• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.428-436
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• 2014

This paper proposes a statistical regression method for classifying pillars and vehicles in parking area using a single ultrasonic sensor. There are three types of information provided by the ultrasonic sensor: TOF, the peak and the width of a pulse, from which 67 different features are extracted through segmentation and data preprocessing. The classification using the multiple SVM and the multinomial logistic regression are applied to the set of extracted features, and has achieved the accuracy of 85% and 89.67%, respectively, over a set of real-world data. The experimental result proves that the proposed feature extraction and classification scheme is applicable to the object classification using an ultrasonic sensor.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.666-668
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• 2016

Salt and pepper noise generally occurs due to errors in the transmission channel or sensors and it lowers the resolution of the image and causes visual errors. To remove this salt and pepper noise, SMF(standard median filter), which represents simple algorithm and excellent noise removal performance, is widely used. However preservation characteristics in the pitch areas of the image is rather lacking. Therefore to effectively restore images damaged by salt and pepper noise, the study suggested a multiple filter that applies filters differently according to size by applying noise density threshold value of local mask on noise signal, while preserving non-noise signal.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.634-640
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• 2015

This paper proposes a novel three-dimensional mapping algorithm in Omni-Directional Vision SLAM based on a fisheye image and laser scanner data. The performance of SLAM has been improved by various estimation methods, sensors with multiple functions, or sensor fusion. Conventional 3D SLAM approaches which mainly employed RGB-D cameras to obtain depth information are not suitable for mobile robot applications because RGB-D camera system with multiple cameras have a greater size and slow processing time for the calculation of the depth information for omni-directional images. In this paper, we used a fisheye camera installed facing downwards and a two-dimensional laser scanner separate from the camera at a constant distance. We calculated fusion points from the plane coordinates of obstacles obtained by the information of the two-dimensional laser scanner and the outline of obstacles obtained by the omni-directional image sensor that can acquire surround view at the same time. The effectiveness of the proposed method is confirmed through comparison between maps obtained using the proposed algorithm and real maps.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8B
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• pp.1003-1011
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• 2011

In this paper, a real-time multi-source sensor data management system based on wireless sensor network is proposed and implemented. The proposed management system is designed to transmit the wireless data to the server in order to monitor and control the multi-source target's status efficiently by analyzing them. The proposed system is implemented to make it possible to control and transmit the wireless sensor data by classifying them, of which data are issued from the clustered sources composed of a number of the remote multiple sensors. In order to evaluate the performance of the proposed system, we measure and analyze both the transmission delay time according to the distance and the data loss rate issued from multiple data sources. From these results, it is verified that the proposed system has a good performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5B
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• pp.443-448
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• 2009

A boundary value of the velocity of data gathering node (DGN) and a critical value for training overhead beyond which the scheme will not be feasible for a Multiple Input Multiple Output (MIMO) based cooperative communication for energy-limited wireless sensor networks is proposed in this paper. The performance in terms of energy efficiency and delay for a combination of two transmitting and two receiving antennas is analyzed. The results show that a set of critical value of velocity and training overhead pair is present for the long haul communication from the sensors to the data gathering node. Finally a relation between training overhead and velocity is simulated.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.659-664
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• 2006

The Context-Aware system is the core technology in the Ubiquitous Computing Environment. Recently, the practical use of a sensor is magnified and the application fields of it are gradually extended in order to collect necessary context information. Context-Aware service integrates the context information which is collected by sensors, and then provides, a suitable service to a user through the process of analysis and reasoning. This service is studied in a variety of fields such as marketing, medical treatment, education and so on. In this paper, we analyze the method of recognizing surrounding context and the result of the awareness by using differential and structural property of multiple valued logic function; propose the model that provides appropriate service depending on the change of surrounding contort; confirm the applicability of the Context-aware system by showing the example of application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1202-1208
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• 2008

This paper represents the multiple sensor fusion algorithm for the deep-sea unmanned underwater vehicles (UUV), composed of a remotely operated vehicle (ROV) 'Hemire' and a depressor 'Henuvy'. The performance of underwater positioning system usually highly depend on that of acoustic sensors such as ultra short base line(USBL), long base line(LBL) and altimeter. A practical sensor fusion algorithm is proposed in the sense of a moving window concept. The performance of the proposed algorithm can be observed by applying the algorithm to the Hemire sea trial data which was measured at the East Sea.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.75-85
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• 2006

This paper has dealt with a data fusion for the problem of land-cover classification using multisensor imagery. Dempster-Shafer evidence theory has been employed to combine the information extracted from the multiple data of same site. The Dempster-Shafer's approach has two important advantages for remote sensing application: one is that it enables to consider a compound class which consists of several land-cover types and the other is that the incompleteness of each sensor data due to cloud-cover can be modeled for the fusion process. The image classification based on the Dempster-Shafer theory usually assumes that each sensor is represented by a single channel. The evidential approach to image classification, which utilizes a mass function obtained under the assumption of class-independent beta distribution, has been discussed for the multiple sets of mutichannel data acquired from different sensors. The proposed method has applied to the KOMPSAT-1 EOC panchromatic imagery and LANDSAT ETM+ data, which were acquired over Yongin/Nuengpyung area of Korean peninsula. The experiment has shown that it is greatly effective on the applications in which it is hard to find homogeneous regions represented by a single land-cover type in training process.

• Smart Media Journal
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• v.8 no.3
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• pp.53-61
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• 2019

In this paper, designing and implementing multi-communication middleware in multi-thread environmet through event-based synchronization method are proposed for stable data transmission of electronic optical equipment, which requires combining camera and various sensors to process multiple high-speed data. To verify the performance of the implemented communication middleware, image data and sensor data were sent to compare differences in reception-based and transmission-based cycles, and the maximum number of communication possibilities to transmit and process multiple was measured and analyzed. In addition, the proposed communication middleware's performance was verified through experiments such as validating the integrity of the transmitted data and measuring the Round Trip Time.