• Title/Summary/Keyword: automated tracking algorithm

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A Tracking Algorithm for Autonomous Navigation of AGVs: Federated Information Filter

  • Kim, Yong-Shik;Hong, Keum-Shik
    • Journal of Navigation and Port Research
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    • v.28 no.7
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    • pp.635-640
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    • 2004
  • In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) operating in container terminals is presented. The developed navigation algorithm takes the form of a federated information filter used to detect other AGVs and avoid obstacles using fused information from multiple sensors. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. It is proved that the information state and the information matrix of the suggested filter, which are weighted in terms of an information sharing factor, are equal to those of a centralized information filter under the regular conditions. Numerical examples using Monte Carlo simulation are provided to compare the centralized information filter and the proposed one.

Automated Cell Counting Method for HeLa Cells Image based on Cell Membrane Extraction and Back-tracking Algorithm (세포막 추출과 역추적 알고리즘 기반의 HeLa 세포 이미지 자동 셀 카운팅 기법)

  • Kyoung, Minyoung;Park, Jeong-Hoh;Kim, Myoung gu;Shin, Sang-Mo;Yi, Hyunbean
    • Journal of KIISE
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    • v.42 no.10
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    • pp.1239-1246
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    • 2015
  • Cell counting is extensively used to analyze cell growth in biomedical research, and as a result automated cell counting methods have been developed to provide a more convenient and means to analyze cell growth. However, there are still many challenges to improving the accuracy of the cell counting for cells that proliferate abnormally, divide rapidly, and cluster easily, such as cancer cells. In this paper, we present an automated cell counting method for HeLa cells, which are used as reference for cancer research. We recognize and classify the morphological conditions of the cells by using a cell segmentation algorithm based on cell membrane extraction, and we then apply a cell back-tracking algorithm to improve the cell counting accuracy in cell clusters that have indistinct cell boundary lines. The experimental results indicate that our proposed segmentation method can identify each of the cells more accurately when compared to existing methods and, consequently, can improve the cell counting accuracy.

Climatic Features of Extratropical Cyclones During the Spring-time Yellow Dust Events in Korea (한반도 봄철 황사 발생시 동아시아 온대저기압의 기후학적 특징)

  • Lee, Jaeyeon;Kim, Junsu;Son, Seok-Woo
    • Atmosphere
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    • v.26 no.4
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    • pp.565-576
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    • 2016
  • The yellow dust events in Korea are often associated with extratropical cyclones (ETCs) that travel across the source regions of yellow dusts. Although such synoptic patterns are well documented, climatic features of ETCs themselves during the yellow dust events are not well understood. The present study reports climatic features of spring-time ETCs, which accompany the yellow dust events in Korea, by tracking individual ETCs with an automated tracking algorithm. By analyzing Lagrangian tracks of ETCs from 1979 to 2014, it is found that, during yellow dust events, ETCs are located around Vladivostok, Russia. They are typically originated from the leeside of Altai-Sayan mountains about three days before the onset of the yellow dust events, and travel either eastward or southeastward in time. While their tracks are not unusual, they grow faster over the source regions of the yellow dusts, possibly lifting desert dusts above the planetary boundary layer, and further develop slowly as they travel eastward.

TRACKING LIFT-PATHS OF A ROBOTIC TOWERCRANE WITH ENCODER SENSORS

  • Suyeul Park;Ghang, Lee;Joonbeom cho;Sungil Hham;Ahram Han;Taekwan Lee
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.250-256
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    • 2009
  • This paper presents a robotic tower-crane system using encoder and gyroscope sensors as path tracking devices. Tower crane work is often associated with falling accidents and industrial disasters. Such problems often incur a loss of time and money for the contractor. For this reason, many studies have been done on an automatic tower crane. As a part of 5-year 23-million-dollar research project in Korea, we are developing a robotic tower crane which aims to improve the safety level and productivity. We selected a luffing tower crane, which is commonly used in urban construction projects today, as a platform for the robotic tower crane system. This system comprises two modules: the automated path planning module and the path tracking module. The automated path planning system uses the 3D Cartesian coordinates. When the robotic tower crane lifts construction material, the algorithm creates a line, which represents a lifting path, in virtual space. This algorithm seeks and generates the best route to lift construction material while avoiding known obstacles from real construction site. The path tracking system detects the location of a lifted material in terms of the 3D coordinate values using various types of sensors including adopts encoder and gyroscope sensors. We are testing various sensors as a candidate for the path tracking device. This specific study focuses on how to employ encoder and gyroscope sensors in the robotic crane These sensors measure a movement and rotary motion of the robotic tower crane. Finally, the movement of the robotic tower crane is displayed in a virtual space that synthesizes the data from two modules: the automatically planned path and the tracked paths. We are currently field-testing the feasibility of the proposed system using an actual tower crane. In the next step, the robotic tower crane will be applied to actual construction sites with a following analysis of the crane's productivity in order to ascertain its economic efficiency.

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Cluster Cell Separation Algorithm for Automated Cell Tracking (자동 세포 추적을 위한 클러스터 세포 분리 알고리즘)

  • Cho, Mi Gyung;Shim, Jaesool
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.37 no.3
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    • pp.259-266
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    • 2013
  • An automated cell tracking system is used to automatically analyze and track the changes in cell behavior in time-lapse cell images acquired using a microscope with a cell culture. Clustering is the partial overlapping of neighboring cells in the process of cell change. Separating clusters into individual cells is very important for cell tracking. In this study, we proposed an algorithm for separating clusters by using ellipse fitting based on a direct least square method. We extracted the contours of clusters, divided them into line segments, and then produced their fitted ellipses using a direct least square method for each line segment. All of the fitted ellipses could be used to separate their corresponding clusters. In experiments, our algorithm separated clusters with average precisions of 91% for two overlapping cells, 84% for three overlapping cells, and about 73% for four overlapping cells.

Adaptive Tracking Algorithm Based on Direction Field for Automated Identification of Vessel Contour (혈관 윤곽의 자동적 식별을 위한 방향성 기반의 적응적 추적 알고리즘)

  • Park, S.I.;Lee, J.S.;Koo, J.Y.;Hong, S.H.
    • Proceedings of the KOSOMBE Conference
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    • v.1997 no.05
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    • pp.414-417
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    • 1997
  • This paper presents vessel contour for extracting features and segmentating narrow blood vessels down to a diameter of two pixels in digital subtraction angiographic image. We present a new tracking algorithm for contour, mainly blood vessels in DSA image, and extracting properties such as their intensities, diameters, and center lines by exploiting spatial continuity. The proposed algorithm comes to detect blood vessel's boundary using difference edge detector one of homogeneity operator and find a next centerline position by direction vector of edge information. This algorithm enhanced variation of vessel's diameter compared to Sun's tracking algorithm and lessoned to compute as direction vector decide adaptively entire vessel's direction field. The processed images are intended to support radiologists in diagnosis, radiation therapy planning, and surgical planning. The algorithm should be useful for automating angiographic analyses of blood vessels.

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AVM Stop-line Detection based Longitudinal Position Correction Algorithm for Automated Driving on Urban Roads (AVM 정지선인지기반 도심환경 종방향 측위보정 알고리즘)

  • Kim, Jongho;Lee, Hyunsung;Yoo, Jinsoo;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.12 no.2
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    • pp.33-39
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    • 2020
  • This paper presents an Around View Monitoring (AVM) stop-line detection based longitudinal position correction algorithm for automated driving on urban roads. Poor positioning accuracy of low-cost GPS has many problems for precise path tracking. Therefore, this study aims to improve the longitudinal positioning accuracy of low-cost GPS. The algorithm has three main processes. The first process is a stop-line detection. In this process, the stop-line is detected using Hough Transform from the AVM camera. The second process is a map matching. In the map matching process, to find the corrected vehicle position, the detected line is matched to the stop-line of the HD map using the Iterative Closest Point (ICP) method. Third, longitudinal position of low-cost GPS is updated using a corrected vehicle position with Kalman Filter. The proposed algorithm is implemented in the Robot Operating System (ROS) environment and verified on the actual urban road driving data. Compared to low-cost GPS only, Test results show the longitudinal localization performance was improved.

Domain decomposition for GPU-Based continuous energy Monte Carlo power reactor calculation

  • Choi, Namjae;Joo, Han Gyu
    • Nuclear Engineering and Technology
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    • v.52 no.11
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    • pp.2667-2677
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    • 2020
  • A domain decomposition (DD) scheme for GPU-based Monte Carlo (MC) calculation which is essential for whole-core depletion is introduced within the framework of the modified history-based tracking algorithm. Since GPU-offloaded MC calculations suffer from limited memory capacity, employing DDMC is inevitable for the simulation of depleted cores which require large storage to save hundreds of newly generated isotopes. First, an automated domain decomposition algorithm named wheel clustering is devised such that each subdomain contains nearly the same number of fuel assemblies. Second, an innerouter iteration algorithm allowing overlapped computation and communication is introduced which enables boundary neutron transactions during the tracking of interior neutrons. Third, a bank update scheme which is to include the boundary sources in a way to be adequate to the peculiar data structures of the GPU-based neutron tracking algorithm is presented. The verification and demonstration of the DDMC method are done for 3D full-core problems: APR1400 fresh core and a mock-up depleted core. It is confirmed that the DDMC method performs comparably with the standard MC method, and that the domain decomposition scheme is essential to carry out full 3D MC depletion calculations with limited GPU memory capacities.

Application of the Laser Vision Sensor for Corrugated Type Workpiece

  • Lee, Ji-Hyoung;Kim, Jae-Gwon;Kim, Jeom-Gu;Park, In-Wan;Kim, Hyung-Shik
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.499-503
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    • 2004
  • This application-oriented paper describes an automated welding carriage system to weld a thin corrugated workpiece with welding seam tracking function. Hyundai Heavy Industries Corporation has developed an automatic welding carriage system, which utilizes pulsed plasma arc welding process for corrugated sheets. It can obtain high speed welding more than 2 times faster than traditional TIG based welding system. The aim of this development is to increase the productivity by using automatic plasma welding carriage systems, to track weld seam line using vision sensor automatically, and finally to provide a convenience to operator in order to carry out welding. In this paper a robust image processing and a distance based tracking algorithms are introduced for corrugated workpiece welding. The automatic welding carriage system is controlled by the programmable logic controller(PLC), and the automatic welding seam tracking system is controlled by the industrial personal computer(IPC) equipped with embedded OS. The system was tested at actual workpiece to show the feasibility and performance of proposed algorithm and to confirm the reliability of developed controller.

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A Study on Tracking and Quantitative Analysis of Regional Left Ventricular Wall Motion in Echocardiography (심초음파에서 국소 좌심실벽 운동 추적 및 정량적 분석에 관한 연구)

  • 신동규;김동윤;최경훈;박광훈
    • Progress in Medical Physics
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    • v.10 no.3
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    • pp.115-123
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    • 1999
  • The two dimensional echocardiography is widely used to evaluate regional wall motion abnormality, because of its abilities to depict left ventricular wall motion. A number of researches have been processed for evaluation and quantitative analysis of left ventricular wall motion functions. In this paper, we proposed an algorithm which detects automatically and analyze quantitatively endocardial wall motion during systole. The echocardiograms were obtained in the short-axis views in normal subjects. Automated edge detection and endocardial contour tracking algorithm was applied to each frames, quantitative analysis based on segmentation was performed, pre-defined color overlays superimposed on the gray scale images, and the images was animated. The proposed algorithm provided automated, quantitative diagnosis of regional wall motion abnormality.

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