Abstract
Recent advancements in the performance and affordability of cameras and inertial measurement units (IMUs) have caused demand for efficient, accurate visual-inertial navigation solutions. In this paper, we present a system for the fusion of preintegrated inertial measurements with highly informative direct alignment of images. In particular, our preintegration theory is based on closed-form solutions of the continuous-time IMU kinematic model, instead of discrete time. This allows for more accurate computation of preintegrated measurements and their uncertainty as well as bias Jacobians. These measurements are fused via graph-based methods with relative pose constraints obtained from direct image alignment from a stereo platform. The proposed system is validated on publicly-available real-world datasets.
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