다중센서 데이터 융합을 이용한 로봇 위치 추정 기법

A stable and precision position estimation algorithm is essential for outdoor mobile robots. Global Positioning System(GPS) is the most powerful measurement for localization but we cannot use them if the signals are blocked for several reasons. To overcome this limitation, we propose a position estimation method using multiple sensors. In this paper, we used multi-rate extended Kalman filter(EKF) algorithm with sensor data from GPS, wheel encoders, Inertial Measurement Unit(IMU) to estimate positions of a robot. And we verify our method with a outdoor mobile robot.