• Journal of Sensor Science and Technology
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• v.19 no.4
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• pp.278-284
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• 2010

Indoor localization for pedestrian is the key technology for caring the elderly, the visually impaired and the handicapped in health care districts. It also becomes essential for the emergency responders where the GPS signal is not available. This paper presents newly developed pedestrian localization system using the gyro sensors, the magnetic compass and pressure sensors. Instead of using the accelerometer, the pedestrian gait is estimated from the gyro sensor measurements and the travel distance is estimated based on the gait kinematics. Fusing the gyro information and the magnetic compass information for heading angle estimation is presented with the error covariance analysis. A pressure sensor is used to identify the floor the pedestrian is walking on. A complete ambulatory system is implemented which estimates the pedestrian's 3D position and the heading.

• Journal of Engineering Education Research
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• v.19 no.6
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• pp.49-56
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• 2016

The Human Robot Interface (HRI) based on 3D depth sensor on the docent robot is developed and the localization algorithm based on extended Kalman Filter (EKFLA) are proposed through the capstone design by graduate students in this paper. In addition to this, the performance of the proposed EKFLA is also analyzed. The developed HRI system consists of the route generation and localization algorithm, the user behavior pattern awareness algorithm, the map data generation and building algorithm, the obstacle detection and avoidance algorithm on the robot control modules that control the entire behaviors of the robot. It is confirmed that the improvement ratio of the localization error in EKFLA on the scenarios 1-3 is increased compared with the localization algorithm based on Kalman Filter (KFLA) as 21.96%, 25.81% and 15.03%, respectively.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4E
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• pp.52-60
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• 2001

This paper describes real time implementation of subband sound localization system on a floating-point DSP TI TMS320C31. The system determines two dimensional location of an active speaker in a closed room environment with real noise presents. The system consists of an two microphone array connected to TI DSP hosted by PC. The implemented sound localization algorithm is Subband CPSP which is an improved version of traditional CPSP (Cross-Power Spectrum Phase) method. The algorithm first split the input speech signal into arbitrary number of subband using subband filter banks and calculate the CPSP in each subband. It then averages out the CPSP results on each subband and compute a source location estimate. The proposed algorithm has an advantage over CPSP such that it minimize the overall estimation error in source location by limiting the specific band dominant noise to that subband. As a result, it makes possible to set up a robust real time sound localization system. For real time simulation, the input speech is captured using two microphone and digitized by the DSP at sampling rate 8192 hz, 16 bit/sample. The source location is then estimated at once per second to satisfy real-time computational constraints. The performance of the proposed system is confirmed by several real time simulation of the speech at a distance of 1m, 2m, 3m with various speech source locations and it shows over 5% accuracy improvement for the source location estimation.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.302-306
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• 2021

Indoor localization is one of the basic elements of Location-Based Service, such as indoor navigation, location-based precision marketing, spatial recognition of robotics, augmented reality, and mixed reality. We propose a Voxel Labeling-based visual positioning system using object simultaneous localization and mapping (SLAM). Our method is a method of determining a location through single image 3D cuboid object detection and object SLAM for indoor navigation, then mapping to create an indoor map, addressing it with voxels, and matching with a defined space. First, high-quality cuboids are created from sampling 2D bounding boxes and vanishing points for single image object detection. And after jointly optimizing the poses of cameras, objects, and points, it is a Visual Positioning System (VPS) through matching with the pose information of the object in the voxel database. Our method provided the spatial information needed to the user with improved location accuracy and direction estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1B
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• pp.162-175
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• 2010

Currently, geographical information is interpreted and adopted in a wide range of context, and used for meeting diverse demands, such as, battlefield, traffic management, or public safety. With such an explosive increase of location-based applications, a considerable amount of research on the localization technique has been carried out. Among them, RSS (Received Signal Strength)-based approach is used especially for the indoor localization due to intrinsic limitations of the indoor environment. In this paper, we perform theoretical and empirical studies on enhancing the accuracy of the RSS-based localization on the IEEE 802.15.4 network. To this end, we set up an indoor testbed and implement a localization system on it. In addition to the theoretical analysis of the localization algorithm that we used, an empirical analysis on the effect of the factors which affect the accuracy of a localization system is carried out. Finally, we suggest some critical guidelines that should be considered for building a highly accurate localization system.

• Computers and Concrete
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• v.7 no.4
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• pp.317-329
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• 2010

The paper describes localization of deformation in a bar under tensile loading. The material of the bar is considered as non-linear viscous elastic and the bar consists of two symmetric halves. It is assumed that the model represents behavior of the quasi-brittle viscous material under uniaxial tension with different loading rates. Besides that, the bar could represent uniaxial stress-strain law on a single plane of a microplane material model. Non-linear material property is taken from the microplane material model and it is coupled with the viscous damper producing non-linear Maxwell material model. Mathematically, the problem is described with a system of two partial differential equations with a non-linear algebraic constraint. In order to obtain solution, the system of differential algebraic equations is transformed into a system of three partial differential equations. System is subjected to loadings of different rate and it is shown that localization occurs only for high loading rates. Mathematically, in such a case two solutions are possible: one without the localization (unstable) and one with the localization (stable one). Furthermore, mass is added to the bar and in that case the problem is described with a system of four differential equations. It is demonstrated that for high enough loading rates, it is the added mass that dominates the response, in contrast to the viscous and elastic material parameters that dominated in the case without mass. This is demonstrated by several numerical examples.

• 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.

• Progress in Superconductivity
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• v.4 no.1
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• pp.19-26
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• 2002

We have earlier developed a 40-channel SQUID system. An important figure of merit of a MEG system is the localization error, within which the underlying current source can be localized. With this system, we investigated the localization error in terms of the standard deviation of the coordinates of the ECDs and the systematic error due to inadequate modeling. To do this, we made localization of single current dipoles from tangential components of auditory evoked fields. Equivalent current dipoles (ECD) at N1m peak were estimated based on a locally fitted spherical conductor model. In addition, we made skull phantom and simulation measurements to investigate the contribution of various errors to the localization error. It was found that the background noise was the main source of the errors that could explain the observed standard deviation. Further, the amount of systematic error, when modeling the head with a spherical conductor, was much less than the standard deviation due to the background noise. We also demonstrated the performance of the system by measuring the evoked fields to grammatical violation in sentence comprehension.

• Journal of Sensor Science and Technology
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• v.26 no.3
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• pp.199-203
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• 2017

In this paper, we developed an underwater localization system for underwater robot docking using the electromagnetic wave attenuation model. Electromagnetic waves are generally known to be impossible to use in water environment. However, according to the conclusions of the previous studies on the attenuation characteristics in underwater, the attenuation pattern is uniform and its model was accurately proposed and verified in 3-dimensional space via the omnidirectional antenna. In this paper, a docking structure and localization sensor system are developed for a widely used cone type docking mechanism. First, we fabricated electromagnetic wave range sensor transmit modules. And a mobile sensor node is equipped with unmanned underwater vehicle(UUV)s. The mobile node senses the four different signal strength (RSS: Received Signal Strength) from fixed nodes, and the obtained RSS data are transformed to each distance information using the 3-Dimensional EM wave attenuation model. Then, the relative localization between the docking area and underwater robot can be achieved according to optimization algorithm. Finally, experimental results show the feasibility of the proposed localization system for the docking induction by comparing the errors in the actual position of the mobile node and the theoretical position through the model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.161-166
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• 2006

Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.