FAST RANGE IMAGE SEGMENTATION FOR INDOOR 3D-SLAM

Real-time 3D localization and mapping is eventually needed in many service robotic applications. Toward a light and practical SLAM algorithm, we focus on feature extraction via segmentation of range images. Using horizontal and vertical traces of the range matrix, 2D observed polygons are considered for calculation of a one-dimensional measure of direction, called Bearing Angle (BA). BA is the incident angle between the laser beam and edges of the observed polygon by the scanner in the selected direction. Based on this measure, two different approaches to range image segmentation, region- and edge-based, are proposed and evaluated through a set of standard analysis. It is experimentally shown that for navigation applications, edge based approaches are more efficient. Extensive tests on real robots prove BA-based segmentation is successful for SLAM.