An Efficient Closed-Form Solution to Full Visual-Inertial State Initialization

Cerezo, Samuel (Universidad de Zaragoza) ; Lee, Seong Hun (Universidad de Zaragoza) ; Civera, Javier (Universidad de Zaragoza)

Resumen: 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×.

Idioma: Inglés

DOI: 10.1109/LRA.2026.3682536

Año: 2026

Publicado en: IEEE Robotics and Automation Letters 11, 6 (2026), 6919-6926
ISSN: 2377-3766

Financiación: info:eu-repo/grantAgreement/ES/AEI/PID2024-155886NB-I00
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2021-127685NB-I00
Financiación: info:eu-repo/grantAgreement/ES/MICINN PRE2022-103765

Tipo y forma: Artículo (PrePrint)

Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)