关于基于VoxelMap的紧密耦合激光雷达-惯性里程计的推导
On the Derivation of Tightly-Coupled LiDAR-Inertial Odometry with VoxelMap
AI总结：
本文基于VoxelMap，推导了紧密耦合激光雷达-惯性里程计的数学模型，通过一致的符号和显式公式统一几何建模与概率状态估计。
摘要：
本文提出了在迭代误差状态卡尔曼滤波框架下，使用VoxelMap表示的紧密耦合激光雷达-惯性里程计的简洁数学推导。本文不提出新算法，而是提供清晰且自包含的推导，通过一致的符号和显式公式统一几何建模和概率状态估计。本文旨在作为技术参考和系统架构及估计原理的基础理解入口。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
