• International Journal of Control, Automation, and Systems
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• 제2권4호
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• pp.485-493
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• 2004

Open-loop position estimation methods are commonly used in mobile robot applications. Their strength lies in the speed and simplicity with which an estimated position is determined. However, these methods can lead to inaccurate or unreliable estimates. Two position estimation methods are developed in this paper, one using a single optical flow sensor and a second using two optical sensors. The first method can accurately estimate position under ideal conditions and also when wheel slip perpendicular to the axis of the wheel occurs. The second method can accurately estimate position even when wheel slip parallel to the axis of the wheel occurs. Location of the sensors is investigated in order to minimize errors caused by inaccurate sensor readings. Finally, a method is implemented and tested using a potential field based navigation scheme. Estimates of position were found to be as accurate as dead-reckoning in ideal conditions and much more accurate in cases where wheel slip occurs.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.584-586
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• 2005

In this paper, low cost inertial sensor and compass were used instead of encoder for localization of mobile robot. Movements by encoder, movements by inertial sensor and movements by complementary filter with inertial sensor and compass were analyzed. Movement by complementary filter was worse than by only inertial sensor because of imperfection of compass. For the complementary filter to show best movements, compass need to be compensated for position error.

• 제어로봇시스템학회논문지
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• 제7권11호
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• pp.933-938
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• 2001

In this paper, we describe a method for the mobile robot using images of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot`s position. Since the equations are based on the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied to this method. Effectiveness of the proposed method is demonstrated by the simulation.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1279-1286
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• 1999

In conventional GPS/DR integration schemes, the GPS position (or pseudo-range) information is used in calibrating DR sensors. In those schemes, however, an inaccurate calibration may degrade the position accuracy when the GPS measurement is not available. This paper presents a new integration scheme where the GPS velocity information is used in calibrating DR sensors. Also proposed is a new error model of DR sensors for calibrating the bias error and the tilt error in dynamic environments. The proposed model makes it possible that the errors of both the DR sensor parameters and the velocity are calibrated using the GPS carrier-based velocity(or the pseudo-range rate) measurement while the DR position error is calibrated using the GPS position measurement. Since the DR sensors are calibrated accurately, the positioning accuracy is drastically improved when the GPS measurements are unavailable.

• 수산해양기술연구
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• 제20권2호
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• pp.105-111
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• 1984

추측항법과 Loran C 항법을 결합한 Hybrid 항법의 정도를 평가하기 위하여, 군산수산전문대학 실습선 전북 401, 403 호에 설치되어 있는 Hybrid항법장치를 이용하여 1982년 7월부터 1983년 6월 사이에 한국서해안 해역에서 실선관측을 행하여 그 측위의 정도를 Radar 위치와 비교.검토한 결과는 다음과 같다. 1. 9970, 5970 Chain의 Loran C 시간차의 표준편차는 각각 약 0.21$\mu$s, 약 0.06$\mu$s로 5970 Chain의 시간차 변동이 9970 Chain보다 적었다. 2. Hybrid위치와 Loran C 위치는 Radar 위치와의 편위거리가 각각 약 0.4 mile, 약 0.51 mile로서 Hybrid 항법이 Loran C 항법보다 정도가 더 높았다. 3. Hybrid 위치와 Loran C의 계산기 simulation 위치는 Radar 위치와의 위치거리가 각각 0.4 mille, dir 0.98 mile로 Hybrid 항법이 Loran C의 계산기 simulation 위치보다 정도가 더 높았으며, 추측위치의 미소한 변동에 대한 Loran C의 변위량을 보정하면 Loran C의 계산기 simulation 위치의 정도도 더 높일 수 있음을 알 수 있었다.

• 전자공학회논문지SC
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• 제47권6호
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• pp.33-42
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• 2010

본 연구에서는 실해역에서 해류를 고려한 실용적인 유도 시스템을 제안하고 있다. 본 논문에서는 생성된 경로의 최적성은 주요 이슈가 아니다. 시작점부터 목표점까지의 경로는 주요 해류의 방향축을 고려하여 운용 경험이 많은 전문가의 경유점 선택을 통하여 생성된다. 본 논문에서는 또한 초단기선, GPS, 도플러 속도계 그리고 자세센서 등의 계측치를 통해서 다중센서융합알고리즘을 이용하여 정밀 수중항법 솔루션 구현에 대하여 설명하고 있다. 정밀하고 정확하고 갱신 주기가 빠른 수중항법 솔루션을 구현하기 위하여 세 가지 전략을 사용하였다. 첫째는 추측항법의 단독 성능을 향상시키기 위하여 선수각 정밀 정렬을 수행하였다. 둘째는 기본이 되는 단독추측항법이 적분 알고리즘에 기반을 두었기 때문에 시간의 추이에 따른 누적오차의 증가 특성을 가지고 있는데 이를 막기 위하여 주기적으로 절대 위치 정보를 다중센서융합 기법을 이용하여 융합하여 주는 것이다. 셋째는 융합알고리즘의 품질 향상을 위하여 효율적인 특이점 제거 알고리즘을 도입하는 것이다. 개발된 정밀수중항법알고리즘의 성능을 검증하기 위하여 자율기뢰처리기와 심해무인잠수정의 실해역 데이터를 사용하였다.

• 전자공학회논문지B
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• 제33B권4호
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• pp.27-40
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• 1996

This paper proposed a kinematic modeling methodlogy and feedback control system based on kinematics for 2 degrees of freedom of 4-wheeled mobile robot. We assigned coordinate systems to specify the transformation matirx and write the kinematic equation of motion. We derived the actuated inverse and sensed forwared solution for the calculation of actual robot orientation and the desired robot orientation. It is the most significant error and has the largest impact on the motion accuracy. To calculate the WMR position in real time, we introduced the dead-reckoning algorithm and composed two feedback control system that is based on kinematics. Through the simulation result, we compare with the ffedback control system for position control.

• 제어로봇시스템학회논문지
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• 제13권9호
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• pp.875-882
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• 2007

In order for a vehicle to follow a predetermined trajectory accurately, its position must be estimated accurately and reliably. In this thesis, we propose trajectory tracking control methods for unmanned vehicle and a positioning system using ultrasonic wave. The positioning problem is an important part of control problem for unmanned navigation of a vehicle. Dead Reckoning is widely used for positioning of vehicle. However this method has problems because it accumulates estimation errors. We propose a new method to increase the accuracy of position estimation using the Ultrasonic Satellite System (USAT). It is shown that we will be able to estimate the position of vehicle precisely, in which errors are not accumulated. And proposed trajectory tracking control methods include both a new path planning method and a lateral control method for vehicle. The experimental results show that the proposed methods enables exact vehicle trajectory tracking even under various environmental factors.

• 제어로봇시스템학회논문지
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• 제11권5호
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• pp.398-405
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• 2005

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Also, the control method is proposed to estimate position and direction between the walking human and the mobile robot, and the Kalman filter scheme is used for the estimation of the mobile robot localization. And its performance is verified by the computer simulation and the experiment.

• 제어로봇시스템학회논문지
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• 제6권10호
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• pp.928-935
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• 2000

In order to improve the performance of a GPS/DR integration system, the error sources of DR sensors should be modeled accurately, This results in the increases in the dimension of the integration filter and, consequently, computational load becomes large. To reduce the computational load, suggested in this paper is a decoupled GPS/DR integration scheme that consists of two cascaded Kalman filters. The GPS velocity output is used in the first filter to calibrate the DR sensor and to fix the velocity as well. The velocity from the first filter is fed to the second filter where the position is corrected using the GPS position output. Experimental results show that the proposed integration scheme has positioning performance comparable to the conventional coupled one, while its computation is reduced to about 2/3.