Adaptive Denoising-Enhanced LiDAR Odometry for Degeneration Resilience in Diverse Terrains

The flexibility of simultaneous localization and mapping (SLAM) algorithms in various environments has consistently been a significant challenge. To address the issue of LiDAR odometry drift in high-noise settings, integrating clustering methods to filter out unstable features has become an effectiv...

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Vydané v:	IEEE transactions on instrumentation and measurement Ročník 73; s. 1 - 15
Hlavní autori:	Ji, Mazeyu, Shi, Wenbo, Cui, Yujie, Liu, Chengju, Chen, Qijun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	3-D LiDAR odometry Adaptive algorithms Algorithms ambient skeleton Cloud computing Clustering Degeneration degeneration scene detection diverse terrains Feature extraction Heuristic algorithms Laser radar Lidar Odometry Point cloud compression point cloud segmentation Simultaneous localization and mapping Three-dimensional displays
ISSN:	0018-9456, 1557-9662
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