• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.211-216
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• 1997

The mode localization phenomenon in non-periodic multispan beam is theoretically investigated. When localization occurs, the free vibration amplitude of a normal mode becomes confined to a local region of the structure. It is well known that the weakly coupled periodic structures are sensitive to certain types of periodicity-breaking disorder, resulting in the mode localization. The results of this study indicate that the mode localization occurs also in nonperiodic structures and the degrees of mode localization of some modes are very sensitive to system parameters. Free vibration analysis of simply supported two-span beams of arbitrary span lengths is performed. Degrees of mode localization and their sensitivities to system parameters are appraised by considering the characteristic graph and the structural line defined in this study first.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.237-240
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• 2000

We have proposed a simple method based on IIR filters for realizing sound image localization. How-ever the nonlinearity of phase characteristics of the IIR filters, which are used for sound image localization, cause decrease of the localization accuracy. In this paper we investigate the influence of phase characteristics on the sound localization. Head-related transfer functions (HRTFs) of a dummy-head are approximated by the IIR filter. We carried out sound image localization experiment with 2-loudspeaker reproduction using the approximated HRTFs. Then the errors which obtained from experiments were compared with the theoretical values which were estimated from the phase shifts of the IIR filters. As a result there was little influence of the nonlinear phase characteristics of the IIR fitters in the localization on the horizontal plane.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.203-210
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• 2009

The problem of outdoor localization can be practically solved by GPS. However, GPS is not perfect and some areas of outdoor navigation should consider other solutions. This research deals with outdoor localization using an elevation map without GPS. This paper proposes a novel feature, elevation moment of inertia (EMOI), which represents the distribution of elevation as a function of distance from a robot in the elevation map. Each cell of an elevation map has its own EMOI, and outdoor localization can be performed by matching EMOIs obtained from the robot and the pre-given elevation map. The experiments and simulations show that the proposed EMOI can be usefully exploited for outdoor localization with an elevation map and this feature can be easily applied to other probabilistic approaches such as Markov localization method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.30 no.1
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• pp.87-95
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• 2016

Recently, the interests of the precise localization are rapidly increasing, which are linked to IoT(Internet of Things) sensors. The precise localization in indoor environment can be utilized in navigation, security, anti-collision, and various location based services etc. However, conventional positioning sensors, such as PIR, ultrasonic, microwave etc. are vulnerable to weather or insensitive to direction of subject movement or low precision performance. In this paper we implement a UWB-IR localization system for long distance and high-precision localization, which is not affected by temperature, light and weather. The proposed system was divided and designed by H/W, Antenna, S/W parts, each of which was designed based on an accurate analysis and simulation. As a result, we can implemented and verified UWB IR system with precise localization performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.551-560
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• 2010

In this paper, we suggest a localization method of factors affecting the accuracy of Air-to-Ground weapon delivery. The proposed method, called FBEL(Factor-Based Error Localization), is based on the fault localization technique widely utilized in the realm of software engineering field. FBEL localizes the major factors affecting the performance of weapon delivery. To analyze the effectiveness and the applicability of FBEL, we applied FBEL to real firing data and got the major factors caused the errors. We expect that the method could contribute to improve the quality of weapon delivery system. We also expect that it may aid improvement of pilot capability greatly, if it is applied to pilot firing training.

• Journal of Mechanical Science and Technology
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• v.19 no.7
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• pp.1405-1413
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• 2005

Malfunctions or critical fatigue problems often occur in mistuned periodic structural systems since their vibration responses may become much larger than those of perfectly tuned periodic systems. These are called vibration localization phenomena and it is of great importance to accurately predict the localization phenomena for safe and reliable designs of the periodic structural systems. In this study, a simple discrete system which represents periodic structural systems is employed to analyze the vibration localization phenomena. The statistical effects of mistuning, stiffness coupling, and damping on the vibration localization phenomena are investigated through Monte Carlo simulation. It is found that the probability of vibration localization was significantly influenced by the statistical properties except the standard deviation of coupling stiffness.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.357-361
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• 2007

This paper presents a multi-robot localization based on Bayesian Multidimensional Scaling (BMDS). We propose a robust MDS to handle both the incomplete and noisy data, which is applied to solve the multi-robot localization problem. To deal with the incomplete data, we use the Nystr${\ddot{o}}$m approximation which approximates the full distance matrix. To deal with the uncertainty, we formulate a Bayesian framework for MDS which finds the posterior of coordinates of objects by means of statistical inference. We not only verify the performance of MDS-based multi-robot localization by computer simulations, but also implement a real world localization of multi-robot team. Using extensive empirical results, we show that the accuracy of the proposed method is almost similar to that of Monte Carlo Localization(MCL).

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.49-54
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• 2021

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.110-117
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• 2022

This paper describes a localization algorithm utilizing relative observations for multiple autonomous underwater vehicles (Multiple-AUVs). In order to maximize the efficiency of operation and mission accomplishment and to prevent problems such as collision and interference, the locations and directions of Multiple-AUVs must be precisely estimated. To estimate the locations and directions, we designed a localization algorithm utilizing relative observations and verified it with simulations based on sensor data sets acquired through real sea experiments. Also, an optimal combination of relative observation information for efficient localization is figured out through combining various relative observations. The proposed method shows improved localization results compared to those only using the navigation algorithm. The performance of localization is improved up to 58% depending on the combination of relative observations.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.44-47
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• 1997

Building a reliable mobile robot - one that can navigate without failures for long periods of time - requires that the uncertainty which results from control and sensing is bounded. This paper proposes a new mobile robot localization method using artificial landmarks. For a mobile robot localization, the proposed method uses a camera calibration(only extrinsic parameters). We use the FANUC arc mate to estimate the posture error, and the result shows that the position error is less than 1 cm and the orientation error less than 1 degrees.