• 제어로봇시스템학회논문지
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• 제9권2호
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• pp.140-144
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• 2003

A navigation sensor system for outdoor AGV(Automatic Guided Vehicle) using AMR(Anisotropic Magnetoresitive) sensors is described. We derive a formula of the position of AMR sensor using the measured magnetic field intensity due to permanent magnet with constant distance. The system consists of sensor board. sensor control board and position processing board. The sensor board measures magnetic field intensity, the sensor control board controls the measurement of six sensors sequentially, and the position processing board computes the accurate position of the permanent magnet using Least Square Method. We arranged six sensors at intervals of 30cm and measured the position of the permanent magnet moving at intervals of 30cm. Experimental results showed that we can get standard deviation of 2mm and error of &\pm&4.5mm at a height of 20cm from the permanent magnet.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2012년도 춘계학술대회
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• pp.160-161
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• 2012

This paper is to develop & analyze the position & direction error equations in the free-gyro positioning & directional system by using two free gyros and is to find out the amount of the errors. First, the position & direction error equations are introduced and developed, based on the position & direction equations. Second, the value of errors is discussed based on sensors errors.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.53.2-53
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• 2001

The Non-Contact Optical Sensor using the Hologram Laser for CD Pickup was developed to measure a shape of transparent objects and shown a good performance. Therefore the problems caused by the contact sensor are solved by using the Non-Contact Sensor. The Non-Contact Sensor has to move toward the objects and obtain the Focus Error Signal to measure a position of transparent objects. However, if the distance between the sensor and the object is shorter than the working distance of the objective lens, the sensor will be collided against the objects. In this paper we proposed a new algorithm to estimate the start position of the Focus Error Signal to solve the problems of collision between the sensor and the objects. In addition, we verified that the algorithm is free from the collision in the real time measurement.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.800-808
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• 2008

This paper presents a localization algorithm of the outdoor wheeled mobile robot using the sensor fusion method based on indirect Kalman filter(IKF). The wheeled mobile robot considered with in this paper is approximated to the two wheeled mobile robot. The mobile robot has the IMU and encoder sensor for inertia positioning system and GPS. Because the IMU and encoder sensor have bias errors, divergence of the estimated position from the measured data can occur when the mobile robot moves for a long time. Because of many natural and artificial conditions (i.e. atmosphere or GPS body itself), GPS has the maximum error about $10{\sim}20m$ when the mobile robot moves for a short time. Thus, the fusion algorithm of IMU, encoder sensor and GPS is needed. For the sensor fusion algorithm, we use IKF that estimates the errors of the position of the mobile robot. IKF proposed in this paper can be used other autonomous agents (i.e. UAV, UGV) because IKF in this paper use the position errors of the mobile robot. We can show the stability of the proposed sensor fusion method, using the fact that the covariance of error state of the IKF is bounded. To evaluate the performance of proposed algorithm, simulation and experimental results of IKF for the position(x-axis position, y-axis position, and yaw angle) of the outdoor wheeled mobile robot are presented.

• International Journal of Aeronautical and Space Sciences
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• 제18권1호
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• pp.118-128
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• 2017

In this study, we propose a real time inertial navigation system/global positioning system (INS/GPS) integrated smoothing algorithm based on an extended Kalman filter (EKF) and a position damping loop (PDL) for synthetic aperture radar (SAR). Integrated navigation algorithms usually induce discontinuities due to error correction update by the Kalman filter, which are as detrimental to the performance of SAR as the relative position error. The proposed smoothing algorithm suppresses these discontinuities and also reduces the relative position error in real time. An EKF estimates the navigation errors and sensor biases, and all the errors except for the position error are corrected directly and instantly. A PDL activated during SAR operation period imposes damping effects on the position error estimates, where the estimated position error is corrected smoothly and gradually, which contributes to the real time smoothing and small relative position errors. The residual errors are re-estimated by the EKF to maintain the estimation performance and the stability of the overall loop. The performance improvements were confirmed by Monte Carlo simulations. The simulation results showed that the discontinuities were reduced by 99.8% and the relative position error by 48% compared with a conventional EKF without a smoothing loop, thereby satisfying the basic performance requirements for SAR operation. The proposed algorithm may be applicable to low cost SAR systems which use a conventional INS/GPS without changing their hardware configurations.

• Journal of Positioning, Navigation, and Timing
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• 제11권1호
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• pp.35-44
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• 2022

In this paper, a dual foot (DF)-PDR system is proposed for the fusion of integration (IA)-based PDR systems independently applied on both shoes. The horizontal positions of the two shoes estimated from each PDR system are fused based on a particle filter. The proposed method bounds the position error even if the walking time increases without an additional sensor. The distribution of particles is a non-Gaussian distribution to express the lateral error due to systematic drift. Assuming that the shoe position is the pedestrian position, the multi-modal position distribution can be fused into one using the Gaussian sum. The fused pedestrian position is used as a measurement of each particle filter so that the position error is corrected. As a result, experimental results show that position of pedestrians can be effectively estimated by using only the inertial sensors attached to both shoes.

• 한국엔터테인먼트산업학회논문지
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• 제5권2호
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• pp.166-172
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• 2011

저가의 홀센서를 이용하여 자석의 위치를 인식하는 센서 시스템을 제안하였다. 먼저 모델식을 이용하여 자석에 의한 자기장을 측정하고, 수평 자계와 수직 자계의 특성을 분석하여, 센서의 배치방법을 결정하였다. 자석과 홀센서의 위치 관계에 따라서 측정된 자기장 값으로부터 자석의 위치를 추정하는 알고리즘을 제안하고, 이론적인 오차를 계산하였다. 또한 마이크로 컨트롤러를 사용하여 개발할 때의 단점인 실시간 데이터 확인이 어려운 점을 극복하기 위해서 컴퓨터용 응용 프로그램을 작성하여, 작업의 수월성을 높였다. 계산된 이론적 오차는 0.0025cm 이하로 나타났으며 실제로 개발된 시스템의 오차는 0.07cm 이하로 측정되어 여러 가지 상황에서 제안한 방법들의 우수성을 입증하였다.

• 한국해양공학회지
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• 제11권3호
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• pp.170-179
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• 1997

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.

• 전자공학회논문지SC
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• 제46권2호
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• pp.28-35
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• 2009

이동 로봇의 요소기술로 위치추정 기술은 로봇의 위치 판별과 사용자가 원하는 위치로 주행하기 위해 반드시 필요한 기술이다. 휠 구동을 기반으로 하는 로봇의 위치추정 방법은 오도메터리 정보를 이용한 기술이다. 그러나 오도메터리 정보를 이용한 위치추정은 이동로봇이 주행하는 동안 휠과 주행 바닥면 사이에서 슬립현상의 발생으로 실제 위치 차이가 발생하고 정량적인 오차 값 확인이 쉽지 않다. 본 연구에서는 이 문제를 해결하기 위해 오도메터리와 관성센서를 이용하여 위치추정 오차를 최소화하는 방법을 제시한다. 또한 관성센서가 영상을 이용한 SLAM에서도 위치오차를 줄일 수 있는 기법을 제시한다.

• 한국인터넷방송통신학회논문지
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• 제14권1호
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• pp.31-36
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• 2014

실내에서의 위치기반 서비스를 위한 실내 위치 인식 기술에 대한 연구가 활발하다. 음향 신호와 TDOA 기술을 기반으로 하는 3차원 위치 인식 시스템에 있어서, 마이크 센서의 개수와 배열 위치에 따라 추정된 위치의 오차 특성이 달라지므로, 본 논문에서는 마이크 센서의 배열과 측정된 거리 차이값의 오차 크기에 따른 추정 위치의 오차를 DOP로 분석하고, 그 추정 위치 오차 패턴과 추정 위치 오차값을 고려하여 최적의 마이크 배열을 결정하는 방법에 대해서 연구하였다.