• 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.

• Smart Structures and Systems
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• v.29 no.6
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• pp.777-783
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• 2022

Even though several deep learning-based methods have been applied in the field of acoustic source localization, the previous works have only been conducted using the two-dimensional representation of the beamforming maps, particularly with the planar array system. While the acoustic sources are more required to be localized in a spherical microphone array system considering that we live and hear in the 3D world, the conventional 2D equirectangular map of the spherical beamforming map is highly vulnerable to the distortion that occurs when the 3D map is projected to the 2D space. In this study, a 3D deep learning approach is proposed to fulfill accurate source localization via distortion-free 3D representation. A target function is first proposed to obtain 3D source distribution maps that can represent multiple sources' positional and strength information. While the proposed target map expands the source localization task into a point-wise prediction task, a PointNet-based deep neural network is developed to precisely estimate the multiple sources' positions and strength information. While the proposed model's localization performance is evaluated, it is shown that the proposed method can achieve improved localization results from both quantitative and qualitative perspectives.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.183-189
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• 2020

In emergency rescue situations, the localization accuracy of the rescue requestor is a very important factor in determining the success or failure of the rescue. Indoors where Global Navigation Satellite System (GNSS) is not operated, there is no choice but to use Wi-Fi or LTE signals. However, the performance of the current emergency rescue system utilizing those RF signals is exceedingly low. In this study, the effectiveness of the surface correlation technology using the accumulated signal pattern of RF signals was verified in relation to the emergency localization technology. To validate the proposed system, we configured and tested an emergency rescue scenario in multi-floors building. When the emergency rescue was requested, it was confirmed that the initial localization error was large owing to the short length of the accumulated signal pattern. However, the localization error decreased over time, which eventually led to the accurate location information being delivered to the rescuer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.640-651
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• 2016

We propose an effective ToA-based localization method considering accuracy in indoor environments. The purpose of the localization system is to estimate the coordinates of the geographic location of target device. In indoor environments, accurately estimating the location of a target device is not easy due to various errors. The accuracy of wireless localization is influenced by NLOS errors. ToA-based localization measures the location of a target device using the distances between a mobile device and three or more base stations. However, each of the NLOS errors along a distance estimated from a target device to a base station is different because of dissimilar obstacles. To accurately estimate the target's location, an optimized localization process is needed in indoor environments. In this paper, effective ToA-based localization method process is proposed for improving accuracy in wireless sensor networks. Performance evaluations are presented, and the experimental localization system results are proved through comparisons of various localization methods with the proposed methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.430-435
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• 2011

In this paper, a navigation technology of an unmanned vehicle using relative localization and magnetic guidance is proposed. Magnetic guidance system had been developed as a robust autonomous driving technology as long as magnetic fields on the path are detected. Otherwise, if magnetic fields were not detected due to some reasons, the vehicle could not drive. Therefore, in order to overcome the drawback, we propose that relative localization would be combined to magnetic guidance system. To validate the usefulness of the proposed method, a robotic vehicle was set up with the magnetic guidance system and the relative localization. In addition, the unmanned driving test was realized on the road without the magnetic fields so that the proposed method is verified by the experiment.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.237-244
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• 2008

Nowadays, research on human-robot interaction has been getting increasing attention. In the research field of human-robot interaction, speech signal processing in particular is the source of much interest. In this paper, we report a speaker localization system with six microphones for a humanoid robot called MAHRU from KIST and propose a time delay of arrival (TDOA)-based feature matrix with its algorithm based on the minimum sum of absolute errors (MSAE) for sound source localization. The TDOA-based feature matrix is defined as a simple database matrix calculated from pairs of microphones installed on a humanoid robot. The proposed method, using the TDOA-based feature matrix and its algorithm based on MSAE, effortlessly localizes a sound source without any requirement for calculating approximate nonlinear equations. To verify the solid performance of our speaker localization system for a humanoid robot, we present various experimental results for the speech sources at all directions within 5 m distance and the height divided into three parts.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.436-442
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• 2015

In this paper, we develop an indoor localization device which embeds localization information into indoor light-emitting-diodes (LED) lighting systems. The key idea of our device is the use of the newly proposed "bit stuffing method". Through the use of stuff bits, our device is able to measure signal strengths even in transient states, which prohibits interference between lighting signals. The stuff bits also scatter the parts of the signal where the LED is turned on, thus provides quality indoor lighting. Additionally, for the indoor localization system based on RSSI and TDM to be practical, we propose methods for the control of LED lamps and compensation of received signals. The effectiveness of the proposed scheme is validated through experiments with a low-cost implementation including an indoor navigation task.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.206-215
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• 2014

Acoustic signal is crucial for the autonomous navigation of underwater vehicles. For this purpose, this paper presents a method of acoustic source localization. The proposed method is based on the probabilistic estimation of time delay of acoustic signals received by two hydrophones. Using Bayesian update process, the proposed method can provide reliable estimation of direction angle of the acoustic source. The acquired direction information is used to estimate the location of the acoustic source. By accumulating direction information from various vehicle locations, the acoustic source localization is achieved using extended Kalman filter. The proposed method can provide a reliable estimation of the direction and location of the acoustic source, even under for a noisy acoustic signal. Experimental results demonstrate the performance of the proposed acoustic source localization method in a real sea environment.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.368-373
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• 2010

A new indoor mobile robot localization method is presented. Robot recognizes well designed single color landmarks on the ceiling by vision system, as reference to compute its precise position. The proposed likelihood prediction based method enables the robot to estimate its position based only on the orientation of landmark.The use of single color landmarks helps to reduce the complexity of the landmark structure and makes it easily detectable. Edge based optical flow is further used to compensate for some landmark recognition error. This technique is applicable for navigation in an unlimited sized indoor space. Prediction scheme and localization algorithm are proposed, and edge based optical flow and data fusing are presented. Experimental results show that the proposed method provides accurate estimation of the robot position with a localization error within a range of 5 cm and directional error less than 4 degrees.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.12
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• pp.994-1000
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• 2002

In periodically repeated cyclic structures, small property irregularity of their substructures often causes significant difference in their dynamic responses. which results in unpredicted premature failures. The small irregularity and the resulting phenomenon are called the mistuning and the vibration localization. respectively. In this paper, the vibration localization phenomena due to mistuned coupling effects are investigated. To effectively achieve the objective, a simple coupled multi-pendulum system Is employed. The results show that if there exists some coupling stiffness irregularity, vibration localization may occur and becomes more predominant as the number of substructures increases.