• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.616-619
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• 2003

In this paper, we develop an input device equipped with accelerometers and gyroscopes. The installed sensors measure the inertial measurements i.e., accelerations and angular rates produced by the movement of the system when a user is writing on the plane surface or in the three dimensional space. The gyroscope measurement are integrated once to give the attitude of the system and consequently used to remove the gravity included in the acceleration measurements. The compensated accelerations bin doubly integrated to yield the position of the system. Due to the integration processes involved in recovering the users'motions, the accuracy of the position estimation significantly deteriorates with time. Among various error sources of the system incorrect estimation of attitude causes the largest portion of the positioning error since the gravity is not fully cancelled. In order to solve this problem, we propose a Kalman filler-based attitude estimation algorithm which fuses measurement data from accelerometers and gyroscopes by fuzzy logic approach. In addition, the online calibration of the gyroscope biases are performed in parallel with the attitude estimation to give more accurate attitude estimation. The effectiveness and the feasibility of the presented system is demonstrated through computer simulations and actual experiments.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.10
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• pp.13-21
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• 2007

Based on the measurement results, a limit value for the change of the brightness of the headlamp, and an estimation algorithm considering the driver's safety was developed. Limitation values concerning being uncomfortable, blinking, and brightness change were indicated based on a subjective estimation of the psychological estimation. Also a safety estimation algorithm and a limitation value for stopping safely without the threat of obstacles to the vehicle were indicated by the perception measurement.

• Proceedings of the KIPE Conference
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• 2016.11a
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• pp.59-60
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• 2016

Flooded lead acid batteries are still very popular in the industry because of their low cost as compared to their counterparts. State of Charge (SOC) estimation is of great importance for a flooded lead acid battery to ensure its safe working and to prevent it from over-charging or over-discharging. Different types of Kalman Filters are widely used for SOC estimation of batteries. The values of process and measurement noise covariance of a filter are usually calculated by trial and error method and taken as constant throughout the estimation process. While in practical cases, these values can vary as well depending upon the dynamics of the system. Therefore an Adaptive Unscented Kalman Filter (AUKF) is introduced in which the values of the process and measurement noise covariance are updated in each iteration based on the residual system error. A comparison of traditional and Adaptive Unscented Kalman Filter is presented in the paper. The results show that SOC estimation error by the proposed method is further reduced by 3 % as compared to traditional Unscented Kalman Filter.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.5
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• pp.777-787
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• 1995

This paper presents a new method for automatically calibrating robot link (Kinematic) parameters during the process of estimating motion parameters of a moving object. The motion estimation is performed based on stereo cameras mounted on the end-effector of a robot manipulator. This approach significantly differs from other calibration approaches in that the calibration is achieved by simply observing the motion of the moving object (without resorting to any other external calibrating tools) at numerous and widely varying joint-angle configurations. A differential error model, which expresses the measurement errors of a robot in terms of robot link parameter errors and motion parameters, is developed. And then a measurement equation representing the true measurement values is derived. By estimating the above two kinds of parameters minimizing the difference between the measurement equations and the true moving pattern, the calibration of the robot link parameters and the estimation of the motion parameters are accomplished at the same time.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1411-1414
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• 1997

It is essential to obtain a distane informaion in order to completely execute assembly tasks such as a grasping and an insertion. In this paper, we propose a method estimating a measurement distance from a sensor to an object through using the omni-directional image sensing system for assembly(OISSA) and show its features and feasibility by a computer simulation. The method, utilizing a forwarded motion stereo technique, is simple to search the corresponding points and possible to immediatiely obtain a three-dimensional 2.pi.-shape information.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.1
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• pp.131-136
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• 2018

Reliable velocity estimation technology for trains is one of technologies used to operate trains safely and effectively. Various sensors such as tachometers, doppler radars, and global positioning systems are used to estimate velocity of a train. Tachometer is widely used to estimate velocity of a trains due to its simplicity, small volume, cost-effectiveness, continuously measurement at high speed, and robustness against noise. Accuracy in the velocity calculation using a tachometer depends on quantization error, measurement error of wheel radius or diameter, and tachometer's imperfection from manufacturing or installation process. In this paper, we present an accurate velocity estimation method using a low-resolution tachometer, which is commonly installed on a high-speed train. Baseline estimation method is proposed to accurately calculate the velocity of the high-speed train from tachometer's pulses. HEMU-430x test train is used for the experiment and verification of the proposed method. Experimental results with several routes show that the proposed method is more accurate than a conventional method.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.239-243
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• 1990

This paper presents a algorithm to improve accuracy and reliability in state estimation of contaminated bad data. The conventional algorithms for detection of bad data confront the problems of excessive memory requirements and long computation time. In order to overcome measurement compensation approach is proposed to reduce computation time and partitioned measurement error model has the advantage of remarkable reduction in computation time and memory requirements in estimated error computation. The proposed algorithm has been tested for IEEE sample systems, which shows its applicability to on-line power systems.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.2
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• pp.144-153
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• 1991

This paper presents an algorithm to improve accuracy and reliability in the state estimation of contaminated bad data. The conventional algorithms for detection of bad data have the problems of excessive memory requirements and long computation time. In order to overcome these problems, a measurement compensation approach is proposed to reduce computation time, and the partitioned measurement error model has the advantage of remarkable reduction in computation time and memory requirements in estimated error computation. The proposed algorithm has been tested for IEEE sample systems, which shows its applicability to on-line power systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.10
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• pp.850-857
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• 2012

A moving network is the usage model that provides the mobile stations to the communication service via the mobile relay deployed in the high-speed vehicle. The mobile relay periodically performs the signal strength measurement of the neighbor base stations to select the target base station during the handover procedure. The mobile stations experience the service disruption during the measurement of the mobile relay. In this paper, we propose the estimation based scanning method to overcome the service disruption of the mobile stations connected via the mobile relay. In the proposed method, mobile stations subordinated in the mobile relay periodically measure the signal strength of neighbor base stations in order to perform handover. The measured signal strength is used to estimate the signal strength between the mobile relay and the neighbor base station. We performed simulations in order to evaluate the performance of the proposed method in terms of the estimation accuracy and the overhead due to the exchange of channel information. By the simulation result, The estimation error is less than 4dBm when more than 6 mobile stations are used for the estimation. The overhead caused by the proposed method is less than that caused by the direct measurement of the mobile relay when the data rate is more than 8Mbps.

• Journal of Biomedical Engineering Research
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• v.29 no.5
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• pp.371-375
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• 2008

In blood pressure measurement, the oscillometric method detects and analyzes the pulse pressure oscillation while deflating the cuff around the arm. For its principle, one has to inflate cuff pressure above the subject's systolic pressure and deflate below the diastolic pressure. Most of the commercialized devices inflate until the fixed target pressure and deflate until the fixed completion pressure because there is no way to know the systolic and diastolic pressure before measurement. Too high target pressure makes stress to the subject and too low target pressure makes big error or long measurement time because of re-inflation. There are similar problems for inadequate completion pressure. In this study, we suggest new algorithm to set proper target and completion pressure for each subject by analyzing pressure waveform while inflating period. We compared our proposed method and auscultation method to see the errors of estimation. The differences between the two measurements were -4.02$\pm$4.80mmHg, -10.50$\pm$10.57mmHg and -0.78$\pm$5.l7mmHg for mean arterial pressure, systolic pressure and diastolic pressure respectively. Consequently, we could set the target pressure by 30 mmHg higher than our estimation and we could stop at 20mmHg lower than our estimated diastolic pressure. Using this method, we could reduce the measurement time.