Abstract
This paper presents a combination of a 3D laser sensor and a line-base SLAM algorithm which together produce 2D line maps of highly cluttered indoor environments. The key of the described method is the replacement of commonly used 2D laser range sensors by 3D perception. A straightforward algorithm extracts a virtual 2D scan that also contains partially occluded walls. These virtual scans are used as input for SLAM using line segments as features. The paper presents the used algorithms and experimental results that were made in a former industrial bakery. The focus lies on scenes that are known to be problematic for pure 2D systems. The results demonstrate that mapping indoor environments can be made robust with respect to both, poor odometry and clutter.
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