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arXiv · 2402.03376

Weighted Conformal LiDAR-Mapping for Structured SLAM

Natalia Prieto-Fernández·Sergio Fernández-Blanco·Álvaro Fernández-Blanco·José Alberto Benítez-Andrades·Francisco Carro-De-Lorenzo·Carmen Benavides
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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.

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Natalia Prieto-Fernández, Sergio Fernández-Blanco, Álvaro Fernández-Blanco, José Alberto Benítez-Andrades, Francisco Carro-De-Lorenzo, Carmen Benavides. 2024-02-03. Weighted Conformal LiDAR-Mapping for Structured SLAM. https://doi.org/10.1109/tim.2023.3284143

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