• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.443-451
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• 2020

A futuristic locomotion system called Hyperloop is projected for driving at ulta-high speed, levitated in the tube. In hyperloop localization of pods on the linear synchronous motor is essential for pod driving. precision localization is required for acceleration and deceleration of pods driving at speed above 1,000km/h, and also required for adjusting the pod speed driving at this very-high speed to maintain inter-vehicle distance. In this work, a new scale of localization is challenged by modified laser surface velocimeter. In acceleration the speed of a virtual pod is calculated along its displacement measured by laser reflection. Under the requirement of precise localization of the pod driving at ultra-high speed, a displacement measurement device, which detects the difference in reflections from tiles passing by the pod, is developed and evaluated through performance test. Tests of pod speeds below 500km/h have showed exact localization results of the precision in centimeters, and tests of pod speeds above 500km/h have showed localization with very low error rates under 0.1%. For the measurement above 500km/h, future works would pursue the error rate converges to zero.

• Composites Research
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• v.29 no.1
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• pp.1-6
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• 2016

Low-speed impact was localized on a stiffened composite structure, using 4 FBG sensors with 100 kHz-sampling rate interrogator and devised localization algorithm. The composite specimen consists of a main spar and several stringers, and the overall size of the specimen's surface is about $0.8{\times}1.2m$. Pre-stored reference data for 247 grid locations and 36 stiffener locations are gathered and used as comparison target for a random impact signal. The proposed algorithm uses the normalized cross-correlation method to compare the similarities of the two signals; the correlation results for each sensor's signal are multiplied by others, enabling mutual compensation. 20 verification points were successfully localized with a maximum error of 43.4 mm and an average error of 17.0 mm. For the same experimental setup, the performance of the proposed method is evaluated by reducing the number of sensors. It is revealed that the mutual compensation between the sensors is most effective in the case of a two sensor combination. For the sensor combination of FBG #1 and #2, the maximum localization error was 42.5 mm, with average error of 17.4 mm.

• Journal of Korea Multimedia Society
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• v.15 no.12
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• pp.1506-1516
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• 2012

In a ship block logistics application, acquisition of locations is required in order to identify location of the ship blocks. A Smart device equipped with a GPS sensor can be used as a mobile client for a ship block logistics application. However the precision of GPS components on a commercial smart device is not high enough. Therefore, using the GPS for localization may produce significant positioning errors in a ship block logistics system. This paper proposes a method to reduce errors in measuring locations using a smart device. Based on the knowledge of how the location information is used in a ship block logistics application, and the predictability of the client's moving line based on geographical layout of a shipyard area, our proposed technique enables a better prediction of the ship blocks location. Performance evaluation shows that the proposed technique can significantly reduce the positional error.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1200-1207
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• 2017

Sensors in a smartphone can be used to measure various physical quantities. In this paper, we propose an object localization scheme in a three dimenstional using a smart phone. The proposed scheme estimates the location of an object by observing it from several different points. The direction to the target object and the locations of the observation points are collected at each observation point using the location sensor and the orientation sensor in the smartphone. Based on these observations, the proposed scheme derives three dimensional line of sight vectors and estimates the location of the target object that minimizes the estimation error. We implemented the proposed scheme on an Android smartphone and tested its performance by estimating the height of a building and characteristics of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.108-115
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• 2011

This paper describes a new sensor system for mobile robot motion estimation using stereo infrared light sources and a camera. Visibility is being applied to robotic obstacle avoidance path planning and localization. Using simple visibility computation, the environment is partitioned into many visibility sectors. Based on the recognized edges, the sector a robot belongs to is identified and this greatly reduces the search area for localization. Geometric modeling of the vision system enables the estimation of the characteristic pixel position with respect to the robot movement. Finite difference analysis is used for incremental movement and the error sources are investigated. With two characteristic points in the image such as vertices, the robot position and orientation are successfully estimated.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.445-450
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• 2009

This paper presents a new mobile robot localization method for indoor robot navigation. The method uses hexagon distributed color-coded patches on the ceiling and a camera is installed on the robot facing the ceiling to recognize these patches. The proposed "cell-coded map", with the use of only seven different kinds of color-coded landmarks distributed in hexagonal way, helps reduce the complexity of the landmark structure and the error of landmark recognition. This technique is applicable for navigation in an unlimited size of indoor space. The structure of the landmarks and the recognition method are introduced. And 2 rigid rules are also used to ensure the correctness of the recognition. Experimental results prove that the method is useful.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.994-1001
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• 2009

CSS (Chirp Spread Spectrum) specified in IEEE 802.15.4a can be used for ranging applications. In this paper, we apply the CSS to estimate the coordinates of a mobile robot. Four anchor nodes are installed at known positions and a tag node is attached to the target mobile robot. By CSS ranging, we measure the distances between each anchor and the tag node. Based on the measured distances, the coordinates of the mobile robot can be calculated by the method of trilateration. However the calculated coordinates are not accurate because of the errors of the measured distances. Therefore we propose an algorithm for reducing the effect of the errors. The proposed algorithm is executed with the extended Kalman filter. Through localization experiments, we show the performance of the proposed algorithm and the accuracy of the estimated position.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.767-773
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• 2008

This paper presents a localization system based on the use of electric compass and tracking IR light source. Digital RGB(Red, Green, Blue)signal of digital CMOS Camera is sent to CPLD which converts the color image to binary image at 30 frames per second. CMOS camera has IR filter and UV filter in front of CMOS cell. The filters cut off above 720nm light source. Binary output data of CPLD is sent to DSP that rapidly tracks the IR light source by moving Camera tilt DC motor. At a robot toward north, electric compass signals and IR light source angles which are used for calculating the data of the location system. Because geomagnetic field is linear in local position, this location system is possible. Finally, it is shown that position error is within ${\pm}1.3cm$ in this system.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1E
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• pp.8-13
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• 2006

In this paper, an Optimized Ambisonic Panning Algorithm (OAPA) which reduces sound localization error, is proposed. In the conventional Ambisonic Panning Algorithm (APA), sound localization is usually different from the panning angle, especially when listeners are not in an ideal listening position, because of low signal separation among other channels. To overcome this problem, an OAPA using window functions is proposed. A proper window function can be verified, comprising of higher harmonic components than 2M+1 and improved DPC and channel separation. Analysis results demonstrate that the proposed method results in higher signal separation among other channels and lower sound localization errors than the conventional APA.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.4
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• pp.437-445
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• 2009

In this paper, we present the performance of the LOB(line of bearing) - based emitter localization algorithm. The linear LSE(least-squared error) algorithm, nonlinear LSE algorithm and Stansfield algorithm are considered. In addition, we focus on the performance improvement of the weighted estimation compared with the unweighted estimation. Each estimation algorithm is briefly introduced, and the performance of the algorithm is illustrated using the numerical results.