Weighted Conformal LiDAR-Mapping for Structured SLAM
<|reference_start|>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 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.<|reference_end|>
@article{prieto-fernández2024weighted,
    title={Weighted Conformal LiDAR-Mapping for Structured SLAM},
    author={Natalia Prieto-Fern'andez, Sergio Fern'andez-Blanco, 'Alvaro
  Fern'andez-Blanco, Jos'e Alberto Ben'itez-Andrades, Francisco
  Carro-De-Lorenzo and Carmen Benavides},
    journal={IEEE Transactions on Instrumentation and Measurement, Volume 72,
  June 2023, 8504110},
    year={2024},
    doi={10.1109/TIM.2023.3284143},
    archivePrefix={arXiv},
    eprint={2402.03376},
    primaryClass={cs.RO}
}