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 article presents an efficient feature extraction approach for mapping structured environments. The propose...

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Bibliographic Details
Published in:arXiv.org 2024-02
Main Authors: Prieto-Fernández, Natalia, Fernández-Blanco, Sergio, Fernández-Blanco, Álvaro, Benítez-Andrades, José Alberto, Carro-De-Lorenzo, Francisco, Benavides, Carmen
Format: Article
Language:English
Subjects:
Algorithms
Data acquisition
Feature extraction
Lidar
Range finders
Simultaneous localization and mapping
Online Access:Get full text
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Summary: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.
ISSN:2331-8422
DOI:10.48550/arxiv.2402.03376