• 한국정밀공학회지
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• 제28권3호
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• pp.330-338
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• 2011

Odometry is the critical factor to estimate the location of the robot. In the mobile robot with wheels, odometry can be performed using the information from the encoder. However, the information of location in the encoder is inaccurate because of the errors caused by the wheel's alignment or slip. In general, visual odometer has been used to compensate for the kinetic errors of robot. In case of using the visual odometry under some robot system, the kinetic analysis is required for compensation of errors, which means that the conventional visual odometry cannot be easily applied to the implementation of the other type of the robot system. In this paper, the novel visual odometry, which employs only the single camera toward the ground, is proposed. The camera is mounted at the center of the bottom of the mobile robot. Feature points of the ground image are extracted by using median filter and color contrast filter. In addition, the linear and angular vectors of the mobile robot are calculated with feature points matching, and the visual odometry is performed by using these linear and angular vectors. The proposed odometry is verified through the experimental results of driving tests using the encoder and the new visual odometry.

• Journal of Positioning, Navigation, and Timing
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• 제6권1호
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• pp.17-26
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• 2017

Latency occurs in RTK, where the measured position actually outputs past position when compared to the measured time. This latency has an adverse effect on the navigation accuracy. In the present study, a system that estimates the latency of RTK and compensates the position error induced by the latency was implemented. To estimate the latency, the speed obtained from an odometer and the speed calculated from the position change of RTK were used. The latency was estimated with a modified correlator where the speed from odometer is shifted by a sample until to find best fit with speed from RTK. To compensate the position error induced by the latency, the current position was calculated from the speed and heading of RTK. To evaluate the performance of the implemented method, the data obtained from an actual vehicle was applied to the implemented system. The results of the experiment showed that the latency could be estimated with an error of less than 12 ms. The minimum data acquisition time for the stable estimation of the latency was up to 55 seconds. In addition, when the position was compensated based on the estimated latency, the position error decreased by at least 53.6% compared with that before the compensation.

• 한국가스학회:학술대회논문집
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• 한국가스학회 2001년도 추계학술발표회 논문집
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• pp.184-193
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• 2001

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 춘계학술대회 논문집
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• pp.671-679
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• 2011

Now, for the continuous location detection of train, The method which the moving distance and speed of vehicles are detected using an odometer mounted within railway vehicle, is used in railway domain generally. There are some problems that the train's positioning errors are accumulated as the moving distances increase. To solve this problems, The Train-borne Positioning System is being developed at Korea Railroad Research Institute. It is required to evaluate exactly a positioning performance of The Train-borne Positioning System for improvement of performance. Therefore, in this paper, we review the CDGPS methods to acquire reference position for performance evaluation of Train-borne Positioning System and verify the accuracy of the reference position through the static test and the vehicle test.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 춘계학술대회 논문집
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• pp.343-349
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• 2011

Now, for the continuous location detection of train, the method that the moving distance of a vehicle is detected using an wheel sensor(odometer) mounted within a train, is generally used. It has a problem that the positioning errors of a train can be accumulated as the moving distance increases. To solve this problem, it is required to apply a variety of positioning sensors and to integrate with sensor data. In this paper, we develop the train-borne positioning system applicable to the conventional railway and high-speed railway, and verify the performance of the train-borne positioning system through a vehicle test.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.713-716
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• 1991

This paper describes a methodology of mobile robot navigation which is designed to carry heavy payloads at high speeds to be used in FMS(Flexible Manufacturing System) without human control. Intelligent control scheme using fuzzy logic is applied to the navigation control. It analyzes sensor readings from multi-sensor system, which is composed of ultrasonic sensors, infrared sensors and odometer, for environment learning, planning, landmark detecting and system control. And it is implemented on a physical robot, AGV(Autonomous Guided Vehicle) which is a two-wheeled, indoor robot. An on-board control software is composed of two subsystems, i.e., AGV control subsystem and Sensor control subsystem. The results show that the navigation of the AGV is robust and flexible, and a real-time control is possible.

• 한국실천공학교육학회논문지
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• 제4권2호
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• pp.162-170
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• 2012

로봇이 수많은 작업을 수행하고 목표를 향해서 진행하기 위해서는 무엇보다 위치를 인식하는 것이 대단히 중요하다. 본 논문에서는 랜드 마크와 센서 네트워크 환경하에서 주행하는 로봇의 위치를 구별할 수 있는 위치 인식시스템을 제안한다. 전적으로 기본 지능형 로봇에 위치 인식 시스템과 환경 센서 모듈을 부가하여 구현하고, 이를 컴퓨터 시뮬레이션을 통해서 제안된 알고리즘이 합당함을 검증한다.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2004년도 GIS/RS 공동 춘계학술대회 논문집
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• pp.167-172
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• 2004

모바일 매핑시스템은 차량에 GPS(Global Positioning System), IMU(Inertial Measurement Unit), CCD 카메라 등을 탑재하고 공간 및 속성 정보를 취득하는 효율적인 방법이다. 모바일 매핑시스템은 도로 시설물 관리, 지도 갱신 등 다양한 분야에 이용되고 있다. 국외에서 개발된 모바일 매핑 시스템을 업그레이드하거나 새로운 센서를 추가 하고자 할 때 기존 시스템의 센서 통합 및 동기화 방안을 알 수 없으므로 시스템의 개선 및 향상이 어렵다. 본 연구에서는 모바일 매핑시스템의 개선 및 센서추가를 위해서 모바일 매핑시스템에 기본적으로 필요한 GPS, IMU, 그리고 CCD 카메라 등의 효율적인 통합 및 동기화 구현 방안을 제시하고, 동기화에 필요한 각 센서의 요구사항을 파악한 후 동기화 장비를 설계 및 제작하였다. 또한, 향후 추가될 센서인 레이져, 오도미터(Odometer) 등을 센서가 추가될 경우를 고려하여 통합장비를 설계하였다.

• Journal of Biosystems Engineering
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• 제33권6호
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• pp.423-429
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• 2008

This study was performed to investigate the effects of inertial navigation system (INS) / global positioning system (GPS) sensor fusion for agricultural vehicle navigation. An extended Kalman filter algorithm was adopted for INS/GPS sensor fusion in an integrated mode, and the vehicle dynamic model was used instead of the navigation state error model. The INS/GPS system was consisted of a low-cost gyroscope, an odometer and a GPS receiver, and its performance was tested through computer simulations. When measurement noises of GPS receiver were 10, 1.0, 0.5, and 0.2 m ($1{\sigma}$), RMS position and heading errors of INS/GPS system at 5 m/s straight path were remarkably reduced with 10%, 35%, 40%, and 60% of those obtained from the GPS receiver, respectively. The decrease of position and heading errors by using INS/GPS rather than stand-alone GPS can provide more stable steering of agricultural equipments. Therefore, the low-cost INS/GPS system using the extended Kalman filter algorithm may enable the self-autonomous navigation to meet required performance like stable steering or more less position errors even in slow-speed operation.

• 한국가스학회지
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• 제6권1호
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• pp.52-58
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• 2002

가스 배관 진단 시스템은 배관 내부에 투입되어 배관 내부의 여러 정보를 수집한다. 배관 진단을 위한 센서로는 배관 내부의 상태를 측정하는 캘리퍼(caliper) 센서와 온도, 압력센서가 있다. 그리고 정확한 위치 정보를 제공할 수 있는 IMU(Inertial Measurement Unit)와 주행 거리계를 사용하는 결합 항법 시스템도 필요하다. 본 논문에서는 가스 배관 진단시스템을 위한 항법 데이터 저장 시스템을 개발한다. 항법 데이터 저장 시스템은 실시간 동작을 위하여 마스터/슬레이브 구조를 가진다. 마스터 시스템은 항법 데이터를 저장하거나 통신하는데 사용하며 슬레이브 시스템은 센서 데이터를 처리한다. 개발된 항법 데이터 저장 시스템의 성능은 Pull Rig 실험을 통하여 검증한다.