Abstract
To create 3D volumetric maps of scenes with
autonomous mobile robots it is necessary to gage
several 3D scans and to merge them into one
consistent 3D model. This paper provides a new
solution to the simultaneous localization and
mapping (SLAM) problem with six degrees of
freedom. Robot motion on natural surfaces has to
cope with yaw, pitch and roll angles, turning pose
estimation into a problem in six mathematical
dimensions. A fast variant of the Iterative Closest
Points (ICP) algorithm registers the 3D scans in a
common coordinate system and relocalizes the
robot. Finally, consistent 3D maps are generated
using closing loop detection and a global
relaxation. Keywords: autonomous mobile robots, 3D
laser scanner, 3D scan matching, simultaneous
localization and mapping (SLAM), closing loop.
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