An Efficient Closed-Form Solution to Full Visual-Inertial State Initialization
Abstract
In this letter, we present a closed-form initialization method that recovers the full visual–inertial state without nonlinear optimization. Unlike previous approaches that rely on iterative solvers, our formulation yields analytical, easy-to-implement, and numerically stable solutions for reliable start-up. Our method builds on small-rotation and constant-velocity approximations, which keep the formulation compact while preserving the essential coupling between motion and inertial measurements. We further propose an observability-driven, two-stage initialization scheme that balances accuracy with initialization latency. Extensive experiments on the EuRoC dataset validate our assumptions: our method achieves 10−20% lower initialization error than optimization-based approaches, while using 4× shorter initialization windows and reducing computational cost by 5×.
Fields of Study & Subjects
Advanced Vision and Imaging
Adaptive optics and wavefront sensing
3D Shape Modeling and Analysis
Publication details
- Journal / source
- IEEE Robotics and Automation Letters
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 11
- Issue
- 6
- Pages
- 6919–6926
- Publication date
- 9 April 2026
- Language
- EN