• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1771-1774
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• 2005

Recently, RFID has become popular in the field of remote sensing applications. Location awareness is one of the most important keys to deploying RFID for advanced object tracking. Generally, multiple reference RF stations or additional sensors are used for the location sensing with RFID, but, particularly in indoor environments, spatial layout and cost problems limit the applicability of those approaches. In this paper, we propose a novel method for location sensing with active RFID systems not requiring the need for reference stations or additional sensors. The system triangulates the position of RF signal source using the signal pattern of the loop antenna connected to the power detector. The power detector consists of a signal strength detector and a signal analysis unit. The signal analysis unit indicates the signal strength and serial number using the signal from the strength detector, and provides the direction of the signal to the application target. We designed three different signal analysis units depending on the threshold type. The developed system can sense the direction to the transponder located over 10 m away within the maximum error of $5^{\circ}$. It falls within a reasonable range in our normal office environment.

• Journal of IKEEE
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• v.19 no.2
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• pp.160-167
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• 2015

We present an experimental implementation of the inexpensive microwave security sensor that can detect both static and slowly moving objects in cluttered environment. The prototype consists of a frequency-modulated continuous wave radar sensor, control board or computer and software. The prototype was tested in a cluttered indoor environment. In case of intrusion or change of environment the sensor will give an alarm, determine the location of new object, change in its location and can detect a slowly moving target. To make a low-cost unit we use commercially available automotive radar and own signal processing techniques for object detection and tracking. The intruder detection is based on a comparison between current 'image' in memory and 'no-intrusion' reference image. The main challenge is to develop a reliable technique for detection of a relatively low-magnitude object signals hidden in multipath clutter echo signals. Various experimental measurements and computations have shown the feasibility and performance of the system.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.121-130
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• 2009

In this paper, Gaussian probability distribution model based multi-sensor data fusion algorithm is proposed for a vehicular location awareness system. Conventional vehicular location awareness systems are operated by GPS (Global Positioning System). However, the conventional system is not working in the indoor of building or urban area where the receiver is difficult to receive the signal from satellites. A method which is combined GPS and UWB (Ultra Wide-Band) has developed to improve this problem. However, vehicular is difficult to receive seamless location information since the measurement systems by both GPS and UWB convert the vehicle's movement information separately at each sensor. In this paper, normalized probability distribution model based Hybrid UWB/GPS is proposed by utilizing GPS location data and UWB sensor data. Therefore the proposed system provides information with seamless and location flexible properties. The proposed system tested by Ubisense and Asen GPS in the $12m{\times}8m$ outdoor environments. As a result, the proposed system has improved performance for accurateness and connection ability between devices to support various CNS (Car Navigation System).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.246-253
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• 2010

In this paper, a method of removing the space skew and cross-talk cancellation is proposed where the self-generated signals from the subject are used to obtain the subject's location. In the proposed method, the good spatial sound image is maintained even when the listener moves from the sweet spot. Two major parts of the proposed method are as follows: listener position tracking using the stimuli from the subject and removal of the space skew and cross-talk signals. Listener position tracking is achieved by estimation of the time difference of arrival (TDoA). The position of the listener is then computed using the Talyer-series estimation method. The head-related transfer functions (HRTF) are used to remove the space skew and cross-talk signals, where the direction of the HRTF is given by the one estimated from the listener position tracking. The performance evaluation is carried out on the signals from the 100 subjects that are composed of the 50 female and 50 male subjects. The positioning accuracy is achieved by 70%~90%, under the condition that the mean squared positioning error is less than $0.07m^2$. The subjective listening test is also conducted where the 27 out of the 30 subjects are participated. According to the results, 70% of the subjects indicates that the overall quality of the reproduced sound from the proposed method are improved, regardless of the subject's position.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.6
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• pp.531-539
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• 2013

Fingerprinting technique uses the radio signal strength measured reference locations is typically used, although there are many Wi-Fi based location tracking techniques. However, it needs numerous reference locations for precision and accuracy. This paper the analyzes problems of previous techniques and proposes a fingerprinting system using reliability based on a signal strength map. The system collects the signal strength data from a number of reference locations designated by the developer. And then it generates path-loss models to one of the access points for each reference location. These models calculate the predicted signal strength and reliability for a lattice. To evaluate proposed method and system performance, We perform experiments in a $20m{\times}22m$ real indoor environment installed access points. According to the result, the proposed system reduced distance error than RADAR. Comparing the existing system, it reduced about 1.74m.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.1141-1144
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• 2005

본 논문은 실내에서 홈 거주자의 위치를 인식하기 위해 근접성을 이용한 위치 추적 시스템 환경을 제안하고자 한다. 이를 위해 기존 실내의 고정된 위치에 있는 구조/시설물 및 가전제품의 ON/OFF 스위치를 이용하며 기타 추가적인 스위치 및 센서를 부착하여 개폐동작이 일어날 때 발생되는 신호를 검출하여 실제위치를 얻는다. 발생되는 신호는 Pull-up 저항을 이용한 신호 검출 방법으로 눌려진 스위치나 센서에서 발생된 아날로그 신호를 검출한다. 검출된 신호의 고유한 ID값은 Sensor TMO로 송신되어 수집된다. 수집된 센서ID는 소켓통신을 이용하여 홈서버인 실내위치추적시스템으로 보내질 뿐아니라 원격 모니터링 GUI를 통해 실내 거주자의 위치를 GUI의 가상공간 좌표와 매핑된 홈 거주자의 위치를 보인다. 본 논문에서 제안한 실내위치추적시스템은 홈 거주자의 위치를 주기적으로 모니터링하고 거주자의 이동 패턴과 활동 상황을 파악하여 헬스케어 정보로 활용할 예정이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.83-85
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• 2016

위치측위 시스템들이 발전함에 따라 실내에서도 다양한 방법으로 신뢰성이 높은 실내 위치측위 시스템들이 보편화되고 있는 추세이다. 허나 기술의 한계점으로 지구자기장을 활용한 새로운 기술이 연구되고 있음에도 불구하고, 위 기술 또한 기존 기술들과는 다른 한계점이 존재한다. 이에 따라 본 논문에서는 각각의 기술점의 한계점을 해소하기 위해서 기존 실내측위 시스템과 새롭게 개발 중인 실내 측위 시스템을 혼합하여 외부장비의 의존도를 낮추고 신뢰성 높은 위치측위를 지속적으로 제공할수 있는 혼합형 실내 위치측위 시스템을 제안하고자 한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.198-204
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• 2007

In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.422-428
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• 2008

In this paper, we propose the robust object detection algorithm with spatial gradient information. To do this, first, we eliminate error values that appear due to complex environment and various illumination change by using prior methods based on hue and intensity from the input video and background. Visible shadows are eliminated from the foreground by using an RGB color model and a qualified RGB color model. And unnecessary values are eliminated by using the HSI color model. The background is removed completely from the foreground leaving a silhouette to be restored using spatial gradient and HSI color model. Finally, we validate the applicability of the proposed method using various indoor and outdoor conditions in a complex environments.