• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.223-228
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• 2011

In this paper, a novel range-free localization algorithm for anisotropic networks is proposed. In the proposed method, the characteristics of the given network are considered and each sensor node estimates the relation between the hop counts and the geographical distances. Unlike most of the previous localization algorithms, the proposed method performs well not only in the isotropic network but also in the anisotropic networks. The proposed method is applied to both isotropic and anisotropic network topologies and the simulation results demonstrate that the method exhibits excellent and robust performances.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.270-274
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• 2007

In this paper, we present a Sound Source Localization (SSL) based GCC (Generalized Cross Correlation)-PHAT (Phase Transform) and new measurement method of angle with robot auditory system for a network-based intelligent service robot. The main goal of this paper is to analysis performance of TDOA and GCC-PHAT sound source localization method and new angle measurement method is compared. We use GCC-PHAT for measuring time delays between several microphones. And sound source location is calculated by using time delays and new measurement method of angle. The robot platform used in this work is wever-R2, which is a network-based intelligent service robot developed at Intelligent Robot Research Division in ETRI.

• Smart Structures and Systems
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• v.30 no.4
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• pp.371-383
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• 2022

A novel impact localization method is presented based on impact induced elastic waves in sensorized composite structure subjected to temperature fluctuations. In real practices, environmental and operational conditions influence the acquired signals and consequently make the feature (particularly Time of Arrival (TOA)) extraction process, complicated and troublesome. To overcome this complication, a robust TOA estimation method is proposed based on the times in which the absolute amplitude of the signal reaches to a specific amplitude value. The presented method requires prior knowledge about the normalized wave velocity in different directions of propagation. To this aim, a finite element model of the plate was built in ABAQUS/CAE. The impact location is then highlighted by calculating an error value at different points of the structure. The efficiency of the developed impact localization technique is experimentally evaluated by dropping steel balls with different energies on a carbon fiber composite plate with different temperatures. It is demonstrated that the developed technique is able to localize impacts with different energies even in the presence of noise and temperature fluctuations.

• Proceedings of the Korea Concrete Institute Conference
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• 1995.10a
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• pp.178-182
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• 1995

Strain localization is important phenomenon since it governs the total behavior or ultimate loads in various kinds of engineering problems. Establishment of an analysis method for strain localization phenomena is also of great concern for expansion of fracture mechanics of concrete. Inside zone of localization, a decrese in stress is accompanied by an increse in strain; outside the strain decreses. All deformation localization phenomenon cannot be predicted by both the classical stress-strain formulation and the linear elastic fracture mechanics. In this paper, a simple one dimensional model including localized deformation zone is studied under compressive and tensile loading. When the model is loaded. localization is assumed to occur uniformly in a finite region and material outside the localization zone is modelled as elastic unloading occurs. Size effects of effective elastic moduli under compression and tension in localization zone are examined.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.117-123
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• 2014

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.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.117-122
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• 2008

This paper presents a multi-robot localization based on multidimensional scaling (MDS) in spite of the existence of incomplete and noisy data. While the traditional algorithms for MDS work on the full-rank distance matrix, there might be many missing data in the real world due to occlusions. Moreover, it has no considerations to dealing with the uncertainty due to noisy observations. We propose a robust MDS to handle both the incomplete and noisy data, which is applied to solve the multi-robot localization problem. To deal with the incomplete data, we use the Nystr$\ddot{o}$m approximation which approximates the full distance matrix. To deal with the uncertainty, we formulate a Bayesian framework for MDS which finds the posterior of coordinates of objects by means of statistical inference. We not only verify the performance of MDS-based multi-robot localization by computer simulations, but also implement a real world localization of multi-robot team. Using extensive empirical results, we show that the accuracy of the proposed method is almost similar to that of Monte Carlo Localization(MCL).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.1
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• pp.37-41
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• 2016

Localization is one of the key issues of demandable applications, especially smart services. Beside the traditional GPS based localization technique, the localization issue by visible light communications is promising market because of possibility of combining visible light communications with positioning technique for a high accurate, especially indoor localization service. This paper provides the overview and new image sensor scheme for localization issue based on visible light communication. The survey is introduced from core techniques to enhancement issues of localization. We hope these will be the essential references for the impact selection method in implementation and standardization issues.

• Journal of Advanced Navigation Technology
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• v.12 no.6
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• pp.619-626
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• 2008

In this paper, we proposed a RSS based cooperative localization algorithm using VRN for wireless sensor networks, which can estimate the BN position. The proposed localization system monitoring all nodes estimates a position of BN, and calculates an intersection area with cooperative localization. From the results, we confirm that BN intersection area is reduced as the number of RN is increased. In addition, the fewer RN exists, the more iteration needs at least 4 times. Moreover, the propose algorithm using 4 RNs is improved 71.6% estimation performance than conventional method. Therefore, the cooperative localization algorithm with VRN provides higher localization accuracy than RSS based conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3657-3682
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• 2018

This paper presents a Bluetooth and pedestrian dead reckoning (PDR)-based indoor fusion localization approach (BtPDR) using smartphones. A Bluetooth and PDR-based indoor fusion localization approach can localize the initial position of a smartphone with the received signal strength (RSS) of Bluetooth. While a smartphone is moving, BtPDR can track its position by fusing the localization results of PDR and Bluetooth RSS. In addition, BtPDR can adaptively modify the parameters of PDR. The contributions of BtPDR include: a Bluetooth RSS-based Probabilistic Voting (BRPV) localization mechanism, a probabilistic voting-based Bluetooth RSS and PDR fusion method, and a heuristic search approach for reducing the complexity of BRPV. The experiment results in a real scene show that the average positioning error is < 2m, which is considered adequate for indoor location-based service applications. Moreover, compared to the traditional PDR method, BtPDR improves the location accuracy by 42.6%, on average. Compared to state-of-the-art Wireless Local Area Network (WLAN) fingerprint + PDR-based fusion indoor localization approaches, BtPDR has better positioning accuracy and does not need the same offline workload as a fingerprint algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.699-705
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• 2012

In this paper, an infrastructure-based localization method using underwater wireless sensor network (UWSN) is addressed. A localization using the UWSN is necessary to widen the usage of underwater applications, however it is very difficult to establish the UWSN due to the restrictions of water. In this paper, to extend the usage of UWSN at the infrastructure, we propose a sophisticated UWSN localization method using the Received Signal Strength Indicator (RSSI) of the electromagnetic waves. During the electromagnetic waves propagating in underwater, there arises a lot of attenuation according to the distance, while the attenuation shows uniformity according to the distance. Using this characteristics, the localization system in underwater infrastructure is proposed and the experimental results show the effectiveness.