• 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.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권4호
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• pp.173-180
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• 2006

A key component of autonomous navigation of intelligent home robot is localization and map building with recognized features from the environment. To validate this, accurate measurement of relative location between robot and features is essential. In this paper, we proposed relative localization algorithm based on 3D reconstruction of scale invariant features of two images which are captured from two parallel cameras. We captured two images from parallel cameras which are attached in front of robot and detect scale invariant features in each image using SIFT(scale invariant feature transform). Then, we performed matching for the two image's feature points and got the relative location using 3D reconstruction for the matched points. Stereo camera needs high precision of two camera's extrinsic and matching pixels in two camera image. Because we used two cameras which are different from stereo camera and scale invariant feature point and it's easy to setup the extrinsic parameter. Furthermore, 3D reconstruction does not need any other sensor. And the results can be simultaneously used by obstacle avoidance, map building and localization. We set 20cm the distance between two camera and capture the 3frames per second. The experimental results show :t6cm maximum error in the range of less than 2m and ${\pm}15cm$ maximum error in the range of between 2m and 4m.

• 대한기계학회논문집A
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• 제34권2호
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• pp.183-189
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• 2010

위치인식시스템은 이동로봇이 실내에서 주행하는데 가장 중요한 기술의 하나인데 본 논문에서 연구된 시스템은 GPS 시스템과 유사하게 3 개이상의 위성 비이컨에서 초음파와 무선통신파를 발사하고 로봇에 부착된 리시버는 초음파와 무선통신파의 수신되는 시간차를 계산하여 각 비컨까지의 거리를 구하고 또한 이로부터 로봇의 위치를 계산한다. 일반적으로 거리정보는 초음파의 한 파장 이내의 오차를 가지게 되는데 본 논문에서는 이에 따른 위치오차를 테일러 확장과 SVD(Singular Value Decomposition)를 이용하여 구하였다. 또한 본 논문에서는 거리오차에 따른 위치오차의 정확도를 잴 수 있는 값으로 민감도를 제시하였다.

• 로봇학회논문지
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• 제11권3호
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• pp.127-132
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• 2016

For a practical mobile robot team such as carrying out a search and rescue mission in a disaster area, the localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a global positioning system (GPS) is unavailable. The proposed architecture supports localizing robots seamlessly by finding their relative locations while moving from a global outdoor environment to a local indoor position. The proposed schemes use a cooperative positioning system (CPS) based on the two-way ranging (TWR) technique. In the proposed TWR-based CPS, each non-localized mobile robot act as tag, and finds its position using bilateral range measurements of all localized mobile robots. The localized mobile robots act as anchors, and support the localization of mobile robots in the GPS-shadow region such as an indoor environment. As a tag localizes its position with anchors, the position error of the anchor propagates to the tag, and the position error of the tag accumulates the position errors of the anchor. To minimize the effect of error propagation, this paper suggests the new scheme of full-mesh based CPS for improving the position accuracy. The proposed schemes assuring localization were validated through experiment results.

• 로봇학회논문지
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• 제5권3호
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• pp.186-196
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• 2010

In this paper, we present a global localization and position error compensation method in a known indoor environment using magnet hall sensors. In previous our researches, it was possible to compensate the pose errors of $x_e$, $y_e$, ${\theta}_e$ correctly on the surface of indoor environment with magnets sets by regularly arrange the magnets sets of identical pattern. To improve the proposed method, new strategy that can realize the global localization by changing arrangement of magnet pole is presented in this paper. Total six patterns of the magnets set form the unique landmarks. Therefore, the virtual map can be built by using the six landmarks randomly. The robots search a pattern of magnets set by rotating, and obtain the current global pose information by comparing the measured neighboring patterns with the map information that is saved in advance. We provide experimental results to show the effectiveness of the proposed method for a differential drive wheeled mobile robot.

• 제어로봇시스템학회논문지
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• 제14권3호
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• pp.242-247
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• 2008

As an absolute positioning system, iGS is designed based on ultrasonic signals whose speed can be formulated clearly in terms of time and room temperature, which is utilized for a mobile robot localization. The iGS is composed of an RFID receiver and an ultra-sonic transmitter, where an RFID is designated to synchronize the transmitter and receiver of the ultrasonic signal. The traveling time of the ultrasonic signal has been used to calculate the distance between the iGS system and a beacon which is located at a pre-determined location. This paper suggests an effective operation method of iGS to estimate position of the mobile robot working in unstructured environment. To expand recognition range and to improve accuracy of the system, two strategies are proposed: utilization of beacons belonging to neighboring blocks and removal of the environment-reflected ultrasonic signals. As the results, the ubiquitous localization system based on iGS as a pseudo-satellite system has been developed successfully with a low cost, a high update rate, and relatively high precision.

• 제어로봇시스템학회논문지
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• 제12궈1호
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• pp.41-46
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• 2006

Ubiquitous location based services, offer helpful services anytime and anywhere by using real-time location information of objects based on ubiquitous network. Particularly, autonomous mobile robots can be a solution for various applications related to ubiquitous location based services, e.g. in hospitals, for cleaning, at airports or railway stations. However, a meaningful and still unsolved problem for most applications is to develop a robust and cheap positioning system. A typical example of position measurements is dead reckoning that is well known for providing a good short-term accuracy, being inexpensive and allowing very high sampling rates. However, the measurement always has some accumulated errors because the fundamental idea of dead reckoning is the integration of incremental motion information over time. The other hand, a localization system using RFID offers absolute position of robots regardless of elapsed time. We construct an absolute positioning system based on RFID and investigate how localization technique can be enhanced by RFID through experiment to measure the location of a mobile robot. Tags are placed on the floor at 5cm intervals in the shape of square in an arbitrary space and the accuracy of position measurement is investigated . To reduce the error and the variation of error, a weighting function based on Gaussian function is used. Different weighting values are applied to position data of tags since weighting values follow Gaussian function.

• 한국전자통신학회논문지
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• 제8권3호
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• pp.421-432
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• 2013

본 논문은 이동 로봇의 자율 주행을 위한 중요한 기술 중 하나인 위치 추정을 위한 함수 구현에 관해 서술되었다. 기존의 로봇 자율주행용 함수 라이브러리 중 일부는 모의실험에만 사용할 수 있기 때문에 실제 적용에 제한이 따른다. 본 논문은 실내 이동 로봇의 위치 추정을 위해 사용할 수 있는 함수의 개발에 중점을 두었다. 함수들은 추측항법, 이동 로봇의 운동 모델, 거리 측정 센서의 측정 모델, 그리고 빈번히 사용되는 방향 관련 연산에 대해 구현되었다. 구현된 함수들은 다양한 로봇과 센서에 적용할 수 있다. 사용자는 적절한 함수를 선택하여 로봇 운동과 센서 측정 불확실성의 다양한 유형을 구현할 수 있다. 구현된 함수들은 모의실험과 실제 실험을 통해 시험 및 증명되었다.

• 제어로봇시스템학회논문지
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• 제18권7호
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• pp.658-663
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• 2012

An accurate outdoor localization method using line/arc features is suggested for mobile robots with LRFs (Laser Range Finders) and odometry. Localization is a key process for outdoor mobile robots which are used for autonomous navigation, exploration and so on. In this paper, an accurate pose correction algorithm is proposed for mobile robots using LRFs, which use three feature types: line, circle, and arc. Using this method we can reduce the number of singular cases that robots couldn't find their pose. Finally we have got simulation results to validate the proposed algorithm.

• 제어로봇시스템학회논문지
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• 제19권5호
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• pp.468-472
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• 2013

This paper deals with the indoor localization problem for a SSMR (Skid Steering Mobile Robot) subjected to wheel-ground friction and with one LRF (Laser Range Finder). In order to compensate for some friction effect, a friction related coefficient is estimated by the recursive least square algorithm and appended to the maneuvering command. Also to reduce odometric information based localization errors, the lines are extracted with scan points of LRF and matched with the ones of the corresponding map built in advance. The present friction compensation and scan map matching schemes have been applied to a laboratory SSMR, and experimental results are given to validate the localization performance along an indoor corridor.