• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.872-876
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• 2005

We propose a real-time post processing of nonlinear amplified signal to improve voice recognition in remote talk. In the previous research, we have found the nonlinear amplification has unique advantage for both the voice activity detection and the sound localization in remote talk. However, the original signal becomes distorted due to its nonlinear amplification and, as a result, the rest of sequence such as speech recognition show less satisfactorily results. To remedy this problem, we implement a linearization algorithm to recover the voice signal's linear characteristics after the localization has been done.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.366-371
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• 2005

For an autonomous mobile robot localization, it is very important for the robot to be able to recognize indoor environment and match a detected object to an object defined within a map developed either online or of offline. Given the map defining the locations of geometric beacons like wall and corner existing in the robot operation environment, this paper presents a stereo ultrasonic sensor based method practically applicable in recognizing the geometric beacons in real-time. The stereo ultrasonic sensor used in the experiment consists of an ultrasonic transmitter and two ultrasonic receivers placed symmetrically about the transmitter Experimental results are provided to demonstrate that the proposed method is more efficient in recognizing wall and coner than the conventional method of using multiple number of transmitter-receiver pairs.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.280-285
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• 2011

Recently, with the development of service robots and the concept of ubiquitous, the position estimation of mobile objects has received great interest. Some of the localization schemes are introduced, which provide the relative location of the moving objects subjected to accumulated errors. To implement a real time localization system, a new absolute position estimation method for a mobile robot in indoor environment is proposed. Design and implementation of the localization system comes from the usage of active beacon systems (based upon RFID technology). The active beacon system is composed of an RFID receiver and an ultra-sonic transmitter. The RFID receiver gets the synchronization signal from the mobile robot and the ultra-sonic transmitter sends out the traveling signal to be used for measuring the distance. Position of a mobile robot in a three dimensional space can be calculated basically from the distance information from three beacons and the absolute position information of the beacons themselves. In some case, the mobile robot can acquire the ultrasonic signals from only one or two beacons, due to the obstacles located along the moving path. In this paper, a position estimation scheme using fewer than three sensors is developed. Also, the extended Kalman filter algorithm is applied for the improvement of position estimation accuracy of the mobile robot.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5422-5441
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• 2016

Despite the abundant literature in the field, there is still the need to find a time-efficient, highly accurate, easy to deploy and robust localization algorithm for real use. The algorithm only involves minimal human intervention. We propose an enhanced Received Signal Strength Indicator (RSSI) based positioning algorithm for Wi-Fi capable devices, called the Dynamic Weighted Evolution for Location Tracking (DWELT). Due to the multiple phenomena affecting the propagation of radio signals, RSSI measurements show fluctuations that hinder the utilization of straightforward positioning mechanisms from widely known propagation loss models. Instead, DWELT uses data processing of raw RSSI values and applies a weighted posterior-probabilistic evolution for quick convergence of localization and tracking. In this paper, we present the first implementation of DWELT, intended for 1D location (applicable to tunnels or corridors), and the first step towards a more generic implementation. Simulations and experiments show an accuracy of 1m in more than 81% of the cases, and less than 2m in the 95%.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.12
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• pp.44-53
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• 2007

In this paper, we focus on the developments of complex location awareness algorithms for real-time location based service and precise/stable localization in the outdoor. In the case of using galileo satellite system along with GPS, several error factor such as the ionosphere can be reduced for an increment of used frequency and visible satellites. Therefore, localization estimation error is no longer having problems with location awareness. But, chips synchronization error induces the error of acquisition and tracking, and the performance of receiver can be decreased. In order to solve this problem, this paper proposes a correlator for performance improvement of receiver in the precise localization.

• Journal of Ship and Ocean Technology
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• v.9 no.4
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• pp.23-34
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• 2005

Increased usage of AUVs has led to the development of alternative navigational methods that use the acoustic beacons and dead reckoning. This paper describes a concurrent mapping and localization (CML) scheme that uses range sonars mounted on SNUUV­I, which is a small test AUV developed by Seoul National University. The CML is one of such alternative navigation methods for measuring the environment that the vehicle is passing through. In addition, it is intended to provide relative position of AUV by processing the data from sonar measurements. A technique for CML algorithm which uses several ranging sonars is presented. This technique utilizes an extended Kalman filter to estimate the location of the AUV. In order for the algorithm to work efficiently, the nearest neighbor standard filter is introduced as the algorithm of data association in the CML for associating the stored targets the sonar returns at each time step. The proposed CML algorithm is tested by simulations under various conditions. Experiments in a towing tank for one dimensional navigation are conducted and the results are presented. The results of the simulation and experiment show that the proposed CML algorithm is capable of estimating the position of the vehicle and the object and demonstrates that the algorithm will perform well in the real environment.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.75-81
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• 2023

The significance of gas sensors has been emphasized in various industries and applications, owing to the growing significance of environmental, social, and governance (ESG) management in corporate operations. In particular, the monitoring of hazardous gas leakages and detection of fugitive emissions have recently garnered significant attention across several industrial sectors. As industrial workplaces evolve to ensure the safety of their working environments and reduce greenhouse gas emissions, the demand for high-performance gas sensors in industrial sectors dealing with toxic substances is on the rise. However, conventional gas-sensing systems have limitations in monitoring fugitive gas leakages at both critical and subcritical concentrations in complex environments. To overcome these difficulties, recent studies in the field of gas sensors have employed techniques such as mobile robotic olfaction, remote optical sensing, chemical grid sensing, and remote acoustic sensing. This review highlights the significant progress made in various technologies that have enabled accurate and real-time mapping of gas distribution and localization of hazardous gas sources. These recent advancements in gas-sensing technology have shed light on the future role of gas-detection systems in industrial safety.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.422-424
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• 2021

In this paper, it leads the approach of fusing multiple RGB cameras for visual objects recognition based on deep learning with convolution neural network and 3D Light Detection and Ranging (LiDAR) to observe the environment and match into a 3D world in estimating the distance and position in a form of point cloud map. The goal of perception in multiple cameras are to extract the crucial static and dynamic objects around the autonomous vehicle, especially the blind spot which assists the AV to navigate according to the goal. Numerous cameras with object detection might tend slow-going the computer process in real-time. The computer vision convolution neural network algorithm to use for eradicating this problem use must suitable also to the capacity of the hardware. The localization of classified detected objects comes from the bases of a 3D point cloud environment. But first, the LiDAR point cloud data undergo parsing, and the used algorithm is based on the 3D Euclidean clustering method which gives an accurate on localizing the objects. We evaluated the method using our dataset that comes from VLP-16 and multiple cameras and the results show the completion of the method and multi-sensor fusion strategy.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.457-461
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• 2013

This paper proposes an image feature-based real-time RGB-D (Red-Green-Blue Depth) 3D SLAM (Simultaneous Localization and Mapping) system. RGB-D data from Kinect style sensors contain a 2D image and per-pixel depth information. 6-DOF (Degree-of-Freedom) visual odometry is obtained through the 3D-RANSAC (RANdom SAmple Consensus) algorithm with 2D image features and depth data. For speed up extraction of features, parallel computation is performed with GPU acceleration. After a feature manager detects a loop closure, a graph-based SLAM algorithm optimizes trajectory of the sensor and builds a 3D point cloud based map.

• Molecules and Cells
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• v.20 no.3
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• pp.348-353
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• 2005

Using in silico approaches and RACE we cloned a full length trinucleotide (CAG) repeat-containing cDNA (cag-3). The cDNA is 2478 bp long and the deduced polypeptide consists of 140 amino acids of which 73 are glutamines. The genomic sequence spans approximately 79 kb on mouse chromosome 7 and the gene is composed of four exons. Standard and real-time PCR analyses of several mouse tissues showed that the gene is exclusively expressed in the brain and is not detected in embryonic stages. Within the brain, it is expressed throughout the forebrain region with predominant expression in the hypothalamus and olfactory bulb and very low levels in the mid- and hindbrain.