Mobile robot localization: integrating measurements from a time-of-flight laser

This paper presents an algorithm for environment mapping by integrating scans from a time-of-flight laser and odometer readings from a mobile robot. The range weighted Hough transform (RWHT) is used as a robust method to extract lines from the range data. The resulting peaks in the RWHT are used as feature coordinates when these lines/walls are used as landmarks during navigation. The associations between observations over the time sequence are made in a systematic way using a decision directed classifier. Natural geometrical landmarks are described in the robot frame together with a covariance matrix representing the spatial uncertainty. The map is thus built up incrementally as the robot moves. If the map is given in advance, the robot can find its location and navigate relative to this a priori given map. Experimental results are presented for a mobile robot with a scanning range measuring laser having 2-cm resolution. The algorithm was also used for an autonomous plastering robot on a construction site. The sensor fusion algorithm makes few erroneous associations