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Mobile robot map building and localization are two fundamental tasks while they are working in indoor environment. With the 2D laser scanning data acquiring in real-time, a robot can calculate the area of the whole free space in a room, then it can select the room center as its position for omni-directional map building. Grid-based representation and least square algorithm are adopted to accomplish instant map building, which can reduce the redundant laser points effectively. With the mapping result, mobile robots can have a room structure as the prior knowledge. To make full use of the room outline information in scanning data matching, Metric-based Iterative Closest Point (MbICP) technique is utilized to obtain robot's observation. An EKF-based pose estimation approach is provided for a robot autonomous localization system in semi-structured indoor environment even if there exists moving disturbance. Experimental results are provided to demonstrate our method's validity and effectiveness.