• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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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.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.06a
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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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• 2001.10a
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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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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• v.18 no.1
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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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• v.11 no.1
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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.

• Journal of Korea Entertainment Industry Association
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• v.5 no.2
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• pp.166-172
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• 2011

This paper presents a sensor system which recognizes the location of a magnet using cheap hall sensor. The proposed methods measure magnetic field from a magnet using model equation, analyze the property of horizontal and vertical magnetic field, and decide the method of sensor arrangement. And, this paper proposes the algorithm which infers the location of a magnet from the measured magnetic field that relates the position between the magnet and the hall sensor, and calculate theoretical error, which is found to be no more than 0.0025cm. The results actually measured show that the measured error no more than 0.07cm and confirm that proposed systems are highly applicable to the various situations.

• Journal of Ocean Engineering and Technology
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• v.11 no.3
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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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.28-35
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• 2009

Positioning technology which a part technology of Mobile Robot is an essential technology to locate the position of Robot and navigate to wanted position. The Robot that based on wheel drive uses Odometry position. technology. But when using Odometry positioning technology, it's hard to find out constant error value because a slip phenomenon occurs as the Robot runs. In this paper, we present the way to minimize positioning error by using Odometry and Inertial sensor. Also, the way to reduce error with Inertial sensor on SLAM using image will be shown, too.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.31-36
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• 2014

A study on the indoor positioning system has been active recently for the location based service indoors. In the 3 dimensional positioning system based on the acoustic signal and TDOA technology, the error characteristics of the estimated source position would be changed depending on the number of microphones and the pattern of the microphone array. In this paper, the estimated position error according to the measured distance error between the microphones and the signal source is analyzed, and the optimum microphone array is decided considering the estimated position error patterns and the total amount of the estimated position error.