• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1259-1263
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• 2004

This paper describes position estimation algorithm using neural network for the navigation of the vision-based wheeled mobile robot (WMR) in a corridor with taking ceiling lamps as landmark. From images of a corridor the lamp's line on the ceiling in corridor has a specific slope to the lateral position of the WMR. The vanishing point produced by the lamp's line also has a specific position to the orientation of WMR. The ceiling lamps have a limited size and shape like a circle in image. Simple image processing algorithms are used to extract lamps from the corridor image. Then the lamp's line and vanishing point's position are defined and calculated at known position of WMR in a corridor. To estimate the lateral position and orientation of WMR from an image, the relationship between the position of WMR and the features of ceiling lamps have to be defined. But it is hard because of nonlinearity. Therefore, data set between position of WMR and features of lamps are configured. Neural network are composed and learned with data set. Back propagation algorithm(BPN) is used for learning. And it is applied in navigation of WMR in a corridor.

• Journal of the Ergonomics Society of Korea
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• v.23 no.3
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• pp.89-99
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• 2004

A comprehensive psychophysical scaling system, multiple-modality magnitude estimation system (MMES) has been designed to measure subjective multidimensional human perception. Unlike paper-based magnitude estimation systems, the MMES has an additional auditory peripheral cue that varies with corresponding visual magnitude. As the simplest, purely psychological case, bimodal divided-attention conditions were simulated to establish the superiority of the MMES. Subjects were given brief presentations of pairs of simultaneous stimuli consisting of visual line-lengths and auditory white-noise levels. In the visual or auditory focused-attention conditions, only the line-lengths or the noise levels perceived should be reported respectively. On the other hand, in the divided-attention conditions, both the line-lengths and the noise levels should be reported. There were no significant differences among the different attention conditions. Human performance was better when the proportion of magnitude in stimulus pairs were identically presented. The additional auditory cues in the MMES improved the correlations between the magnitude of stimuli and MMES values in the divided-attention conditions.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.521-530
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• 2005

In this paper, a new high resolution reflectometry scheme, time-frequency domain reflectometry(TFDR), isproposed to detect and estimate a fault in a transmission line. Traditional reflectometry methodologies have been achieved either in the time domain or in the frequency domain only. However, the TFDR can jump over the performance limits of the traditional reflectometry methodologies because the acquired signal is analyzed in time and frequency domain simultaneously. In the TFDR, the new reference signal and the novel TFDR algorithm are proposed for analyzing the acquired signal in the time-frequency domain. Because the reference signal of Gaussian envelop chirp signal is localized in the time and frequency domain simultaneously, it is suitable to the analysis in the time-frequency domain. In the proposed TFDR algorithm, the time-frequency distribution function and the normalized time-frequency cross correlation function are used to detect and estimate a fault in a transmission line. That algorithm is verified for real-world coaxial cables which are typical transmission line with different types of faults by the TFDR system composed of real instruments. The performance of the TFDR methodology is compared with that o( the commercial time domain reflectomeoy(TDR) experiments, so that concludes the TFDR methodology can detect and estimate the fault with smaller error than TDR methodology.

• Korean Journal of Computational Design and Engineering
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• v.13 no.4
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• pp.296-304
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• 2008

Recently, various attempts are being done to apply off-line programming system to field of paint robot. But most commercial simulation softwares have problems that are slow simulation speed and not support various painting paramenters on simulation. This paper proposes enhanced paint simulation method for off-line programming system. For these, this method used the mathematical model of flux field from a previous research. The flux field has the flux distribution function, which reflects on the feature of paint spray. A previous research derived this flux distribution function for an integral function and calculated paint thickness function for an integral function. But if flux distribution function is defined as an integral function, it is inadequate to use for real-time simulation because a number of calculation is needed for estimation of paint thickness distribution. Therefore, we defined the flux distribution function by numerical method for reducing a mount of calculation for estimation of paint thickness. We derived the equation of paint thickness function analytically for reducing a mount of calculation from the paint distribution function defined by numerical method. In order to prove proposed paint simulation method this paper compares the simulated and measured thickness. From this comparison this paper show that paint thickness distribution is predicted precisely by proposed spray paint simulation process.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.825-828
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• 1991

This paper addresses estimation of the relative shift vector from aerial image sequences. We perform similarity function tests and decide the most appropriate similarity function for the visual navigation system using aerial images. Finally, we propose the maximum variance reference line selection method for reducing the estimation error of the shift vector.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.785-787
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• 1999

In this paper, recursive least square algorithm is presented to estimate the parameters of step motor under low-speed operation. Parameter estimation is important for compensating the input current by calculating the ratio of the motor torque constant and detent torque constant that causes torque-ripple in low-speed applications. On-line parameter estimation process is a preliminary procedure to apply step motor to adaptive control. Computer simulation shows that the estimated parameters converge in finite time.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.76.5-76
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• 2001

This paper considers the parameter estimation for the state-space model based time-delay systems in the case that the Lyapunov stability of the system is guaranteed. In order to estimate the parameters, two estimation methods can be proposed which are known as the parallel model and the series parallel model. It is shown that the parameters can be estimated using each method, and also certied that the results are correct by simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.268-273
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• 1991

Missile and target closing velocity is used in the proportional navigation(PN) missile guidance loop. But it is difficult to estimate the closing velocity when passive seeker is used and only the Line-of-Sight(LOS) rate is available in the guidance loop. In this study, new closing velocity estimation method is developed. This method uses LOS rate measurement only and uses some characteristics of PN guidance law. The Lyapunov method is used to analyze the stability of the developed estimation method.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.188-191
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• 2002

This paper presents a method for on-line estimation of rotor time constant of induction motor. The proposed method applies a model reference adaptive system(MRAS) using rotor flux vector. The MRAS consists of two independent observers to estimate the rotor flux vector; one based on voltage equations of rotor flux vector, the other based on current equations of them. The MRAS utilizes concept of auxiliary variables to normalize observer output and decrease high-frequency components of its input. Experimental results verify the validity and usefulness of proposed method

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1101-1104
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• 1995

Through welding fabrication, user can feel an surficaial and capable unsatisfaction because of welded defects, Generally speaking, these are called weld defects. For checking these defects effectively without time loss effectively, weldability estimation system setup isan urgent thing for detecting whole specimen quality. In this study, by laser vision camera, catching a rawdata on welded specimen profiles, treating vision processing with these data, qualititative defects are estimated from getting these information at first. At the same time, for detecting quantitative defects, whole specimen weldability estimation is pursued by multifeature pattern recognition, which is a kind of fuzzy pattern recognition. For user friendly, by weldability estimation results are shown each profiles, final reports and visual graphics method, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line weldability estimation.