칼만 필터를 이용한 이동 로봇의 간이 복합 항법 시스템 설계
A Design of a Simplified Hybrid Navigation System for a Mobile Robot by Using Kalman Filter
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초록
In this paper, a simple version of the hybrid navigation system using Kalman filter is proposed. The implemented hybrid navigation system is composed of a GPS to measure the position and the velocity, and a IMU(inertial measurement unit) to measure the acceleration and the posture of a mobile robot. A discrete Kalman filter is applied to provide the position of the robot by fusing both of the sensor data. When GPS signal is available, the navigation system estimates the position of the robot from the Kalman filter using position and velocity from GPS, and acceleration from IMU. During the interval until next GPS signal arrives, the system calculates the position of the robot using acceleration from IMU and velocity obtained at the previous step. Performance of the navigation system is verified by comparing the real path and the estimated path of the mobile robot. From experiments, we conclude that the navigation system is acceptable for the mobile robot.
Abstract
In this paper, a simple version of the hybrid navigation system using Kalman filter is proposed. The implemented hybrid navigation system is composed of a GPS to measure the position and the velocity, and a IMU(inertial measurement unit) to measure the acceleration and the posture of a mobile robot. A discrete Kalman filter is applied to provide the position of the robot by fusing both of the sensor data. When GPS signal is available, the navigation system estimates the position of the robot from the Kalman filter using position and velocity from GPS, and acceleration from IMU. During the interval until next GPS signal arrives, the system calculates the position of the robot using acceleration from IMU and velocity obtained at the previous step. Performance of the navigation system is verified by comparing the real path and the estimated path of the mobile robot. From experiments, we conclude that the navigation system is acceptable for the mobile robot.
참고문헌 (12)
- 김태윤, "라오-블랙웰라이즈드 입자필터를 이용한 지형참조 수중항법", 제어.로봇.시스템학회 논문지, 19(8), pp.682~687 (2013), 제어·로봇·시스템학회[DOI]
- 홍성표, "고속 수중운동체 정밀 유도제어를 위한 항법성능 분석", 한국정보통신학회논문지, 17(9), pp.2227~2232 (2013), 한국정보통신학회[DOI]
- 이정환, "GPS", INS센서 융합을 이용한 고 정밀 위치 추정에 관한 연구, 2012, pp.49(11), 159~166[DOI]
- 정재영, "파티클 필터를 이용한 GPS 위치보정과 GPS", INS 센서 결합에 관한 연구, 2013, pp.50(6), 267~275[DOI]
- 서원교, "이산 웨이블릿 변환과 Unscented 파티클 필터를 이용한 GPS-INS 결합 시스템의 실외 정밀 위치 추정", 전자공학회논문지 - SC, 48(6), pp.82~90 (2011), 대한전자공학회
- 박제두, "속도 측정치를 활용한 GPS", INS 통합 항법의 Lever arm 오차 보상, 2013, pp.41(6), 481~487[DOI]
- 조성윤, "다중속도 INS", GPS 결합항법시스템의 실시간 구현을 고려한 수정된 UKF, 2013, pp.19(2), 87~94[DOI]
- 전상운, "센서 융합기반의 추측항법을 통한 야지 주행 이동로봇의 위치 추정 및 제어", 대한임베디드공학회논문지, 4(2), pp.69~78 (2009), 대한임베디드공학회
- L.A. Cooney, "Dynamic Response Maneuvering Strategies of a Hybrid Autonomous Underwater Vehicle in Hovering", 석사, pp.2009
- C.K. Yang, "Performance Investigation of the Ensemble Kalman Filter for Tightly-coupled GPS", INS Integration, 2011, pp.40, 629~632
- 엄기환, "자율이동 로봇의 위치추정을 위한 변형된 칼만필터 방식", 한국정보통신학회논문지, 12(4), pp.781~790 (2008), 한국정보통신학회
- 윤득선, "확장형 칼만필터를 이용한 무인 자동차의 자율항법 최적화 알고리즘 개발", 한국자동차공학회 논문집, 16(3), pp.7~14 (2008), 한국자동차공학회