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This paper presents a mobile robot self localization method used to determine the position of the mobile robot Robucar. The localization approach is based on using both grids matching method and extended Kalman filter (EKF) method. The grids matching method provides accurate results but requires a large computational time that is why the EKF is introduced. EKF fuses odometric data and laser data to estimate the robot position. The developed algorithms are implemented and tested on the mobile robot Robucar.