2025/11/24 by Cerezo, Samuel, Lee, Seong Hun, Civera, Javier
Computer Science · Engineering · #Advanced Vision and Imaging #FOS: Computer and information sciences #Inertial Sensor and Navigation #Robotics (cs.RO) #Robotics and Sensor-Based Localization
paper · doi:10.48550/arxiv.2511.18910
openalex publication_date 2025/11/24 · openalex created_date 2025/11/27 · openalex updated_date 2026/07/28
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 4x shorter initialization windows and reducing computational cost by 5x.