Related Work

Automatic and autonomous reconstruction of environments has received much attention for several years. Some groups have attempted to build 3D volumetric representations of environments with 2D laser range finders. Thrun et al. (12,25,15), Früh et al. (10) and Zhao et al. (26) use two 2D laser range finder for acquiring 3D data. One laser scanner is mounted horizontally and one is mounted vertically. The latter one grabs a vertical scan line which is transformed into 3D points using the current robot pose. Since the vertical scanner is not able to scan sides of objects, Zhao et al. use two additional vertical mounted 2D scanner shifted by $45^\circ$ to reduce occlusion (26). The horizontal scanner is used to compute the robot pose. The precision of 3D data points depends on that pose and on the precision of the scanner. A few other groups use 3D laser scanners (21,2,13). A 3D laser scanner generates consistent 3D data points within a single 3D scan. The RESOLV project aimed to model interiors for virtual reality and tele presence (21). They used a RIEGL laser range finder on robots and the ICP algorithm for scan matching (5). The AVENUE project develops a robot for modeling urban environments (2), using a CYRAX laser scanner and a feature based scan matching approach for registration of the 3D scans in a common coordinate system (22). The research group of M. Hebert reconstruct environments using the Zoller+Fröhlich laser scanner and aim to build 3D models without initial position estimates, i.e., without odometry information (13).