Self-localization is a fundamental requirement for the mobile robot. Robot usually contains a large number of dif- ferent sensors, which provide the information of robot localization, and all the sensor information should be considered for the optimal location. Kalman filter is efficient to realize the information fusion. Used as an efficient sensor fusion algorithm, Kalman filter is an advanced filtering technique which can reduce errors of the position and orientation of the sensors. Kalman filter has been paied much attention to robot automation and solutions to solve uncertainties such as robot localization, navigation, following, tracking, motion control, estimation and prediction. The paper briefly describes Kalman filter theory, and establishes a simple mathematical model based on muti-sensor mobile robot. Meanwhile, Kalman filter is used in robot self-localization by simulations, and it is demonstrated by simulations that Kalman filter is effective.
