Weighted Conformal LiDAR-Mapping for Structured SLAM
Abstract
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 article 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 M bius transformation. The algorithm has been validated experimentally using 2-D data obtained from a low-cost Light Detection and Ranging (LiDAR) range finder. The results obtained suggest that computational efficiency is significantly improved with reference to other state-of-the-art SLAM approaches.
Cite
@article{arxiv.2402.03376,
title = {Weighted Conformal LiDAR-Mapping for Structured SLAM},
author = {Natalia Prieto-Fernández and Sergio Fernández-Blanco and Álvaro Fernández-Blanco and José Alberto Benítez-Andrades and Francisco Carro-De-Lorenzo and Carmen Benavides},
journal= {arXiv preprint arXiv:2402.03376},
year = {2024}
}