High-speed and accurate laser scan matching using classified features

Laser scan matching algorithm plays a key role in robot localization and mapping. In this paper, we propose a classified feature-based algorithm that matches laser scans in a closed-form manner called Classified Feature-based Scan Matcher (CFSM). Based on a geometric observation, our classified features are defined as rotational features and translational features separately to improve matching accuracy. Experimental results demonstrate that CFSM can produce better accuracy for scans with large angular displacement, without increasing running time. Indoor robot can take advantage of this algorithm in performing fast and accurate pose estimation.