• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1606-1611
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• 2005

The goal of this paper is to develop a self localization of mobile robot using UHF RFID landmark. We present landmark, a location sensing archetype system that uses UHF Radio Frequency Identification (UHF RFID) technology for locating objects inside buildings. The major advantage of landmark is that it improves the overall accuracy of locating objects by utilizing the concept of reference tags. Based on experimental analysis, we demonstrate that passive UHF RFID is a viable and cost-effective candidate for indoor location sensing. We conduct a series of experiments to evaluate performance of the positioning of the landmark System. In the standard setup, we place RF Reader which has two antennas and 25 tags in our lab. This research uses the assumption-based coordinates (ABC) algorithm[3] for determining the localization of robot. Also, we show how Radio Frequency Identification (UHF RFID) can be used in robot-assisted indoor navigation for the visually impaired. The experiments illustrate that passive UHF RFID tags can act as reliable landmark that trigger local navigation behaviors to achieve global navigation objectives.

• 제어로봇시스템학회논문지
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• 제21권5호
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• pp.490-495
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• 2015

As flying robots are becoming popular, there are increased needs to use themforsuch purposes as parcel delivery, serving in restaurants, and stage performances. To control flying robots such as quad copters, localization is essential. In order to properly position flying robots, many techniques are in development, including IR (infra-red)-based systemswhich catch markers on a flying robot in order that it can position itself. However, this technique demonstrates only short coverage. Furthermore, localization from inertial sensors diverges as time passes. For this reason, this paper suggests a TWR (two-way ranging) based positioning technique. Despite the weaknesses in currently available TWR system, this paper suggests a self-positioning and outlier detection technique in order to provide reliable position information with a faster update rate. The self-positioning system sends a shorter message which reduces wireless traffic. By detecting and removing outlier measurements, a positioning result with better accuracy is acquired. Finally, this paper shows that the suggesting system detects outlierssequentially from less than half the number of anchors in localization system according to the degree of outlier in measurement and the noise level. By performing an outlier algorithm, better positioning accuracy is acquired as shown in the experimental result.

• 동력기계공학회지
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• 제17권5호
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• pp.100-111
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• 2013

Indoor real-time positioning for multiple targets is required to realize human-robot symbiosis. This study firstly presents positioning accuracy on an autonomous mobile robot controlled by 3-D coordinates that is obtained by a real-time indoor positioning system with spread spectrum (SS) ultrasonic signals communicated by code-division multiple access. Although many positioning systems have been investigated, the positioning system with the SS ultrasonic signals can measure identified multiple 3-D positions in every 70 ms with noise tolerance and error within 100 mm. This system is also robust to occlusion and environmental changes. However, thus far, the positioning errors in an autonomous mobile robot, controlled by these systems using the SS ultrasonic signals, have not been evaluated as an experimental study. Therefore, a positioning experiment for trajectory control is conducted using an autonomous mobile robot and our positioning system. The effectiveness of this positioning method for robot self-localization is shown, from this experiment, because the average control error between the target position and the robot's position at 29 mm is obtained.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2301-2306
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• 2005

Even if there are lots of researches on localization using 2D range finder in static environment, very few researches have been reported for robust real-time localization of mobile robot in uncertain and dynamic environment. In this paper, we present a new localization method based on ICP(Iterative Closest Point) algorithm for navigation of mobile robot under dynamic or uncertain environment. The ICP method is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. We use the method to align global map with 2D scanned data from range finder. The proposed algorithm accelerates the processing time by uniformly sampling the line fitted data from world map of mobile robot. A data filtering method is also used for threshold of occluded data from the range finder sensor. The effectiveness of the proposed method has been demonstrated through computer simulation and experiment in an office environment.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.934-937
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• 2003

In this paper, authors use a stereo vision system based on the visual model of human and establish inexpensive method that recognizes moving distance using characteristic points around the robot. With the stereovision. the changes of the coordinate values of the characteristic points that are fixed around the robot are measured. Self-displacement and self-localization recognition system is proposed from coordination reconstruction with those changes. To evaluate the proposed system, several characteristic points that is made with a LED around the robot and two cheap USB PC cameras are used. The mobile robot measures the coordinate value of each characteristic point at its initial position. After moving, the robot measures the coordinate values of the characteristic points those are set at the initial position. The mobile robot compares the changes of these several coordinate values and converts transformation matrix from these coordinate changes. As a matrix of the amount and the direction of moving displacement of the mobile robot, the obtained transformation matrix represents self-displacement and self-localization by the environment.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.527-529
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• 2006

In this paper, we find a robot's path using a Virtual Reality Modeling Language and overlay vision. For correct robot's path we describe a method for localizing a mobile robot in its working environment using a vision system and VRML. The robt identifies landmarks in the environment, using image processing and neural network pattern matching techniques, and then its performs self-positioning with a vision system based on a well-known localization algorithm. After the self-positioning procedure, the 2-D scene of the vision is overlaid with the VRML scene. This paper describes how to realize the self-positioning, and shows the overlap between the 2-D and VRML scenes. The method successfully defines a robot's path.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.907-908
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• 2006

We describe a method for localizing a mobile robot in its working environment using a vision system and Virtual Reality Modeling Language (VRML). The robot identifies landmarks in the environment, using image processing and neural network pattern matching techniques, and then its performs self-positioning with a vision system based on a well-known localization algorithm. After the self-positioning procedure, the 2-D scene of the vision is overlaid with the VRML scene. This paper describes how to realize the self-positioning, and shows the overlap between the 2-D and VRML scenes. The method successfully defines a robot's path.

• 융합신호처리학회논문지
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• 제11권4호
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• pp.345-353
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• 2010

로봇의 대역적 자기 위치 추정에서의 일반적인 해법은 로봇의 자기 위치에서 복수의 가설을 생성하고, 관측된 랜드마크의 특정을 기초로 각 가설을 평가하여 가장 확실한 자기 위치를 구하는 것이다. 기존의 대표적인 방법인 ML이나 MCL은 랜드마크의 특징과 생성된 가설의 모든 조합을 평가하는 방법으로서 충분한 계산 자원에서는 최적의 방법이라 할 수 있다. 그러나, 일반적으로 계산량은 평가할 조합의 수에 비례하므로 다수의 조합이 존재하는 넓은 환경에서는 이러한 방법은 계산량이 아주 많아진다. 이러한 문제를 해결하기 위하여 본 논문에서는 확실하고 유망한 조합을 우선적으로 선택 평가하는 것으로, 계산시간을 효율적으로 이용하는 새로운 추정방법을 제안한다. 그 기본이 되는 방법으로는 RANSAC 알고리즘과 RANSAC 알고리즘의 효율화 방법인 Preemption scheme을 이용한다. 제안된 방법은 로봇이 관측할 때마다 계산량을 일정치 이하로 억제할 수가 있고, 또한 검증 실험에서 높은 추정 성능을 확인할 수 있었다.

• 제어로봇시스템학회논문지
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• 제12권5호
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• pp.480-488
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• 2006

Industrial and economical importance of CP(Cellular Phone) is growing rapidly. Combined with IT technology, CP is one of the most attractive technologies of today. However, unless we find a new breakthrough in the technology, its growth may slow down soon. RT(Robot Technology) is considered one of the most promising next generation technologies. Unlike the industrial robot of the past, today's robots require advanced features, such as soft computing, human-friendly interface, interaction technique, speech recognition object recognition, among many others. In this paper, we present a new technological concept named RCP (Robotic Cellular Phone) which integrates RT and CP in the vision of opening a combined advancement of CP, IT, and RT, RCP consists of 3 sub-modules. They are $RCP^{Mobility}$(RCP Mobility System), $RCP^{Interaction}$, and $RCP^{Integration}$. The main focus of this paper is on $RCP^{Mobility}$ which combines an autonomous navigation system of the RT mobility with CP. Through $RCP^{Mobility}$, we are able to provide CP with robotic functions such as auto-charging and real-world robotic entertainment. Ultimately, CP may become a robotic pet to the human beings. $RCP^{Mobility}$ consists of various controllers. Two of the main controllers are trajectory controller and self-localization controller. While the former is responsible for the wheel-based navigation of RCP, the latter provides localization information of the moving RCP With the coordinates acquired from RFID-based self-localization controller, trajectory controller refines RCP's movement to achieve better navigation. In this paper, a prototype of $RCP^{Mobility}$ is presented. We describe overall structure of the system and provide experimental results on the RCP navigation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권2호
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• pp.161-166
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• 2006

Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.