Ground Segmentation for LiDAR Point Clouds in Structured and Unstructured Environments Using a Hybrid Neural–Geometric Approach

Ground Segmentation for LiDAR Point Clouds in Structured and Unstructured Environments Using a Hybrid Neural–Geometric Approach

Ground segmentation in LiDAR point clouds is a foundational capability for autonomous systems, enabling safe navigation in applications ranging from urban self-driving vehicles to planetary exploration rovers. Reliably distinguishing traversable surfaces in geometrically irregular or sensor-sparse e...

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Bibliographic Details
Main Authors: Antonio Santo, Enrique Heredia, Carlos Viegas, David Valiente, Arturo Gil
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Technologies
Subjects:
ground segmentation
LiDAR point clouds
annotation procedure
autonomous navigation
traversability estimation
Online Access:https://www.mdpi.com/2227-7080/13/4/162
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