의 핵심기술 중 하나이다. 이동국(MS, mobile station)의 위치는 세 개의 기지국(BS, base station)들의 좌표와 이동국과 기지국들 사이의 거리에 상응하는 반지름에 기초한 세 개의 원들에 기반한 도래시간(TOA, Time of Arrival)기법을 사용하여 추정된다. 삼각변 측량법을 이용하여 정확한 이동국의 위치를 추정하기 위해서는 세 개의 원들이 한 점에서 만나야 하는데, 이동국과 기지국의 거리를 추정하기 위한 시간지연 개수와 전송 주파수에 따라 원들의 반지름이 증가하여 세 개의 원들이 한 점에서 만나지 못하는 경우들이 발생한다. 반지름이 증가된 세 개의 원들은 여섯 개의 교점을 가지게 되고 이 교점들 중 세 개의 교점들이 특정 이동국의 좌표에 가까이 위치하게 된다. 본 논문에서는 여섯 개의 전체 교점들 중에서 세 개의 내부 교점들을 선택하는 TOA 삼각변 측량법을 위한 최단 거리 알고리즘을 제안한다. 제안된 방법은 여섯 개의 교점들 중 이동국의 좌표와 가장 가까운 세 개의 교점을 선택하고, 선택된 교점들의 평균 좌표를 특정 이동국의 위치로 결정한다. 제안된 알고리즘의 성능은 컴퓨터 시뮬레이션 예를 통해 확인된다.

Tree Structure Modeling and Genetic Algorithm-based Approach to Unequal-area Facility Layout Problem

  • Honiden, Terushige
    • Industrial Engineering and Management Systems
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    • 제3권2호
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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.

앤트로피 응집력척도를 활용한 군락화기법개발에 관한 연구 (A Study on the Development of Clustering Algorithm Using the Entropic Measure of Cohesion)

  • 정현태;최인수
    • 한국경영과학회지
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    • 제14권1호
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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.

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Design of 3D Laser Radar Based on Laser Triangulation

  • Yang, Yang;Zhang, Yuchen;Wang, Yuehai;Liu, Danian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권5호
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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.