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On the Derivation of Tightly-Coupled LiDAR-Inertial Odometry with VoxelMap

Zhihao Zhan

arXiv:2603.15471Published March 16, 2026Updated April 21, 20260 citations
  • cs.RO
  • eess.SP

Abstract

This note presents a concise mathematical formulation of tightly-coupled LiDAR-Inertial Odometry within an iterated error-state Kalman filter framework using a VoxelMap representation. Rather than proposing a new algorithm, it provides a clear and self-contained derivation that unifies the geometric modeling and probabilistic state estimation through consistent notation and explicit formulations. The document is intended to serve both as a technical reference and as an accessible entry point for a foundational understanding of the system architecture and estimation principles.

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