Fast position tracking of an autonomous vehicle in cluttered and dynamic indoor environments

This paper deals with map-based self-localization in a dynamic environment. In order to detect localization features, laser range finders traditionally scan a horizontal plane: we hypothesize the existence of a "low frequency cross-section" (informally, over people heads), where even highly dynamic environments become more "static" and "regular". We show that, by accurately choosing the scanning plane, problems related to moving objects, occluded features, etc. are simplified. Experimental results showing hours of continuous work in a real-world scenario, with an accuracy of about 2.5cm and a speed of 0.6m/sec, demonstrate the reliability of the approach