• Journal of Institute of Control, Robotics and Systems
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• v.13 no.10
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• pp.956-961
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• 2007

We propose a new distance measurement method and local positioning system for the autonomous mobile robots localization. The distance measurement method is able to measure long-range distances with a high accuracy by using ultrasonic sensors. The time of flight of the ultrasonic waves include various noises is calculated accurately by the proposed period detecting method. The proposed local positioning system is composed of four ultrasonic transmitters and one ultrasonic receiver. The ultrasonic transmitter and receiver are separated but they are synchronized by RF (Radio frequency) signal. The proposed system using ultrasonic waves is represented as USAT(Ultrasonic Satellite System). USAT is able to estimate the position using the least square estimation. The experimental results show that the proposed local positioning system enables to estimate the absolute position precisely.

• ETRI Journal
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• v.37 no.4
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• pp.707-716
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• 2015

The purpose of a localization system is to estimate the coordinates of the geographic location of a mobile device. The accuracy of wireless localization is influenced by nonline-of-sight (NLOS) errors in wireless sensor networks. In this paper, we present an improved time of arrival (TOA)-based localization method for wireless sensor networks. TOA-based localization estimates the geographic location of a mobile device using the distances between a mobile station (MS) and three or more base stations (BSs). However, each of the NLOS errors along a distance measured from an MS (device) to a BS (device) is different because of dissimilar obstacles in the direct signal path between the two devices. To accurately estimate the geographic location of a mobile device in TOA-based localization, we propose an optimized localization method with a BS selection scheme that selects three measured distances that contain a relatively small number of NLOS errors, in this paper. Performance evaluations are presented, and the experimental results are validated through comparisons of various localization methods with the proposed method.

• IE interfaces
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• v.23 no.3
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• pp.239-245
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• 2010

This paper considers a localization problem of a moving tag on RFID(Radio Frequency Identification) systems, where a positioning engine collects TDOA(Time-difference of Arrival) signal from a target tag to estimate the position of the tag. To localize the tag in the RFID system, we develop two heuristic algorithms and evaluate their performance in the estimation error and computational time by using randomly generated numerical examples. Based upon the performance evaluation, we can conclude our algorithms are valuable for localization the moving target.

• ETRI Journal
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• v.37 no.2
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• pp.262-272
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• 2015

In particular, for a practical mobile robot team to perform such a task as that of carrying out a search and rescue mission in a disaster area, the network connectivity and localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a Global Positioning System is unavailable. This paper proposes the new collective intelligence network management architecture of multiple mobile robots supporting seamless network connectivity and cooperative localization. The proposed architecture includes a resource manager that makes the robots move around and not disconnect from the network link by considering the strength of the network signal and link quality. The location manager in the architecture supports localizing robots seamlessly by finding the relative locations of the robots as they move from a global outdoor environment to a local indoor position. The proposed schemes assuring network connectivity and localization were validated through numerical simulations and applied to a search and rescue robot team.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.101-105
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• 2014

For a localization system, the TDOA (Time Difference of Arrival) measurement and AOA (Angle of Arrival) measurement are often used for estimating target's positions. Although it is known that the accuracy of TDOA based localization is superior to that of AOA based one, it may have a poor vertical accuracy in bad geometrical conditions. This paper, therefore, proposes a localization algorithm in which the vertical position is estimated by AOA measurements and the horizontal one is estimated by TDOA measurement in order to achieve high 3D-location accuracy. And this algorithm is applied to a GPS jammer localization systems because it has a large value of the DOP (Dilution of Precision) when the jammer is located far away from the system. Simulation results demonstrate that the proposed hybrid TDOA/AOA location algorithm gives much higher location accuracy than TDOA or AOA only location.

• 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.

• Journal of KIISE:Information Networking
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• v.32 no.5
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• pp.574-582
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• 2005

Localization in wireless sensor networks is essential to important network functions such as event detection, geographic routing, and information tracking. Localization is to determine the locations of nodes when node connectivities are given. In this paper, centroid approach known as a distributed algorithm is extended to a centralized algorithm. The centralized algorithm has the advantage of simplicity. but does not have the disadvantage that each unknown node should be in transmission ranges of three fixed nodes at least. The algorithm shows that localization can be formulated to a linear system of equations. We mathematically show that the linear system have a unique solution. The unique solution indicates the locations of unknown nodes are capable of being uniquely determined.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.27-30
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• 2012

One of the most fundamental functions required for an intelligent agent is to estimate its current position based upon uncertain sensor data. In this paper, we explain the implementation of a robot localization system using Particle filters, which are the most effective one of the probabilistic localization methods, and then present the result of experiments for evaluating the performance of our system. Through conducting experiments to compare the effect of the noise-free model with that of the noisy state transition model considering inherent errors of robot actions, we show that it can help improve the performance of the Particle filter localization to apply a state transition model closely approximating the uncertainty of real robot actions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.678-700
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• 2023

Diagnosing breast diseases using ultrasound (US) images remains challenging because it is time-consuming and requires expert radiologist knowledge. As a result, the diagnostic performance is significantly biased. To assist radiologists in this process, computer-aided diagnosis (CAD) systems have been developed and used in practice. This type of system is used not only to assist radiologists in examining breast ultrasound images (BUS) but also to ensure the effectiveness of the diagnostic process. In this study, we propose a new approach for breast lesion localization and segmentation using a multi-scale pyramid of the ultrasound image of a breast organ and a convolutional semantic segmentation network. Unlike previous studies that used only a deep detection/segmentation neural network on a single breast ultrasound image, we propose to use multiple images generated from an input image at different scales for the localization and segmentation process. By combining the localization/segmentation results obtained from the input image at different scales, the system performance was enhanced compared with that of the previous studies. The experimental results with two public datasets confirmed the effectiveness of the proposed approach by producing superior localization/segmentation results compared with those obtained in previous studies.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.106-116
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• 2012

The huge success of location-aware applications has called for the rapid development of an alternative positioning system to the global positioning system (GPS) for indoor localization based on existing technologies, such as 802.11 wireless networks. This paper proposes the Wireless MAC Processor Positioning System (WMPS), which is a localization system running on off-the-shelf 802.11 Access Points and based on the time-of-flight ranging of users' standard terminals. This paper proves through extensive experiments that the propagation delays can be measured with the accuracy required by indoor applications despite the different noise components that can affect the result: latencies of the hardware transreceivers, multipath, ACK jitters and timer quantization. Key to this solution is the choice of the Wireless MAC Processor architecture, which enables a straightforward implementation of the ranging subsystem directly inside the commercial cards without affecting the basic DCF channel access algorithm. In addition to the proposed measurement framework, this study developed a simple and effective localization algorithm that can work without requiring any preliminary calibration or device characterization. Finally, the architecture allows the measurement methodology to be adjusted as a function of the network load or propagation environments at the run time, without requiring any firmware update.