We present an algorithm for merging two partial maps obtained with a laser range scanner into a single map. The most

Abstract—Localization plays a significant role in the autonomous navigation of a mobile robot. This paper investigates mobile robot localization based on Extended Kalman Filter (EKF) algorithm and a feature based map. Corner angles in the environment are detected as the features, and the detailed processes of feature extraction are described. Then the motion model and odometry information are elaborated, and the EKF localization algorithm is presented. Finally, the experimental result is given to verify the feasibility and performance of the proposed localization algorithm. Keywords-EKF; localization; feature extraction; Odometry; motion model I.