• 센서학회지
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• 제10권5호
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• pp.329-336
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• 2001

This paper describes the steering control and geomagnetism cancellation for an autonomous vehicle using an MR sensor. The magneto-resistive (MR) sensor obtains the vector summation of the magnetic fields from embedded magnets and the Earth. The vehicle is controlled by the magnetic fields from embedded magnets. So, geomagnetism is the disturbance in the steering control system. In this paper, we propose a new method of the sensor arrangement in order to remove the geomagnetism and vehicle body interference. The proposed method uses two MR sensors located in a level plane and the steering controller has been developed. The controller has three input variables ($dB_x$, $dB_y$, $dB_z$) using the measured magnetic field difference, and an output variable (the steering angle). A simulation program was developed to acquire the data to teach the neural network, in order to test the ability of a neural network to learn the steering control process. Also, the computer simulation of the vehicle (including vehicle dynamics and steering) was used to verify the steering performance of the vehicle controller using the neural network. From the simulation and field test, good result was obtained and we confirmed the robustness of the neural network controller in a real autonomous vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.32.6-32
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• 2001

This paper describes the steering control and geomagnetism cancellation for an autonomous mobile robotusing MR sensors. The magnetic-resistive (MR) sensor obtains the vector summation of the magnetic fields from embedded magnets and the Earth. The robot is controlled by the magnetic fields from embedded magnets. So, geomagnetism is the disturbance in the steering control system. In this paper, we propose a new method of the sensor arrangement in order to remove the geomagnetism and robotbody interference. The proposed method uses two MR sensors located in a level plane and the steering controller has been developed. The controller has three input variables (dBx, dBy, dBz) using the measured magnetic field difference, and an output variable (the steering angle) ...

• 센서학회지
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• 제16권1호
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• pp.17-23
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• 2007

This paper presents a miniaturized turn-counting sensor (TCS) where the geomagnetism and high-rpm rotation of ammunition are used to detect the turn number of ammunition for applications to small-caliber turn-counting fuzes. The TCS, composed of cores and a coil, has a robust structure with no moving part for increasing the shock survivability in the gunfire environments of ${\sim}30,000$ g's. The TCS is designed on the basis of the simulation results of an electromagnetic analysis tool, $Maxwell^{(R)}$3D. In experimental study, the static TCS test using a solenoid-coil apparatus and the dynamic TCS test (firing test) have been made. The presented TCS has shown that the induction voltage of $6.5{\;}mV_{P-P}$ is generated at the magnetic flux density of 0.05 mT and the rotational velocity of 30,000 rpm. From the measured signal, the TCS has shown the SNR of 44.0 dB, the nonlinearity of 0.59 % and the frequency-normalized sensitivity of $0.26{\pm}0.01{\;}V/T{\cdot}Hz$ in the temperature range of $-30{\sim}+43^{\circ}C$. Firing test has shown that the TCS can be used as a turn-counting sensor for small-caliber ammunition, verifying the shock survivability of TCS in high-g environments.

• 한국측량학회지
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• 제32권3호
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• pp.253-259
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• 2014

There has been a need for replacing human labors with a robot in such dangerous and hard jobs of various construction sites. For that reason, many researches have been made about the high quality robot, which performs its duty instead of human labors. This study is about auto surveying system development based on VRS-GPS which enables autodriving in dangerous areas where it's difficult for humans to measure directly. This study is about the auto-surveying system development, based on VRS-GPS, which enables auto-drive in dangerous areas, whereas difficult for humans to measure directly. The GPS is made with GRXI and SHC250 controllers of the SOKKIA company. The auto surveying system is composed of DPS module, geomagnetism sensor, bluetooth, gimbals, IMU, etc to automatic drive via enter into a route of position. The developed auto surveying system has installed the carmeras for front and vertical axis as well as systems to grasp situation of surveying with smartphone in real time. The result from analysed RMSE of auto surveying system and VRS-GPS surveying is 0.0169m of X-axis and 0.0246m of Y-axis.

• 센서학회지
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• 제22권2호
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• pp.111-117
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• 2013

The autonomous driving method using magnetic sensors recognizes the position by measuring magnetic fields in autonomous robots or vehicles after installing magnetic markers in a moving path. The Position estimate method using magnetic sensors has an advantage of being affected less by variation of driving environment such as oil, water and dust due to the use of magnetic field. It also has the advantages that we can use the magnet as an indicator and there is no consideration for power and communication environment. In this paper, we propose an efficient sensor system for an autonomous driving vehicle supplemented for existing disadvantage. In order to efficiently eliminate geomagnetism, we analyze the components of the horizontal and vertical magnetic field. We propose an algorithm for position estimation and geomagnetic elimination to ease analysis, and also propose an initialization method for sensor applied in the vehicle. We measured and analyzed the developed system in various environments, and we verify the advantages of proposed methods.

• 한국산학기술학회논문지
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• 제14권10호
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• pp.5215-5220
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• 2013

최근 건설현장에서는 3D 기피 현상으로 자동화에 대한 관심이 증대되고 있다. 본 연구는 개발된 VRS-GPS 기반 자동 측위시스템으로 해안매립지를 측량한 결과에 관한 연구이다. 자동측위시스템에 설치된 GPS는 GRX1 수신기와 SHC250 컨트롤러를 사용하였다. 자동측위시스템은 DSP모듈, 지자기센서, 블루투스, 짐벌, IMU등으로 구성되어 있으며, 입력된 위치경로로 자동주행이 가능하도록 하였다. 개발된 GPS 자동측위시스템은 전방과 구심점 관측 카메라를 설치하여 측량상황을 스마트폰으로 실시간으로 파악 할 수 있도록 하였다. 개발된 자동측위시스템을 건설현장에 적용하여 실험한 결과 평균제곱근오차는 X축에서 0.009m, Y측에서 0.010m, 높이는 0.002m로 나타났으며, 현장적용 가능성이 있음을 확인하였다.

• 한국인터넷방송통신학회논문지
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• 제22권6호
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• pp.137-141
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• 2022

지자기를 측정하여 방위각을 추정하는 방법은 매우 오래전부터 사용되어 왔다. 그러나 실내외의 금속 구조물 때문에 지자기에 외란이 발생하여 추정된 방위각에 오차가 발생하는 경우가 많다. 이를 보정하기 위한 연구가 많이 진행되어 왔지만 오차를 줄이는데 한계가 있다. 본 논문에서는 측정된 지자기 센서 값을 LSTM 구조의 신경망에 적용하여 방위각을 추정하는 방법을 제안한다. 신경망을 학습시키기 위해서는 데이터의 사전 처리가 매우 중요하며, 본 논문에서는 스마트폰에 내장된 가속도 센서와 자이로 센서, 지자기 센서를 이용하여 데이터를 수집하고, EKF를 사용하여 지자기 센서 값을 균등하게 샘플링하는 방법으로 학습 데이터를 생성하였다. 4개의 은닉층을 사용하여 평균 방위각 추정 오차가 0.9도인 결과를 얻었다.

• 센서학회지
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• 제14권6호
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• pp.409-414
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• 2005

For an intelligent vehicle driving which uses magnetic markers and magnetic sensors, we can get every kind of road information while moving the vehicle if we use the code that is encoded with N, S pole direction of markers. If we make it an only aim to move the vehicle, it becomes easy to control the vehicle the more we put markers close. By the way, to recognize the direction of a marker pole it is much better that the markers have no effect each other. To get road informations and move the vehicle autonomously we propose the methods of arranging magnetic sensors and algorithm of recognizing the position of the vehicle with those sensors. We verified the effectiveness of the methods with computer simulation.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2008년도 공동학술대회
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• pp.85-92
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• 2008

국립해양조사원에서는 우리나라 관할 해역에 대한 국가해양기본도 조사계획을 수립하여 1996년부터 동해를 시작으로 연차적으로 한반도 주변의 해역 전체에 대한 해양조사를 실시 중에 있고, 본 논문은 1999년도에 '해양2000호'를 이용하여 서해 남부지역에서 측정한 해양 지자기 자료를 이용하였으며, 지자기 자료를 처리하고 이를 해석하는 과정에서 지자기 이상대의 원인을 밝히는데 목적이 있다. 자력자료 처리는 불량자료의 검색 및 제거, Sensor 위치보정, 선체자기장 영향 보정, 일변화 보정, 정규보정, 교차점 오차 보정 등의 과정을 거쳐 조사 해역에서의 전자력치와 지자기 이상치를 구하였다. 조사해역의 전자력 분포는 $49000\;{\sim}\;51600\;nT$로 황해 해역에서의 정상적인 전자력세기 분포 범위에 속하는 것으로 판단된다. 등자력선의 분포는 북동-남서 방향으로 분포하고 있으며 북서쪽으로 갈수록 전자력치가 증가한다. $124^{\circ}$ 49' 48" E, $35^{\circ}$ 10' 48" N $\sim$ $125^{\circ}$ 7' 48" E, $35^{\circ}$ 33' 00" N 사이 구간 해역에 대한 자기 이상과 탄성파 단면도를 비교한 결과와 모델링 결과가 기존 탄성파 탐사단면에서 밝혀진 지하지질구조와 잘 일치하고 있다. 따라서 자력이상의 분포는 대체적으로 해저면 하부에 발달되어 있는 제3기 퇴적분지와 백악기 기반암의 분포에 따른 영향을 나타내고 있는 것으로 판단된다.