用体素地图统一建模与估计，清晰推导紧耦合激光惯性里程计。
On the Derivation of Tightly-Coupled LiDAR-Inertial Odometry with VoxelMap
- 基于体素地图在误差状态卡尔曼滤波中构建几何与概率统一框架
- 通过一致符号与显式公式实现系统级推导，无新算法但逻辑严密
- 适合想深入理解紧耦合系统原理的开发者与研究者
本文在迭代误差状态卡尔曼滤波框架下，为紧耦合激光-惯性里程计提供了一个简洁的数学推导，采用体素地图（VoxelMap）表示。不同于提出新算法，本工作旨在通过一致的符号和明确的公式表达，统一几何建模与概率状态估计，使系统架构与估计算法原理更加清晰。文档可作为技术参考，也适合作为理解该类系统基础原理的入门材料。
原文摘要 · Abstract (English)
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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