• KIPS Transactions on Computer and Communication Systems
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• v.2 no.10
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• pp.427-436
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• 2013

In this paper, a method of moving path control of an automatic guided vehicle in an indoor environment through recognition of marker images using vision sensors is presented. The existing AGV moving control system using infrared-ray sensors and landmarks have faced at two critical problems. Since there are many windows in a crematorium, they are going to let in too much sunlight in the main hall which is the moving area of AGVs. Sunlight affects the correct recognition of landmarks due to refraction and/or reflection of sunlight. The second one is that a crematorium has a narrow indoor environment compared to typical industrial fields. Particularly when an AVG changes its direction to enter the designated furnace the information provided by guided sensors cannot be utilized to estimate its location because the rotating space is too narrow to get them. To resolve the occurrences of such circumstances that cannot access sensing data in a WSN environment, a relative distance from marker to an AGV will be used as fingerprinting used for location estimation. Compared to the existing fingerprinting method which uses RSS, our proposed method may result in a higher reliable estimation of location. Our experimental results show that the proposed method proves the correctness and applicability. In addition, our proposed approach will be applied to the AGV system in the crematorium so that it can transport a dead body safely from the loading place to its rightful destination.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.10
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• pp.58-66
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• 2008

In the development of intelligent vehicles, path tracking of unmanned vehicle is a basis of autonomous driving and automatic navigation. It is very important to find the exact position of a vehicle for the path tracking, and it is possible to get the position information from GPS. However the information of GPS is not the current position but the past position because a vehicle is moving and GPS has a time delay. In this paper, therefore, the moving distance of a vehicle is estimated using a direction sensor and a velocity sensor to compensate the position error of GPS. In the steering control, optimal fuzzy rules for the path tracking can be found through the simulation of Simulink. Real driving experiments show the fuzzy rules are good for the steering control and the position error of GPS is well compensated by the proposed estimation method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.143-148
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• 2022

It is very important for metaverse, mobile robot, and user location services to analyze the images continuously taken using a mobile smartphone or robot's monocular camera to estimate the camera's location. So far, PnP-related techniques have been applied to calculate the position. In this paper, the camera's moving direction is obtained using the essential matrix in the epipolar geometry applied to successive images, and the camera's continuous moving position is calculated through geometrical equations. A new estimation method was proposed, and its accuracy was verified through simulation. This method is completely different from the existing method and has a feature that it can be applied even if there is only one or more matching feature points in two or more images.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.281-289
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• 2000

While acquiring images, the relative motion between the imaging device and the object scene seriously damages the image quality. This phenomenon is called motion blur. The peak-trace approach, which is our recent previous work, identifies important parameters to characterize the point spread function (PSF) of the blur, given only the blurred image itself. With the peak-trace approach the direction of the motion blur can be extracted regardless of the noise corruption and does not need much Processing time. In this paper stochastic peak-trace approaches are introduced. The erroneous data can be selected through the ML classification, and can be made small through weighting. Therefore the distortion of the direction in the low frequency region can be prevented. Using the linear prediction method, the irregular data are prohibited from being selected as the peak point. The detection of the second peak using the proposed moving average least mean (MALM) method is used in the Identification of the motion extent. The MALM method itself includes a noise removal process, so it is possible to extract the parameters even an environment of heavy noise. In the experiment, we could efficiently restore the degraded image using the information obtained by the proposed algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.121-131
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• 2015

Passive emitter localization is preferred to use a small number of receivers as possible for the efficiency of strategic management in the field of modern electronic warfare support. Accurate emitter localization can be expected when utilizing continuous measurable parameters and a appropriate combination of theirs. For this reason, we compare CRLB (Cramer-Rao lower bound) of two moving platform with various measurable parameters to choose a appropriate combination of parameters for a better localization performance. And we propose the passive emitter localization method based on Levenberg-Marquardt algorithm with combined TDOA/FDOA and DOA to achieve better accuracy of emitter localization which is located on the ground and stationary. In addition, we present a method for determining the initial emitter position for LM algorithm's input to avoid the divergence of estimation and local minimum.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.10
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• pp.1-8
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• 2000

In this paper, positioning schemes based on AOA(Angle of Arrival), TOA(Time of Arrival), and TDOA(Time Difference of Arrival) measurements are reviewed and analyzed. In the case of using those schemes in microcell structure with severe multipath fading and shadowing conditions, the rapid and unpredictable variation of signal level makes it difficult to estimate the position and velocity of mobiles. Therefore, we propose a novel mobile tracking method based on the multicriteria decision making, in which uncertain parameters such as RSS(Received Signal Strength), the distance between mobile and base station, the moving direction, and the previous location are participated in the decision process using aggregation function in fuzzy set theory. Through a simulation, we analysis the impaction of the frequent change of direction and speed of mobiles.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10A
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• pp.1512-1520
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• 2000

The wireless communication network is evolving toward IMT-2000 for providing various multimedia services. In order to accomplish this ultimate goal the effective schemes are required which can dynamically utilize the limited wireless resources based on different traffic characteristics of various services. This paper proposes a novel bandwidth allocation and call admission control scheme to transmit multimedia traffic based on the bandwidth reservation procedure using direction estimation in the IMT-2000 This scheme estimates the position of mobiles based on the mliticriteria decision making in which uncertain parameters such as RSS(Received Signal Strength), the distance between mobile and base station the moving direction and the previous location are participated in the decision process using aggregation function in fuzzy set theory. Its effectiveness is investigated by simulation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.341-345
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• 2009

We present an augmented reality (AR) application for cell phone where users put a virtual pet on their palms and play/interact with the pet by moving their hands and fingers naturally. The application is fundamentally based on hand/palm pose recognition and finger motion estimation, which is the main concern in this paper. We propose a fast and efficient hand/palm pose recognition method which uses natural features (e.g. direction, width, contour shape of hand region) extracted from a hand image with prior knowledge for hand shape or geometry (e.g. its approximated shape when a palm is open, length ratio between palm width and pal height). We also propose a natural interaction method which recognizes natural motion of fingers such as opening/closing palm based on fingertip tracking. Based on the proposed methods, we developed and tested the AR application on an ultra-mobile PC (UMPC).

• Journal of the Korean housing association
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• v.12 no.3
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• pp.109-116
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• 2001

Street is an important factor that street quality determines urban quality as the space of the high public nature in city. The research method considering sequence landscape is important because it is considered that the impression of such a street is formed by the wholeness of consecutive landscape and experience in moving street. Therefore, this study are pursued to structure the analysis of psychological evaluation and environmental attribute base on the physical characteristics of sequence landscape to supply the basic materials for seeking the national direction as qualitative improvement of urban street space and the attractive urban street space. Then the results are as follows. It is shown that the psychological evaluation structure of sequence landscape is evaluated by ornamental nature, intimacy, orderliness, openness and movability and that of environmental attributes is evaluated by four factors such as activity, intimacy, spatial attribute and openness.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.53-58
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• 2023

In general, in order to operate an autonomous underwater vehicle (AUV) in an underwater environment, a navigation system such as a Doppler Log (DVL) using a Doppler phenomenon of ultrasonic waves is used for speed and direction estimation. However, most of the ultrasonic sensors in underwater is large for long-distance sensing and the cost is very high. In this study, not only canal neuromast on the fish's lateral lines but also superficial neuromast are studied on the simulation to obtain pressure values for each pressure sensor, and the obtained pressure data is supervised using spherical CNN. To this end, through supervised learning using pressure data obtained from a pressure sensor attached to an underwater vehicle, we can estimate the speed and angle of the underwater vehicle in a quasi-static underwater environment and propose a method for a non-ultrasonic based navigation system.