Geometry matters: Place recognition in 2D range scans using Geometrical Surface Relations

Place recognition is a fundamental requirement for mobile robots. It is particularly needed for detecting loop closures in SLAM and to enable self-localization for mobile robots given a prior map. The multitude of existing approaches rely on appearance based methods, e.g. the extraction of interest points in terms of local extrema. It can be observed that the availability of these features is highly environment specific and the limited descriptiveness causes a large number of false-positive matches. This paper utilizes a generic environment description based on normal surface primitives. The association of different places is done using Geometrical Surface Relations (GSR) of co-occurring primitives. Experimental results obtained from publicly available datasets demonstrate that GSR outperforms state-of-the-art approaches in place recognition for large scale outdoor as well as indoor environments.