• Title/Summary/Keyword: locating

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Packet-Reduced Ranging Method with Superresolution TOA Estimation Algorithm for Chirp-Based RTLS

  • Oh, Daegun;Go, Seungryeol;Chong, Jong-Wha
    • ETRI Journal
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    • v.35 no.3
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    • pp.361-370
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    • 2013
  • In this paper, a packet-reduced ranging method using a superresolution time of arrival estimation algorithm for a chirp-based real-time locating system is presented. A variety of ranging methods, such as symmetric double-sided two-way ranging (SDS-TWR), have been proposed to remove the time drift due to the frequency offset using extra ranging packets. Our proposed method can perform robust ranging against the frequency offset using only two ranging packets while maintaining almost the same ranging accuracy as them. To verify the effectiveness of our proposed algorithm, the error performance of our proposed ranging method is analyzed and compared with others. The total ranging performance of TWR, SDS-TWR, and our proposed TWR are analyzed and verified through simulations in additive white Gaussian noise and multipath channels in the presence of the frequency offset.

Vision-Based Roadway Sign Recognition

  • Jiang, Gang-Yi;Park, Tae-Young;Hong, Suk-Kyo
    • Transactions on Control, Automation and Systems Engineering
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    • v.2 no.1
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    • pp.47-55
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    • 2000
  • In this paper, a vision-based roadway detection algorithm for an automated vehicle control system, based on roadway sign information on roads, is proposed. First, in order to detect roadway signs, the color scene image is enhanced under hue-invariance. Fuzzy logic is employed to simplify the enhanced color image into a binary image and the binary image is morphologically filtered. Then, an effective algorithm of locating signs based on binary rank order transform (BROT) is utilized to extract signs from the image. This algorithm performs better than those previously presented. Finally, the inner shapes of roadway signs with curving roadway direction information are recognized by neural networks. Experimental results show that the new detection algorithm is simple and robust, and performs well on real sign detection. The results also show that the neural networks used can exactly recognize the inner shapes of signs even for very noisy shapes.

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Development of a Novel 3-DOF Hybrid Robot with Enlarged Workspace (확장 작업업영역을 갖는 고속 3자유도 하이브리드 로봇 개발)

  • Jeong, Sung Hun;Kim, Giseong;Gwak, Gyeong Min;Kim, Han Sung
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.5
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    • pp.875-880
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    • 2020
  • In this paper, a novel 3-DOF hybrid robot with enlarged workspace is presented for high speed applications. The 3-DOF hybrid robot is made up of one linear actuator and 2-DOF planar parallel robot in series. The actuation consists of one ball-screw to make one linear motion and two rotary ball-screws to transmit rotational motion to 2-DOF parallel robot. The workspace can be enlarged according to ball-screw stroke and the moving inertia can be reduced due to locating all the heavy actuators at the fixed base. The inverse kinematics and workspace analyses are presented. The robot prototype and PC-based control system are developed.

Utilizing Soft Computing Techniques in Global Approximate Optimization (전역근사최적화를 위한 소프트컴퓨팅기술의 활용)

  • 이종수;장민성;김승진;김도영
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2000.04b
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    • pp.449-457
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    • 2000
  • The paper describes the study of global approximate optimization utilizing soft computing techniques such as genetic algorithms (GA's), neural networks (NN's), and fuzzy inference systems(FIS). GA's provide the increasing probability of locating a global optimum over the entire design space associated with multimodality and nonlinearity. NN's can be used as a tool for function approximations, a rapid reanalysis model for subsequent use in design optimization. FIS facilitates to handle the quantitative design information under the case where the training data samples are not sufficiently provided or uncertain information is included in design modeling. Properties of soft computing techniques affect the quality of global approximate model. Evolutionary fuzzy modeling (EFM) and adaptive neuro-fuzzy inference system (ANFIS) are briefly introduced for structural optimization problem in this context. The paper presents the success of EFM depends on how optimally the fuzzy membership parameters are selected and how fuzzy rules are generated.

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A Face Detection Algorithm using Skin Color and Elliptical Shape Information (살색 정보와 타원 모양 정보를 이용한 얼굴 검출 기법)

  • 강성화;김휘용;김성대
    • Proceedings of the IEEK Conference
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    • 2000.11d
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    • pp.41-44
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    • 2000
  • In this paper, we present an efficient face detection algorithm for locating vertical views of human faces in complex scenes. The algorithm models the distribution of human skin color in YCbCr color space and find various ace candidate regions. Face candidate regions are found by thresholding with predetermined thresholds. For each of these face candidate regions, The sobel edge operator is used to find edge regions. For each edge region, we used an ellipse detection algorithm which is similar to hough transform to refine the candidate region. Finally if a substantial number of he facial features (eye, mouth) are found successfully in the candidate region, we determine he ace candidate region as a face region. e show empirically that the presented algorithm an find the face region very well in the complex scenes.

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A Study of Optimal Group Number to Minimize Average Paging Delay (최소 평균 페이징 지연을 위한 최적의 페이징 그룹 수에 관한 연구)

  • Lee, Goo-Yeon
    • Journal of Industrial Technology
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    • v.25 no.B
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    • pp.221-229
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    • 2005
  • We present a numerical analysis of the optimal group number for minimizing the average paging delay. In the analysis, we consider uniform distributions for location probability conditions and apply M/D/1 queueing model to paging message queues of cells. We also get the lower bounds of group numbers and investigate the minimum transmission capacity under average paging delay constraints. Minimizing the average paging delay is important because it means minimizing the amount of bandwidth used for locating mobile terminals. Therefore, the numerical results of this paper will be very useful in PCS system when designing its signalling capacity due to its simplicity and effectiveness.

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A Study on the RTLS Performance Improvement Using WLAN RSSI Level Filtering (무선랜 RSSI 신호의 필터링을 통한 RTLS의 성능 개선에 관한 연구)

  • Lee, Joo-Hyun;Kang, Byeong-Gwon
    • 한국ITS학회:학술대회논문집
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    • 2010.05a
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    • pp.184-187
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    • 2010
  • RFID 기술은 각 사물에 전자태그를 부착하고, 사물의 고유 ID를 무선으로 인식하여, 해당 정보를 수집, 저장, 추적함으로써 사물에 대한 측위, 원거리 관리 및 사물 간 정보교환 등의 서비스를 제공하는 기술이다. RFID의 응용 분야의 하나로 전자태그가 부착되어 있는 대상의 위치를 실시간으로 파악하고 확인할 수 있는 RTLS(Real Time Locating Systems) 기술이 새로이 부각되고 있다. 본 논문에서는 AP의 RSSI(Received Signal Strength Indication)를 이용해 데이터의 정확도를 위해 약 30회의 위치 추정을 통한 위치 추정의 정확도를 알아보고 스무딩을 통한 측정 거리의 오차를 확인했다. AP의 RSSI를 통한 위치추정은 AP가 설치된 건물내의 실내환경에서 이루어졌으며, 비교적 정확한 약 3m의 오차를 보였고, 필터링을 통한 교통 추정값은 그보다 약 0.5~1m 향상된 성능을 보였다.

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The development of the landmark tracking system

  • Lee, Eun Ho;Dickerson, Steve
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10b
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    • pp.1894-1898
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    • 1991
  • A landmark tracking system(LTS) has been developed for use in locating objects in a manufacturing environment. The Landmark Tracking System is an integrated system which consists of a grey scale CCD camera, an image processor, an illumination system based on electronic flash, and software intended primarily for tracking retroreflective landmarks. The term "integreated" means that the camera electronics and the strobe electronics are directly linked to the computer system, governed by the same clock and under direct software control. A novel element in the LTS is that a pinhole is used for the optics.he optics.

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Numerical Analysis for Improving Passing Flow Rate Quantity abound a Radiator (라디에이터 통과풍량 확보를 위한 수치적 검토)

  • 김은필;강상훈
    • Journal of Advanced Marine Engineering and Technology
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    • v.25 no.2
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    • pp.304-310
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    • 2001
  • This paper describes the analysis of flow field using a projection finite element method. The projection scheme with a pressure correction is presented for the analysis of an incompressible Navier-Stokes flow. The projection scheme is analyzed numerically and applied to the well-known bench marking problems such as lid driven cavity. Finally, the projection scheme is applied to a flow through the automobiles front. In the automobiles cooling system, the flow through its front is very important to a cooling performance. The results show that the flow quantity increases by locating the position of bumper to the further front position of a car. And, the improvement on the suction part below a bumper achieves the more passing flow quantity. The attachment of an air dam increases passing flow quantity causing the pressure rise to the front part and the pressure drop beneath a car.

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Automatic partial shape recognition system using adaptive resonance theory (적응공명이론에 의한 자동 부분형상 인식시스템)

  • 박영태;양진성
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.3
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    • pp.79-87
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    • 1996
  • A new method for recognizing and locating partially occluded or overlapped two-dimensional objects regardless of their size, translation, and rotation, is presented. Dominant points approximating occuluding contoures of objects are generated by finding local maxima of smoothed k-cosine function, and then used to guide the contour segment matching procedure. Primitives between the dominant points are produced by projecting the local contours onto the line between the dominant points. Robust classification of primitives. Which is crucial for reliable partial shape matching, is performed using adaptive resonance theory (ART2). The matched primitives having similar scale factors and rotation angles are detected in the hough space to identify the presence of the given model in the object scene. Finally the translation vector is estimated by minimizing the mean squred error of the matched contur segment pairs. This model-based matching algorithm may be used in diveerse factory automation applications since models can be added or changed simply by training ART2 adaptively without modifying the matching algorithm.

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