학술논문

Weighted Conformal LiDAR-Mapping for Structured SLAM
Document Type
Periodical
Source
IEEE Transactions on Instrumentation and Measurement IEEE Trans. Instrum. Meas. Instrumentation and Measurement, IEEE Transactions on. 72:1-10 2023
Subject
Power, Energy and Industry Applications
Components, Circuits, Devices and Systems
Simultaneous localization and mapping
Laser radar
Uncertainty
Feature extraction
Computational efficiency
Signal to noise ratio
Sensor phenomena and characterization
feature extraction
light detection and ranging (LiDAR)
simultaneous localization and mapping (SLAM)
weighted conformal mapping
Language
ISSN
0018-9456
1557-9662
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.