Weighted Conformal LiDAR-Mapping for Structured SLAM

One of the main challenges in Simultaneous Localization and Mapping (SLAM) is real-time processing. High computational loads linked to data acquisition and processing complicate this task. This paper presents an efficient feature extraction approach for mapping structured environments. The proposed methodology, Weighted Conformal LiDAR-Mapping (WCLM), is based on the extraction of polygonal profiles and propagation of uncertainties from raw measurement data. This is achieved using conformal Möbius transformation. The algorithm has been validated experimentally using 2D data obtained from a low cost LiDAR range finder. The results obtained suggest that computational efficiency is significantly improved with reference to other state-of-the-art SLAM approaches.