The localization of the robot is one of the most important factors of navigating mobile robots. The use of featured information of landmarks is one approach to estimate the location of the robot. This approach can be classified into two categories: the natural-landmark-based and artificial-landmark-based approach. Natural landmarks are suitable for any environment, but they may not be sufficient for localization in the less featured or dynamic environment. On the other hand, artificial landmarks may generate shaded areas due to space constraints. In order to improve these disadvantages, this paper presents a novel development of the localization system by using artificial and natural-landmarks-based approach on a topological map. The proposed localization system can recognize far or near landmarks without any distortion by using landmark tracking system based on top-view image transform. The camera is rotated by distance of landmark. The experiment shows a result of performing position recognition without shading section by applying the proposed system with a small number of artificial landmarks in the mobile robot.

For the underwater localization, acoustic sensor systems are widely used due to greater penetration properties of acoustic signals in underwater environments. On the other hand, the good penetration property causes multipath and interference effects in structured environment too. To overcome this demerit, a localization method using the attenuation of electro-magnetic(EM) waves was proposed in several literatures, in which distance estimation and 2D-localization experiments show remarkable results. However, in 3D-localization application, the estimation difficulties increase due to the nonuniform (doughnut like) radiation pattern of an omni-directional antenna related to the depth direction. For solving this problem, we added a depth sensor for improving underwater 3D-localization with the EM wave method. A micro scale pressure sensor is located in the mobile node antenna, and the depth data from the pressure sensor is calibrated by the curve fitting algorithm. We adapted the depth(z) data to 3D EM wave pattern model for the error reduction of the localization. Finally, some experiments were executed for 3D localization with the fast calculation and less errors.

A rectangle-based relative localization method is proposed for a mobile robot based on a novel geometric formulation. In an artificial environment where a mobile robot navigates, rectangular shapes are ubiquitous. When a scene rectangle is captured using a camera attached to a mobile robot, localization can be performed and described in the relative coordinates of the scene rectangle. Especially, our method works with a single image for a scene rectangle whose aspect ratio is not known. Moreover, a camera calibration is unnecessary with an assumption of the pinhole camera model. The proposed method is largely based on the theory of coupled line cameras (CLC), which provides a basis for efficient computation with analytic solutions and intuitive geometric interpretation. We introduce the fundamentals of CLC and describe the proposed method with some experimental results in simulation environment.

This paper proposes an underwater localization algorithm using probabilistic object recognition. It is organized as follows; 1) recognizing artificial objects using imaging sonar, and 2) localizing the recognized objects and the vehicle using EKF(Extended Kalman Filter) based SLAM. For this purpose, we develop artificial landmarks to be recognized even under the unstable sonar images induced by noise. Moreover, a probabilistic recognition framework is proposed. In this way, the distance and bearing of the recognized artificial landmarks are acquired to perform the localization of the underwater vehicle. Using the recognized objects, EKF-based SLAM is carried out and results in a path of the underwater vehicle and the location of landmarks. The proposed localization algorithm is verified by experiments in a basin.

Acoustic signal is crucial for the autonomous navigation of underwater vehicles. For this purpose, this paper presents a method of acoustic source localization. The proposed method is based on the probabilistic estimation of time delay of acoustic signals received by two hydrophones. Using Bayesian update process, the proposed method can provide reliable estimation of direction angle of the acoustic source. The acquired direction information is used to estimate the location of the acoustic source. By accumulating direction information from various vehicle locations, the acoustic source localization is achieved using extended Kalman filter. The proposed method can provide a reliable estimation of the direction and location of the acoustic source, even under for a noisy acoustic signal. Experimental results demonstrate the performance of the proposed acoustic source localization method in a real sea environment.

Through Estimation of stress distribution, both value and location of the maximum stress can be found. and the maximum stress is very important indicator for structural safety evaluation. In this connection, a lot of studies to estimate stress distributions are conducted. But studies on the optimal number and location of measurement points are few. So, In this study, the effects of the number and location of measurement points on the estimation stress distribution for the steel beam structure using motion capture system and cubic smoothing spline interpolation are researched.

This paper proposes a novel upward-looking camera-based global localization using a ceiling image map. The ceiling images obtained through the SLAM process are integrated into the ceiling image map using a particle filter. Global localization is performed by matching the ceiling image map with the current ceiling image using SURF keypoint correspondences. The robot pose is then estimated by the coordinate transformation from the ceiling image map to the global coordinate system. A series of experiments show that the proposed method is robust in real environments.

Localization is one of the essential tasks necessary to achieve autonomous navigation of a mobile robot. One such localization technique, Monte Carlo Localization (MCL) is often applied to a digital surface model. However, there are differences between range data from laser rangefinders and the data predicted using a map. In this study, commonly observed from air and ground (COAG) features and candidate selection based on the shape of sensor data are incorporated to improve localization accuracy. COAG features are used to classify points consistent with both the range sensor data and the predicted data, and the sample candidates are classified according to their shape constructed from sensor data. Comparisons of local tracking and global localization accuracy show the improved accuracy of the proposed method over conventional methods.

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.

This paper verifies the performance of Extended Kalman Filter(EKF) and MCL(Monte Carlo Localization) approach to localization of an underwater vehicle through experiments. Especially, the experiments use acoustic range sensor whose measurement accuracy and uncertainty is not yet proved. Along with localization, the experiment also discloses the uncertainty features of the range measurement such as bias and variance. The proposed localization method rejects outlier range data and the experiment shows that outlier rejection improves localization performance. It is as expected that the proposed method doesn’t yield as precise location as those methods which use high priced DVL(Doppler Velocity Log), IMU(Inertial Measurement Unit), and high accuracy range sensors. However, it is noticeable that the proposed method can achieve the accuracy which is affordable for correction of accumulated dead reckoning error, even though it uses only range data of low reliability and accuracy.

The purpose of this study is to provide the damage detection method using wavelet transformation. The damage location index through the mode shape of damaged structure is formulated theoretically and applied to numerical analysis model of MATLAB. The shacking table test on reduced 3 story shear building is performed and the dynamic response signal is wavelet transformed. The result of damage detection using wavelet transformed signal is compared to that of non wavelet transformed signal to verify the applicability of the wavelet transformation in damage detection.

The purpose of this study is to present the damage detection method on shear building structures by mode shape. The damage location index using 1st mode shape is observed theoretically to find out damage location. The damage detection method is applied to numerical analysis model such as MATLAB and MIDAS GENw for the verification. Finally the shacking table test on 3 story shear building is performed for the examination of the damage detection method.

As the building maintenance and safety management have recently been brought to attention, the utilization of non-destructive testing methods for internal inspection of concretes is increasing. Non-destructive testing methods, unlike typical destructive testing methods that deconstruct or cut the building in case of issues such as pores, heterogeneous material, cracks or any such equivalent issues inside/outside the building, refer to the testing methods for pores, heterogeneous material, or defectiveness occurring in the specimen without changes or destruction of internal structure using ultrasound, radiation, electromagnetism, fluid, heat, or light. In this study, among such non-destructive testing methods, the impact echo method was used for an experiment to estimate the steel rebar location and thickness in the concrete mock member.

In this paper, a high precision outdoor positioning system is newly proposed using multiple GPS receivers based on the Extended Kalman Filter (EKF). Typically, the GPS signal has the instantaneous errors that degrade the positioning seriously. Using the multiple GPS receivers instead of an expensive DGPS receiver, the positioning reliability and accuracy are improved in this research as a low cost solution. To incorporate the small displacement, an INS data have been tightly coupled to the GPS data, which has the inherit disadvantage of the cumulative error occurring over time. To achieve a stabilized and accurate positioning system, the multiple GPS receiver data are fused with the INS data through the EKF process. Through real navigation experiments of an outdoor mobile robot, the performance of the proposed system has been verified to be accurate comparable to DGPS system with a lower cost.

손상된 구조물의 동적응답신호를 역해석함으로써 손상위치와 정도를 파악할 수 있다. 일반적으로 손상 전 후 고유진동수의 변화로부터 강성의 감소량을 구하고, 모드형상의 변화로부터 손상위치를 파악할 수 있다. 토목구조물의 경우 동적 응답신호로부터 손상을 검출코자 하는 연구가 상당히 진행되었으며 실용화 되었다. 그러나 건축구조물의 경우 몇 가지 문제로 인하여 이에 대한 연구가 활발히 진행되지 못하고 있다. 본 연구에서는 모드형상을 이용한 전단형 건물의 손상위치 추적방안을 제시 하고자 한다. 전단형 건물의 손상 전 후 1차 모드강성의 차이를 이용한 손상위치 추적지수를 이론적으로 고찰하였으며, 이를 Matlab 또는 MIDAS GENw와 같은 수치해석모델에 적용함으로써 손상위치추적기법의 타당성을 검증하였다. 또한 소형 진동대 실험을 수행하고 실측된 동적응답신호를 이용하여 손상위치를 추적함으로써 실구조물에 대한 적용성을 검토하였다. 진동대 실험결과 층강성이 25% 감소할 때 1차 모드 진동수는 12%증가 하였으며, 손상위치 지수는 손상 층에서 마이너스 값을 나타내었다.

Due to the low localization accuracy and the requirement of special infrastructure, current LBS(Localization Based Service) is limited to show P.O.I.(Point of Interest) nearby. Improvement of IMU(Inertial Measurement Unit) based deadreckoning is presented in this paper. Additional sensors such as the magnetic compass and magnetic flux sensors are used as well as the accelerometer and the gyro for getting more information of movement. Based on the pedestrian movement, appropriate sensor information is selected and the complementary filter is used in order to enhance the accuracy of the localization.

This paper proposes particle filter(PF) method using acoustic signal for localization of an underwater robot. The method uses time of arrival(TOA) or time difference of arrival(TDOA) of acoustic signals from beacons whose locations are known. An experiment in towing tank uses TOA information. Simulation uses TDOA information and it reveals dependency of the localization performance on the uncertainty of robot motion and senor data. Also, comparison of the PF method with the least squares method of spherical interpolation(SI) and spherical intersection(SX) is provided. Since PF uses TOA or TDOA which comes from measurement of external information as well as internal motion information, its estimation is more accurate and robust to the sensor and motion uncertainty than the least squares methods.

The purpose of this study is to present the damage detection method on shear building structures by mode shape. The damage location index using 1st mode shape is observed theoretically to find out damage location. The damage detection method is applied to numerical analysis model such as MATLAB and MIDAS GENw for the verification. Finally the shacking table test on 3 story shear building is performed for the examination of the damage detection method.

The purpose of this study is to present the damage detection method on shear building structures by wavelet transformation. The damage location index using 1st mode shape is observed theoretically to find out damage location. The damage detection method is applied to numerical analysis model such as MATLAB for the verification. The shacking table test on 3 story shear building is performed for the examination of the damage detection method. Wavelet transformation and directly fast fourier transformation are performed for the data, and damage index is compared. Finally the applicability of the wavelet transformation for damage detection is examined.