• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.107-112
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• 2013

In this paper, we discuss a 3-dimensional localization sensor node using EM waves (Electromagnetic waves) with RSSI (Received Signal Strength Indicator). Generally EM waves cannot be used in underwater environment, because the signal is highly attenuated by the water medium according to the distance. Although the signal quickly reduces in underwater, the reducing tendency is very clear and uniform. Hence EM waves have possibility as underwater distance sensors. The authors have verified the possibility by theory and several experiments, and developed calibration methods in case of linear and planer environment. For 3-dimensional localization in underwater, it must be known antenna's radiation pattern property in electric plane(called E-plane). In this paper, we proceed experiments to verify attenuation tendency with z axis movement, PLF (Polarization Loss Factor) and ILF (Inclination Loss Factor) with its theoretical approach.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1931-1935
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• 2004

A location estimate problem is critical issues for mobile robot. Because it is basic problem in practical use of the mobile robot which do what, or move where, or reach an aim. Already there are many technologies of robot localization (like GPS, vision, sonar sensor, etc) used on development. But the elevation of accurateness was brought the problem that must consider an increase of a hardware cost and addition electric power in each ways. There is the core in question to develop available and accurate sensing algorithm though it is economical. We used a ultrasonic sensor and was going to implement comparatively accurate localization though economical. Using a sensing data, we could make a grid map and estimate a position of a mobile robot. In this paper, to get a satisfactory answer about this problem using a ultrasonic sensor.

• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2189-2196
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• 2006

The present work is concerned with the development of a procedure for adaptive computations of shear localization problems. The maximum jump of equivalent strain rates across element boundaries is proposed as a simple error indicator based on interpolation errors, and successfully implemented in the adaptive mesh refinement scheme. The time step is controlled by using a parameter related to the Lipschitz constant, and state variables in target elements for refinements are transferred by $L_2$-projection. Consistent tangent moduli with a proper updating scheme for state variables are used to improve the numerical stability in the formation of shear bands. It is observed that the present adaptive mesh refinement procedure shows an excellent performance in the simulation of shear localization problems.

• Current Research on Agriculture and Life Sciences
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• v.16
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• pp.1-14
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• 1998

As a result of the execution of the import liberalization and local autonomy with WTO system launching, centralized rural extension service converted to localized rural extension service. This advent of globalization and localization era affects our over all agricultural condition, moreover the duty and role of rural extension organization which take complete of rural extension, is compelled to diversified and specified technology. In this study, first we will investigate the change of agricultural, rural community, and local rural extension service in globalization and localization era. Second we will analyze the confronted problems of local rural extension service. With this study's outcome for basis, we will present new role and direction of local rural extension service which can contribute to local agricultural development.

• Journal of Aerospace System Engineering
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• v.12 no.6
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• pp.32-40
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• 2018

An impact localization for a carbon fiber reinforced plastic (CFRP) composite plate was performed using the multiplexed fiber bragg grating (FBG) sensors and the error-outlier based impact localization algorithm. We found that the optimal impact localization with the maximum error of 31.82 mm and the averaged error of 6.31 mm are obtained when the error threshold (ET) and constant level (CL) are 0.3 nm and 110, respectively. Moreover, the detailed process of impact localization under certain optimal parameters and the relevant results were thoroughly investigated. We conclude that the multiplexed FBG sensors and the error-outlier based impact localization algorithm are suitable for an impact localization on composite structures, and expect that they can be utilized for various structural health monitoring (SHM) in the future.

• Journal of Ocean Engineering and Technology
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• v.19 no.2 s.63
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• pp.82-89
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• 2005

This study deals with the development of the extended Kalman filter(EKF) algorithm for the localization of underwater mining vehicles. Both simulation and experimental studies in a test bed are carried out. For the experiments, a scale dawn tracked vehicle is run in a soil bin containing cohesive soil of bentonite-water mixture. To develop the EKF algorithm, we use a kinematic model including the inner/outer track slips and the slip angle for the vehicle. The measurements include the inner and outer wheel speeds from encoders, the heading angle from a compass sensor and a fiber optic rate gyro, and x and y coordinate position values from a vision system. The vision sensor replaces the LBL(Long Base Line) sonar system used in the real underwater positioning situations. Artificial noise signals mimicking the real LBL noise signal are added to the vision sensor information. To know the mean slip values of the tracks in both straight and cornering maneuver, several trial running experiments are executed before applying the EKF algorithm. Experimental results show the effectiveness of the EKF algorithm in rejecting the sensor measurements noise. Also, the simulation and experimental results show close correlations.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.674-684
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• 2011

More and more elderly and disabled people are using electric scooters instead of electric wheelchairs because of higher mobility. However, people with high levels of impairment or the elderly still have difficulties in driving the electric scooters safely. Semi-autonomous electric scooter system is one of the solutions for the safety: Either manual driving or autonomous driving can be used selectively. In this paper, we implement a semi-autonomous electric scooter system with functions of localization and path following. In order to recognize the pose of electric scooter in outdoor environments, we design an outdoor localization system based on the extended Kalman filter using DGPS (Differential Global Positioning System) and wheel encoders. We added an accelerometer to make the localization system adaptable to road condition. Also we propose a path following algorithm using two arcs with current pose of the electric scooter and a given path in the map. Simulation results are described to show that the proposed algorithms provide the ability to drive an electric scooter semi-autonomously. Finally, we conduct outdoor experiments to reveal the practicality of the proposed system.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.2
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• pp.187-194
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• 2015

Accurate relative location estimation is a key requirement in indoor localization systems based on wireless sensor networks (WSNs). However, although these systems have applied not only various optimization algorithms but also fusion with sensors to achieve high accuracy in position determination, they are difficult to provide accurate relative azimuth and locations to users because of cumulative errors in inertial sensors with time and the influence of external magnetic fields. This paper based on ultra-wideband positioning system, which is relatively suitable for indoor localization compared to other wireless communications, presents an indoor localization system for estimating relative azimuth and location of location-unaware nodes, referred to as target nodes without applying any algorithms with complex variable and constraints to achieve high accuracy. In the proposed method, the target nodes comprising three mobile nodes estimate the relative distance and azimuth from two reference nodes that can be installed by users. In addition, in the process of estimating the relative localization information acquired from the reference nodes, positioning errors are minimized through a novel modified rounding estimation technique in which Kalman filter is applied without any time consumption algorithms. Experimental results show the feasibility and validity of the proposed system.

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.1-8
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• 2015

This paper proposes a study for accurate surface localization system using DWT(Discrete Wavelet Transform) and GPS/INS fusion algorithm. Because the propagation in the underwater is not passed by characteristics of the medium unlike the ground, the sonar system like DVL is used instead of GPS. But since these systems are installed on the seafloor and operated, a long time is required for installation and navigation systems are limited outside of the range area. And it is difficult to estimate position in a three-dimensional considering the depth in actual marine environment. In this paper, before the development of underwater localization system, precisely estimated position system is proposed in a two-dimensional by developing surface localization system using removing noise and disturbance with DWT and relatively inexpensive GPS and INS sensor.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.4
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• pp.517-524
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• 2007

This paper presents a global localization method using circular correlation of an omni-directional image. The localization of a mobile robot, especially in indoor conditions, is a key component in the development of useful service robots. Though stereo vision is widely used for localization, its performance is limited due to computational complexity and its narrow view angle. To compensate for these shortcomings, we utilize a single omni-directional camera which can capture instantaneous $360^{\circ}$ panoramic images around a robot. Nodes around a robot are extracted by the correlation coefficients of CHL (Circular Horizontal Line) between the landmark and the current captured image. After finding possible near nodes, the robot moves to the nearest node based on the correlation values and the positions of these nodes. To accelerate computation, correlation values are calculated based on Fast Fourier Transforms. Experimental results and performance in a real home environment have shown the feasibility of the method.