• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.253-258
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• 2016

This paper proposes a method that utilizes optimization approach for localization of an indoor mobile robot. Bayesian filters which have been widely used for localization of a mobile robot use many control parameters to take the uncertainties in measurement and environment into account. The estimation performance depends on the selection of these parameter values. Also, the performance of the Bayesian filters deteriorate as the non-linearity of the motion and measurement increases. On the other hand, the optimization approach uses fewer control parameters and is less influenced by the non-linearity than the Bayesian methods. This paper compares the localization performance of the proposed method with the performance of the extended Kalman filter to verify the feasibility of the proposed method. Measurements of ranges from beacons of ultrasonic satellite to the robot are used for localization. Mahalanobis distance is used for detection and rejection of outlier in the measurements. The optimization method sets performance index as a function of the measured range values, and finds the optimized estimation of the location through iteration. The method can improve the localization performance and reduce the computation time in corporation with Bayesian filter which provides proper initial location for the iteration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.721-730
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• 2012

In this paper the problem of a moving control of an automatic guided vehicle(AGV) which transports a dead body to a designated cinerator safely in a crematorium, an special indoor environment, will be discussed. Since a method of burying guided lines in the floor is not proper to such an environment, a method of moving control of an AGV based on infrared ray sensors is now proposed. With this approach, the AGV emits infrared ray to the landmarks adheres to the ceiling to find a moving direction and then moves that direction by recognizing them. One of the typical problems for this method is that dead zone and/or overlapping zone may exist when the landmarks are deployed. To resolve this problem, an algorithm of recognizing double landmarks at each time is applied to minimize occurrences of sensing error. In addition, at the turning area to entering the designated cinerator, to fit an AGV with the entrance of the designated cinerator, an algorithm of controlling the velocity of both the inner and outer wheel of it. The functional correctness of our proposed algorithm has been verified by using a prototype vehicle. Our real AGV system has been applied to a crematorium and it moves automatically within an allowable range of location error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.446-452
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• 2020

As the use of children's school buses increases, accidents caused by the negligence of school bus drivers and ride carers have also increased significantly. To prevent such accidents, the government is coming up with various policies. We propose an accident prevention and safety management system for children's school buses. Through this system, bus drivers can easily check whether each child is seated and whether the seat belt is used, so it is possible to quickly respond to children's conditions while driving. With the ability to recognize faces by analyzing camera images, children can use a seat belt that is automatically adjusted to their height. It is therefore possible to prevent secondary injuries that may occur in the event of a traffic accident. In addition, a sleeping child-check system is provided to confirm that all children get off the bus, and a text service is provided to inform parents of their children's locations in real time. Based on Raspberry Pi, the system is implemented with cameras, pressure sensors, motors, Bluetooth modules, and so on. This proposed system was attached to a bus model to confirm that the series of functions work correctly.