• 소성∙가공
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• 제13권7호
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• pp.594-599
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• 2004

In the sheet metal forming operations, the strain measurement of sheet panel is an essential work which provides the formability information needed in die design, process design, and product inspection. To measure efficiently complex geometry strains, the 3-dimensional automative strain measurement system, which theoretically has a high accuracy but practically has about 3～5％ strain error, is often used. For eliminating the strain error resulted in measuring the strains of formed panels using an automated strain measurement system, the position error calibration method is suggested, which computes accurate strains using the grids with accurate nodal coordinates. The accurate nodal coordinates are calculated by adding the nodal coordinates measured by the measurement system and the position error found using the multiple regression method as a function of the main error parameters obtained from the analysis of strain error in a standard cube. For the verification, the strain distributions of square and dome cups obtained from the position error calibration method are compared with those provided by the finite element analysis and ASAME.

• 한국공작기계학회논문집
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• 제10권1호
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• pp.36-42
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• 2001

In this paper, PSD(Position Sensitive Detector) sensor system that estimates position for moving objects in 2D plane is developed. PSD sensor is used to measure the position the position of and incidence light in real-time. To get the position of light source of moving target, a new parameter calibration algorithm and neural network technique are proposed and applied. Real-time position measurements of the mobile robot with light source is examined to validate the proposed method. It is shown that the proposed technique provides accurate position estimation of the moving object.

• 한국정밀공학회지
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• 제18권5호
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• pp.9-11
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• 2001

• 대한전기학회논문지:전력기술부문A
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• 제48권12호
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• pp.1537-1543
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• 1999

In this paper, PSD(Position Sensitive Detector) sensor system that estimates position for moving objects in 2D plane is developed. PSD sensor is used to measure the position of an incidence light in real-time. To get the position of light source of moving target, a new parameter calibration algorithm and neural network technique are proposed and applied. Real-time position measurements of the mobile robot with light source is examined to validate the proposed method. It is shown that the proposed technique provides accurate position estimation of the moving object.

• International Journal of Aeronautical and Space Sciences
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• 제13권2호
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• pp.250-259
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• 2012

The need for position information in indoor environments has been growing lately. Several indoor navigation systems have been studied. Among them, pseudolite-based indoor positioning systems are one of the best systems to obtain precise position measurements. However, the installation of such systems is very difficult because the calibration of pseudolite antenna position is complicated. For precise calibration, the use of carrier phase measurements is necessary, and whenever carrier phase measurements are considered, problems with cycle ambiguity appear. In this paper, a new approach to calibrate the positions of pseudolite antennas is proposed. By using a multi-antenna, the ambiguity can be eliminated, epoch by epoch, for every single carrier phase measurement. Moreover, the number of calibration points can be reduced down to 3 by use of measurements collected at unknown positions. Using the proposed methods, the process of the collection of carrier phase measurements becomes considerably simple and convenient. Simulation results are presented to verify the proposed algorithms.

• 대한인간공학회지
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• 제19권1호
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• pp.77-90
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• 2000

The aim of this study is to develop and evaluate an efficient camera calibration method for vision-based head tracking. Tracking head movements is important in the design of an eye-controlled human/computer interface. A vision-based head tracking system was proposed to allow the user's head movements in the design of the eye-controlled human/computer interface. We proposed an efficient camera calibration method to track the 3D position and orientation of the user's head accurately. We also evaluated the performance of the proposed method. The experimental error analysis results showed that the proposed method can provide more accurate and stable pose (i.e. position and orientation) of the camera than the conventional direct linear transformation method which has been used in camera calibration. The results of this study can be applied to the tracking head movements related to the eye-controlled human/computer interface and the virtual reality technology.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2006년도 춘계학술발표회 논문집
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• pp.9-14
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• 2006

A determinated position with GPS (Global Positioning System) data processing is the position of the phase center of a GPS antenna. The phase center of a GPS antenna is. not a stable point and depends on the azimuth and elevation angles of GPS satellites. It is known that the phase center variations (PCV) of a GPS antenna are greater in the vertical than the horizontal directions. The PCV calibration models for a GPS. antenna has two approaches: relative and absolute. In this study. we compared the two calibration models using the six operational permanent GPS stations in South Korea and analysed the PCV of each station. In addition, we. tested two different kinds of GPS antennas and compared the results. The accuracy and precision of the relative calibration was worse than the absolute calibration.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.527-530
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• 1996

The Kalman filter has been used as a self-localization method for the mobile robot. To satisfy the assumptions inherent in the Kalman filter, we should calibrate the sensors of the robot before use of them. However, it is generally hard to find exact sensor parameters, and the parameters may change during the robot task as the environment varies. Thus we need to perform on-line sensor calibration, by which we can obtain more credible location of the mobile robot. In this paper, we present an on-line sensor calibration scheme which estimates the unknown sensor bias and the current position of the robot. To this end, first we find out the calibration errors of the sensor from redundant sensory data using the parity vector and recursive minimum variance estimation. Then we calculate the current position of the robot by weighted least square estimation without internal encoder data. The performance of the proposed method is evaluated through computer simulation.

• 제어로봇시스템학회논문지
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• 제15권12호
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• pp.1223-1231
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• 2009

We derive a systematic and iterative calibration algorithm, and position and pose estimation algorithm for the mobile robots in formation system based on the vision system. In addition, we develop a coordinate matching algorithm which calculates matched sequence of order in both extracted image coordinates and object coordinates for non interactive calibration and pose estimation. Based on the results of calibration, we also develop a camera simulator to confirm the results of calibration and compare the results of simulations with those of experiments in position and pose estimation.

• 한국통신학회논문지
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• 제31권4C호
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• pp.400-406
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• 2006

3차원 정보 복원이나 형상 복원, 가상 물체 삽입 등의 과정을 수행하기 위해서는 영상 촬영에 사용된 카메라의 위치와 방향, 그리고 초점 거리 등의 변수가 필요하다. 본 논문에서는 이차원 영상간의 대응관계를 이용하여 카메라 내부 변수인 초점 거리를 추정하는 셀프 캘리브레이션(self-calibration) 과정에서 특징점의 위치가 초점 거리 추정에 미치는 영향을 분석하였다. 캘리브레이션에 사용하는 특징점과 주점과의 거리에 따라 초점 거리 추정 결과에 미치는 영향을 시뮬레이션을 통하여 검증하고, 이를 바탕으로 오차 민감도를 줄일 수 있는 특징점 선택 방법을 제안한다.