• Smart Structures and Systems
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• 제3권2호
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• pp.201-217
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• 2007

An active damage detection technique is introduced to locate damage in an isotropic plate using Lamb waves. This technique uses a time-domain energy model of Lamb waves in plates that the wave amplitude inversely decays with the propagation distance along a ray direction. Accordingly the damage localization is formulated as a least-squares problem to minimize an error function between the model and the measured data. An active sensing system with integrated actuators/sensors is controlled to excite/receive $A_0$ mode of Lamb waves in the plate. Scattered wave signals from the damage can be obtained by subtracting the baseline signal of the undamaged plate from the recorded signal of the damaged plate. In the experimental study, after collecting the scattered wave signals, a discrete wavelet transform (DWT) is employed to extract the first scattered wave pack from the damage, then an iterative method is derived to solve the least-squares problem for locating the damage. Since this method does not rely on time-of-flight but wave energy measurement, it is more robust, reliable, and noise-tolerant. Both numerical and experimental examples are performed to verify the efficiency and accuracy of the method, and the results demonstrate that the estimated damage position stably converges to the targeted damage.

• 한국정밀공학회지
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• 제30권2호
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• pp.177-184
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• 2013

This paper proposes an enhanced Simultaneous Localization and Mapping (SLAM) algorithm based on matching laser image and Extended Kalman Filter (EKF). In general, laser information is one of the most efficient data for localization of mobile robots and is more accurate than encoder data. For localization of a mobile robot, moving distance information of a robot is often obtained by encoders and distance information from the robot to landmarks is estimated by various sensors. Though encoder has high resolution, it is difficult to estimate current position of a robot precisely because of encoder error caused by slip and backlash of wheels. In this paper, the position and angle of the robot are estimated by comparing laser images obtained from laser scanner with high accuracy. In addition, Speeded Up Robust Features (SURF) is used for extracting feature points at previous laser image and current laser image by comparing feature points. As a result, the moving distance and heading angle are obtained based on information of available points. The experimental results using the proposed laser slam algorithm show effectiveness for the SLAM of robot.

• 제어로봇시스템학회논문지
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• 제12권10호
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• pp.968-974
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• 2006

We are moving into the era of ubiquitous computing. Ubiquitous Sensor Network (USN) is a base of such computing paradigm, where recognizing the identification and the position of objects is important. For the object identification, RFID tags are commonly used. For the object positioning, use of sensors such as laser and ultrasonic scanners is popular. Recently, there have been a few attempts to apply RFID technology in robot localization by replacing the sensors with RFID readers to achieve simpler and unified USN settings. However, RFID does not provide enough sensing accuracy for some USN applications such as robot navigation, mainly because of its inaccuracy in distance measurements. In this paper, we describe our approach on achieving accurate navigation using RFID. We solely rely on RFID mechanism for the localization by providing coordinate information through RFID tag installed floors. With the accurate positional information stored in the RFID tag, we complement coordinate errors accumulated during the wheel based robot navigation. We especially focus on how to distribute RFID tags (tag pattern) and how many to place (tag granularity) on the RFID tag-floor. To determine efficient tag granularities and tag patterns, we developed a simulation program. We define the error in navigation and use it to compare the effectiveness of the navigation. We analyze the simulation results to determine the efficient granularities and tag arrangement patterns that can improve the effectiveness of RFID navigation in general.

• 한국컴퓨터정보학회논문지
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• 제12권5호
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• pp.155-162
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• 2007

스마트한 홈서비스를 제공하기 위해서는 가전기기를 제어하기위한 미들웨어 기술과 사용자의 위치를 기반 서비스를 위한 사용자의 위치 정보가 중요하다. 기존에 연구되는 초음파 및 전파를 사용한 기술은 장애물 및 주변 환경의 영향을 많이 받는다. 따라서 본 논문에서는 사용자의 위치 추정에 장애물 등의 영향을 받지 않는 관성센서를 사용하고, RFID를 사용하여 초기 위치를 설정하는 기법을 제안한다. 이 기법을 사용하여 초기 위치를 상대 좌표가 아닌 실제 좌표로 바로 할당할 수 있게 하여 이를 통해 관성센서의 단점인 오차누적 문제를 해결한다. 본 논문에서 제안하는 시스템은 서비스제공 및 확장성을 위한 미들웨어와 미들웨어 상위계층에서 동작하는 사용자 위치 추정시스템, 그리고 사용자의 위치계산을 위한 데이터를 수집하는 관성센서 및 RFID Reader로 구성한다. 또한 스마트 홈 환경에서 본 논문에서 제안한 시스템이 장애물의 영향을 받지 않고 동작하는 것을 확인한다.

• ETRI Journal
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• 제37권4호
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• pp.824-832
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• 2015

Heart sounds are the main obstacle in lung sound analysis. To tackle this obstacle, we propose a diagnosis algorithm that uses singular spectrum analysis (SSA) and frequency features of heart and lung sounds. In particular, we introduce a frequency coefficient that shows the frequency difference between heart and lung sounds. The proposed algorithm is applied to a synthetic mixture of heart and lung sounds. The results show that heart sounds can be extracted successfully and localizations for the first and second heart sounds are remarkably performed. An error analysis of the localization results shows that the proposed algorithm has fewer errors compared to the SSA method, which is one of the most powerful methods in the localization of heart sounds. The presented algorithm is also applied in the cases of recorded respiratory sounds from the chest walls of five healthy subjects. The efficiency of the algorithm in extracting heart sounds from the recorded breathing sounds is verified with power spectral density evaluations and listening. Most studies have used only normal respiratory sounds, whereas we additionally use abnormal breathing sounds to validate the strength of our achievements.

• International Journal of Control, Automation, and Systems
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• 제5권3호
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• pp.251-268
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• 2007

A Gaussian sum filter (GSF) is proposed in this paper on simultaneous localization and mapping (SLAM) for mobile robot navigation. In particular, the SLAM problem is tackled here for cases when only bearing measurements are available. Within the stochastic mapping framework using an extended Kalman filter (EKF), a Gaussian probability density function (pdf) is assumed to describe the range-and-bearing sensor noise. In the case of a bearing-only sensor, a sum of weighted Gaussians is used to represent the non-Gaussian robot-landmark range uncertainty, resulting in a bank of EKFs for estimation of the robot and landmark locations. In our approach, the Gaussian parameters are designed on the basis of minimizing the representation error. The computational complexity of the GSF is reduced by applying the sequential probability ratio test (SPRT) to remove under-performing EKFs. Extensive experimental results are included to demonstrate the effectiveness and efficiency of the proposed techniques.

• 로봇학회논문지
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• 제14권1호
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• pp.65-73
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• 2019

In this paper, we propose an algorithm that estimates the location of lunar rover using IMU and vision system instead of the dead-reckoning method using IMU and encoder, which is difficult to estimate the exact distance due to the accumulated error and slip. First, in the lunar environment, magnetic fields are not uniform, unlike the Earth, so only acceleration and gyro sensor data were used for the localization. These data were applied to extended kalman filter to estimate Roll, Pitch, Yaw Euler angles of the exploration rover. Also, the lunar module has special color which can not be seen in the lunar environment. Therefore, the lunar module were correctly recognized by applying the HSV color filter to the stereo image taken by lunar rover. Then, the distance between the exploration rover and the lunar module was estimated through SIFT feature point matching algorithm and geometry. Finally, the estimated Euler angles and distances were used to estimate the current position of the rover from the lunar module. The performance of the proposed algorithm was been compared to the conventional algorithm to show the superiority of the proposed algorithm.

• 한국인터넷방송통신학회논문지
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• 제11권1호
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• pp.15-21
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• 2011

무선 센서 네트워크(WSN)에서 센서 노드의 위치 추정 기술 중 거리 기반의 위치 추정 기술은 거리 측정에 따라 센서 노드의 위치 추정의 정확성이 달라진다. 거리 기반의 위치 추정 기술에서 거리를 측정하는 많은 기술 중에 추가적인 장비 없이 쉽게 구현이 가능한 기술 중 하나는 수신 신호 세기이다. 그러나 수신신호세기 기반의 위치 추정 기법은 몇 가지 문제점을 고려해야 한다. 하나는 수신된 신호는 채널 환경에서 페이딩, 쉐도잉 그리고 장애물 등으로 인해서 거리 추정의 오차가 생긴다. 이로 인해서 센서 노드의 위치 추정의 정확성은 낮게 된다. 또 다른 하나는 거리 기반의 위치 추정 기술은 대부분 센서 노드에 의해서 자신의 위치를 추정한다는 것이다. 하지만 센서 노드의 한정된 배터리 용량 때문에 무선 센서 네트워크의 동작 시간이 감소하게 된다. 반면에 비콘 노드는 센서 노드보다 처리 능력과 배터리 용량이 더 높기 때문에 비콘 노드 기반 위치 추정 기법은 무선 센서 네트워크의 동작 시간을 연장 할 수 있다. 본 논문에서는 비콘 노드에서 수신 신호 세기와 전력손실지수 추정을 활용하여 센서 노드의 위치를 추정하는 알고리즘을 제안함으로써 위의 문제점을 극복한다. 시뮬레이션을 통해서 제안한 기법을 검증한다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1999년도 학술대회
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• pp.243-248
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• 1999

MPEG-4에서 오류강인성(Error Resilience)를 위한 한 방법으로 Resynchronization Markers(RM)을 사용한다. 한 프레임이 시작될 때 StartCode를 사용하여 동기를 맞추고 몇 개의MacroBlock을 encoding한 후 일정한 비트수(Threshold 값)가 지나면 재동기 마커 표시하여 재동기를 한다. 이렇게 하므로서 한 프레임 내에서 어떤 부분에 에러가 발생하더라도 그 에러가 속해있는 비디오패킷(재동기 마커와 재동기 마커사이의 Data)만을 버리거나 RVLC(ReversibleVariable Length Codes)를 사용하여 Data를 복원할 수 있다. 그러나 만약 재동기 마커에 에러가 발생하거나 에러의 전파로 인하여 재동기 마커를 인식 못한다면 두 개 이상의 패킷이 손실되거나RVLC를 사용한 데이터 복원을 할 수 없다. 본 논문에서는 이를 막기위해 디코딩 전에 Prescan을 통해서 재동기 마커의 위치를 탐지하고 에러가 생긴 재동기 마커를 복원하는 방법을 제안하였다. 그리고 bitrate에 따른 MB(MacroBlock)의 크기와 비디오 패킷 크기(재동기 마커와 재동기 마커간의 거리)를 분석하여 재동기 마커를 찾는 루틴에 적용하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.560-562
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• 2006

In this paper, Correct problem in dead reckoning system and proposed about position error revision techniques of mobile robot to use RFID tag for position awareness. With the dead reckoning system, as the accumulation of error are unavoidable because of accumulation of informations as the time passage, so it is impossible to get correct information about posture, including torrent direction, movement distance, etc. As one of compensation method, the suggested method is that after selecting special area (corridor), compensate absolute location information by arranging two line of RFID tag along two side of corridor. Through this suggested method, it could be used when robot wants to move in limited areas.