• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.597-599
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• 2006

In this paper, we propose an artificial intelligence method to compensate the nonlinearity error which occurs in the heterodyne laser interferometer. Some superior properties such as long measurement range, ultra-precise resolution and various system set-up lead the laser interferometer to be a practical displacement measurement apparatus in various industry and research area. In ultra-precise measurement such as nanometer or subnanometer scale, however, the accuracy is limited by the nonlinearity error caused by the optical parts. The feedforward neural network trained by back-propagation with a capacitive sensor as a reference signal minimizes the nonlinearity error and we demonstrate the effectiveness of our proppsed algorithm through some experimental results.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.234-236
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• 2006

Because of its long measurement range and ultra-precise resolution. the heterodyne laser interferometer systems are very common in various industry area such as semiconductor manufacturing. However the periodical nonlinearity property caused from frequency mixing is an obstacle to improve the high measurement accuracy in nanometer scale. In this paper to minimize the effect of nonlinearity, we propose an adaptive nonlinearity compensation algorithm. We first compute compensation parameters using least square (LS) with the capacitance displacement sensor as a reference input. We then update the parameters with recursive LS (RLS) while the values are optimized to modify the elliptical phase into circular one. Through comparison with some experimental results of laser system, we demonstrate the effectiveness of our proposed algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.257-258
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• 2006

This paper presents the displacement sensor based on astigmatic method that has a small measurement range. The sensor has the characteristic that the measuring range is changed easily by exchanging a objective lens or distance between a objective lens and a collimator lens. The measuring range and resolution is evaluated by a laser interferometer.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.265-275
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• 2015

This paper describes extraction methods of five different types of geometrical features (line, arc, corner, polynomial curve, NURBS curve) from the obtained raw data by using a two-dimensional laser range finder (LRF). Natural features with their covariance matrices play a key role in the realization of feature-based simultaneous localization and mapping (SLAM), which can be used to represent the environment and correct the pose of mobile robot. The covariance matrices of these geometrical features are derived in detail based on the raw sensor data and the uncertainty of LRF. Several comparison are made and discussed to highlight the advantages and drawbacks of each type of geometrical feature. Finally, the extracted features from raw sensor data obtained by using a LRF in an indoor environment are used to validate the proposed extraction methods.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.330-332
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• 2006

A short distance laser range detector was developed on digital circuit. The circuit changed the analog circuit to digital circuit as possible as. The currently available laser range circuit one uses analog circuit mainly. But this ranger design targeted mass production with digital reporting function. So digital circuits replaced the analog circuit except amplifier and remained minor circuits those are hard to replace with digital circuit. The simulation shows that it is possible to make a reasonable distance measuring circuit on a digital circuit for very low price compare to analog circuit one.

• Journal of Mechanical Science and Technology
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• v.17 no.1
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• pp.139-145
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• 2003

Diode laser sensor is conducted to measure the gas temperature in the liquid-gas 2-phase counter flow flame. C$\_$10/H/ sub 22/ and city gas were used as liquid fuel and gas fuel, respectively. Two vibrational overtones of H$_2$O were selected and measurements were carried out in the spray flame region stabilized the above gaseous premixed flame. The path-averaged temperature measurement using diode laser absorption method succeeded in the liquid fuel combustion environment regardless of droplets of wide range diameter. The path-averaged temperature measured in the post flame of liquid-gas 2-phase counter flow flame showed qualitative reliable results. The successful demonstration of time series temperature measurement in the liquid-gas 2-phase counter flow flame gave us motivation of trying to establish the effective control system in practical combustion system. These results demonstrated the ability of real-time feedback from combustor inside using the non-intrusive measurement as well as the possibility of application to practical combustion system. Failure case due to influence of spray flame was also discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.803-810
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• 2016

This paper presents a study of localization methods based on particle filter using 2D laser sensor measurements and road feature map information, for autonomous vehicles. In order to navigate in an urban environment, an autonomous vehicle should be able to estimate the location of the ego-vehicle with reasonable accuracy. In this study, road features such as curbs and road markings are detected to construct a grid-based feature map using 2D laser range finder measurements. Then, we describe a particle filter-based method for accurate positional estimation of the autonomous vehicle in real-time. Finally, the performance of the proposed method is verified through real road driving experiments, in comparison with accurate DGPS data as a reference.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.253-264
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• 1999

Most autonomous mobile robots view only things in front of them, and as a result, they may collide with objects moving from the side or behind. To overcome this problem. an Active Omni-directional Range Sensor System has been built that can obtain an omni-directional range data through the use of a laser conic plane and a conic mirror. Also, mobile robot has to know its current location and heading angle by itself as accurately as possible to successfully navigate in real environments. To achieve this capability, we propose a self-localization algorithm of a mobile robot using an active omni-directional range sensor in an unknown environment. The proposed algorithm estimates the current position and head angle of a mobile robot by a registration of the range data obtained at two positions, current and previous. To show the effectiveness of the proposed algorithm, a series of simulations was conducted and the results show that the proposed algorithm is very efficient, and can be utilized for self-localization of a mobile robot in an unknown environment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.121-126
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• 2002

This paper introduces a method that can get information for the movement of a spreader and skew in order to drive ALS(Automatic Landing System) in the crane used at the harbor. Some methods that use 3D laser scanner sensor or laser range finder to obtain the information in ALS are used presently. But these have some defects respectively in economical efficiency and performance. Therefore, to recover these defects, we propose a method acquiring the information for the movement of a spreader and skew using CCD camera for image processing and laser range finder

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.123.1-123
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• 2001

For Autonomous navigation of the mobile robots, the robots' capability to recognize 3D environment is necessary. In this paper, an on-line 3D map building method for autonomous mobile robots is proposed. To get range data on the environment, we use an sensor system which is composed of a structured light and a CCD camera based on optimal triangulation. The structured laser is projected as a horizontal strip on the scene. The sensor system can rotate $\pm$ $30{\Circ}$ with a goniometer. Scanning the system, we get the laser strip image for the environments and update planes composing the environment by some image processing steps. From the laser strip on the captured image, we find a center point of each column, and make line segments through blobbing these center poings. Then, the planes of the environments are updated. These steps are done on-line in scanning phase. With the proposed method, we can efficiently get a 3D map about the structured environment.