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

Robotics 2026-04-22 v2 Signal Processing

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.

Keywords

Cite

@article{arxiv.2603.15471,
  title  = {On the Derivation of Tightly-Coupled LiDAR-Inertial Odometry with VoxelMap},
  author = {Zhihao Zhan},
  journal= {arXiv preprint arXiv:2603.15471},
  year   = {2026}
}