Mobile robot instant indoor map building and localization using 2D laser scanning data

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.