DB-LIO: Database-Driven LiDAR–Inertial Odometry for Memory-Bounded Persistent Mapping

This paper proposes DB-LIO (database-driven LiDAR-inertial odometry), a simultaneous localization and mapping (SLAM) system that addresses memory scalability challenges in extended autonomous operation. Existing LiDAR-SLAM systems accumulate keyframe history in memory, leading to <inline-formula><ma...

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Autors principals:	Hun-Hee Kim, Ho-Hyun Kang, Dong-Hee Noh, Hea-Min Lee
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-05-01
Col·lecció:	Sensors
Matèries:	LiDAR-SLAM memory management spatial indexing LRU cache factor graph optimization sliding window
Accés en línia:	https://www.mdpi.com/1424-8220/26/10/3061
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