• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.423-423
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• 2000

This paper proposes an effective algorithm for following a wall by an autonomous mobile robot with sonar sensors and infrared sensors in an indoor environment. The proposed method uses deadreckoning to estimate the current position and orientation of a mobile robot. Sonar sensor data are used to estimate shape and position of wall using proposed algorithm. Infrared sensor data are used as assistant when sonar sensor data is uncertain. Simulation results using mobile robot show that the proposed algorithm is proper for the following wall.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.1
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• pp.100-107
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• 2003

This study was to control magnetic field orientation-typed sensorless vector control by applying the theory of a rotor flux observer to drive an induction motor. This research suggested a new speed estimation method that estimates speed with the rotor flux obtained by using a flux observer and the variable of state current detected by a current sensor without a speed sensor. Because the speed estimation method is independent from the motor constants, it is not necessary to control the gain of the parameters and the algorithm is simple. In the findings of the study, the researcher was convinced of the control function and the possibility of realization in the simulation experiment of sensorless vector control system by using DSP(Digital Signal Prosessor).

• International Journal of Aeronautical and Space Sciences
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• v.11 no.1
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• pp.31-40
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• 2010

For weapon cueing and Head-Mounted Display (HMD), it is essential to continuously estimate the motion of the helmet. The problem of estimating and predicting the position and orientation of the helmet is approached by fusing measurements from inertial sensors and stereo vision system. The sensor fusion approach in this paper is based on nonlinear filtering, especially expended Kalman filter(EKF). To reduce the computation time and improve the performance in vision processing, we separate the structure estimation and motion estimation. The structure estimation tracks the features which are the part of helmet model structure in the scene and the motion estimation filter estimates the position and orientation of the helmet. This algorithm is tested with using synthetic and real data. And the results show that the result of sensor fusion is successful.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2067-2069
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• 2002

The study of the vector control of the induction machine without speed sensor is going on and there are the adaptive performance method to use the flux observer. This study is to make the vector control without the speed sensor based on the flux oriented reference vector control theory. This paper proposes the new speed follow-up method to deduce the current value in the current sensor and the 2 order flux observer based on the observer theory and examine the possibility to realize the flux oriented vector control system using the simulation in this proposed method of this study.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1998.06a
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• pp.411-414
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• 1998

In this paper, the silicon-nitride membrane structure for IR sensor was fabricated through the etching and the direct bonding. The PT layer as a IR detection layer was deposited on the membrane and its characteristics were measured. The attack of PT layer during the etching of silicon wafer as well as the thermal isolation of the IR detection layer can be solved through the method of bonding/etching of silicon wafer. Because the PT layer of c-axial orientation rained thermal polarization without polling, the more integration capability can be achieved. The surface roughness of the membrane was measured by AFM, the micro voids and the non-contacted area were inspected by IR detector, and the bonding interface was observed by SEM. The polarization characteristics and the dielectric characteristics of the PT layer were measured, too.

• Journal of the Korean Society for Nondestructive Testing
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• v.10 no.1
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• pp.10-17
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• 1990

Recently, object recognition ultrasonic sensor is being used with automatization of industrial machine. Points which characterize the object can be deleted by measuring the propagation time of ultrasonic impulse and azimuth which gives its maximum amplitude, and from these points shape, position and orientation of the object are deduced. A new measuring method is adopted, where the distance to the object is calculated by sound reflection time which is measured from O-cross point of sound wave, and azimuth is measured by angle indicating maximum amplitude. The measuring accuracy of 1.0mm for distance and $0.5-2^{\circ}$ for azimuth have been accomplished. By rotational scanning of sensor the characteristic point of an object can be known and it gives the information of its shape, position and orientation. Experimental results showed that the object of some complicated shape can be recognized, which suggest its applicability to robot.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.55-62
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• 2019

The stereo geometry establishment based on the precise sensor modeling is prerequisite for accurate stereo data processing. Ground control points are generally required for the accurate sensor modeling though it is not possible over the area where the accessibility is limited or reference data is not available. For the areas, the relative orientation should be carried out to improve the geometric consistency between the stereo data though it does not improve the absolute positional accuracy. The relative orientation requires conjugate points that are well distributed over the entire image region. Therefore the automatic conjugate point extraction is required because the manual operation is labor-intensive. In this study, we applied the method consisting of the key point extraction, the search space minimization based on the epipolar line, and the rigorous outlier detection based on the RPCs (Rational Polynomial Coefficients) bias compensation modeling. We tested different parameters of window sizes for Kompsat-2 across track stereo data and analyzed the RPCs precision after the bias compensation for the cases whether the epipolar line information is used or not. The experimental results showed that matching outliers were inevitable for the different matching parameterization but they were successfully detected and removed with the rigorous method for sub-pixel level of stereo RPCs precision.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.410-413
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• 1993

Chamferless peg-in-hole process of the cylindrical type parts using force/torque sensor and vision sensor is analyzed and simulated in this paper. Peg-in-hole process is classified to the normal mode (only position error) and tilted mode(position and orientation error). The tilted mode is sub-classified to the small and the big tilted mode according to the relative orientation error. Since the big tilted node happened very rare, most papers dealt with only the normal or the small tilted mode. But the most errors of the peg-in-hole process happened in the big tilted mode. This problem is analyzed and simulated in this paper using the force/torque sensor and vision senor. In the normal mode, fuzzy logic is introduced to combine the data of the force/torque sensor and vision sensor. Also the whole processing algorithms and simulations are presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1165-1171
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• 2022

Human behavior recognition using an accelerometer has been applied to various fields. As smartphones have become used commonly, a method for human behavior recognition using the acceleration sensor built into the smartphone is being studied. In the case of the elderly, falling often leads to serious injuries, and falls are one of the major causes of accidents at construction fields. In this article, we proposed recognition method for human falling direction using built-in acceleration sensor and orientation sensor in the smartphone. In the past, it was a common method to use the magnitude of the acceleration vector to recognize human behavior. These days, deep learning has been actively studied and applied to various areas. In this article, we propose a method for recognizing the direction of human falling by applying the deep learning multilayer technique, which has been widely used recently.

• Journal of Mechanical Science and Technology
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• v.20 no.4
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• pp.505-512
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• 2006

This paper presents an integrated multifunctional sensor based on MEMS technology, which can be used or embedded in mobile devices for environmental monitoring. An absolute pressure sensor, a temperature sensor and a humidity sensor are integrated in one silicon chip of which the size is $5mm\times5mm$. The pressure sensor uses a bulk-micromachined diaphragm structure with the piezoresistors. For temperature sensing, a silicon temperature sensor based on the spreading-resistance principle is designed and fabricated. The humidity sensor is a capacitive humidity sensor which has the polyimide film and interdigitated capacitance electrodes. The different piezoresistive orientation is used for the pressure and temperature sensor to avoid the interference between sensors. Each sensor shows good sensor characteristics except for the humidity sensor. However, the linearity and hysteresis of the humidity sensor can be improved by selecting the proper polymer materials and structures.