On the Derivation of Tightly-Coupled LiDAR-Inertial Odometry with VoxelMap
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...
Description / Details
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.
Source: arXiv:2603.15471v1 - http://arxiv.org/abs/2603.15471v1 PDF: https://arxiv.org/pdf/2603.15471v1 Original Link: http://arxiv.org/abs/2603.15471v1
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Mar 17, 2026
Chemical Engineering
Engineering
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