• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.214-220
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• 2004

A computationally efficient algorithm is presented for 3-D near-field source localization using a uniform circular away (UCA). Algebraic relations are demonstrated between the incident angles (elevation angle and azimuth angle) under the far-field assumption and the actual near-field location (range. elevation angle, and azimuth angle). Using these relations as paths to follow to the peak of the 3-D MUSIC spectrum, the proposed algorithm replaces the 3-D search required in the conventional 3-D MUSIC with a 1-D path following after a 2-D initialization. thereby reducing the computational burden.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.253-256
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• 2000

This paper describes a DSP implementation of a real-time 3D sound localization algorithm with the use of a low power embedded DSP. A distinctive feature of this implementation is that the audible frequency band is divided into three, in accordance with the sound reflection and diffraction phenomena through different media from a certain sound source to human ears, and then in each subband a specific implementation procedure of the 3D sound localization is devised so as to operate real-time at a low frequency of 50MHz on a 16bit fixed-point DSP. Thus out DSP implementation can provide a listener with 3D sound effects through a headphone at low cost and low power consumption.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.264-267
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• 2000

This paper describes a real-time 3D sound localization algorithm to be implemented with the use of a Bow power embedded DSP. This algorithm first divides the audible frequency band into three, on the basis of the analysis of the sound reflection and diffraction effects through different media from a certain sound source to human ears, and then in each subband a specific procedure is devised fur the 3D sound localization so as to operate real-time on a low power embedded DSP This algorithm aims at providing a listener with the 3D sound effects through a headphone at low cost and low power consumption.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.33-41
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• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• Aerospace Engineering and Technology
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• v.12 no.1
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• pp.128-136
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• 2013

Recently, the localization recognition system research has been studied using various sensors according to increased interest in autonomous navigation flight. In case of indoor environment which cannot support GPS information, we have to look for another way to recognize current position. The Image-based localization recognition system has been interested although there are lots of way to know current pose. In this paper, we explain the localization recognition system based on mark and implementation of autonomous navigation flight. In order to apply to real environment which cannot support marks, localization based on real-time 3D map building is discussed.

• Journal of KIBIM
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• v.13 no.4
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• pp.64-73
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• 2023

This study introduces a method of estimating the 3D coordinates of structural damage from the detection results of visual inspection provided in 2D image coordinates using sensing data of UAV and 3D shape information of BIM. This estimation process takes place in a virtual space and utilizes the BIM model, so it is possible to immediately identify which member of the structure the estimated location corresponds to. Difference from conventional structural damage localization methods that require 3D scanning or additional sensor attachment, it is a method that can be applied locally and rapidly. Measurement accuracy was calculated through the distance difference between the measured position measured by TLS (Terrestrial Laser Scanner) and the estimated position calculated by the method proposed in this study, which can determine the applicability of this study and the direction of future research.

• The Journal of the Acoustical Society of Korea
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• v.25 no.4
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• pp.184-190
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• 2006

Recently, Lee et al. have proposed an algorithm utilizing the signals from different paths by using bottom mounted simple linear array to estimate 3-D location of oceanic target. But this algorithm assumes that sound velocity is constant along depth of sea. Consequently, serious performance loss is appeared in real oceanic environment that sound speed is changed variously. In this paper, we present a 3-D near field localization algorithm for inhomogeneous sound speed. The proposed algorithm adopt localization function that utilize ray propagation model for multipath environment with linear sound speed profile(SSP), after that, the proposed algorithm searches for the instantaneous azimuth angle, range and depth from the localization cost function. Several simulations using linear SSP and non linear SSP similar to that of real oceans are used to demonstrate the performance of the proposed algorithm. The estimation error in range and depth is decreased by 100m and 50m respectively.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.25-31
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• 2022

Moving among multiple floors is one of the most challenging tasks for indoor autonomous robots. Most of the previous researches for indoor mapping and localization have focused on singular floor environment. In this paper, we present an algorithm that creates a multi-floor map using 3D point cloud. We implement localization within the multi-floor map using a LiDAR and an IMU. Our algorithm builds a multi-floor map by constructing a single-floor map using a LOAM-based algorithm, and stacking them through global registration that aligns the common sections in the map of each floor. The localization in the multi-floor map was performed by adding the height information to the NDT (Normal Distribution Transform)-based registration method. The mean error of the multi-floor map showed 0.29 m and 0.43 m errors in the x, and y-axis, respectively. In addition, the mean error of yaw was 1.00°, and the error rate of height was 0.063. The real-world test for localization was performed on the third floor. It showed the mean square error of 0.116 m, and the average differential time of 0.01 sec. This study will be able to help indoor autonomous robots to operate on multiple floors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9C
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• pp.573-580
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• 2011

WSNs (Wireless Sensor Networks) are becoming more widely used in various fields, and improving localization performance is a crucial and essential issue for sensor network applications. In this paper, we propose a low-complexity localization mechanism for WSNs that operates in 3D (Three-Dimensional) space. The basic idea is to use aerial vehicles or flying objects that are deliberately equipped with the anchor nodes. These anchor nodes periodically broadcast beacon signals containing their current locations, and the unknown nodes receive these signals as soon as they enter the communication range of the anchors. We estimate the locations of the unknown nodes based on the proposed scheme that transforms the 3D problem into 2D computations to reduce the complexity of 3D localization. Simulated results show that our approach is an effective scheme for 3D self-positioning in WSNs.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.617-624
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• 2004

This paper describes a new facial feature localization method that uses Adjacent Depth Differences(ADD) in 3D facial surface. In general, human recognize the extent of deepness or shallowness of region relatively, in depth, by comparing the neighboring depth information among regions of an object. The larger the depth difference between regions shows, the easier one can recognize each region. Using this principal, facial feature extraction will be easier, more reliable and speedy. 3D range images are used as input images. And ADD are obtained by differencing two range values, which are separated at a distance coordinate, both in horizontal and vertical directions. ADD and input image are analyzed to extract facial features, then localized a nose region, which is the most prominent feature in 3D facial surface, effectively and accurately.