An Efficient Iterated EKF-Based Direct Visual-Inertial Odometry for MAVs Using a Single Plane Primitive

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This letter proposes an efficient visual-inertial estimator for aerial robots. The main contribution lies in the direct use of intensity measurements of the latest image frames and key frame via both continuous and regular homographic relations under an assumption of a single planar scene. The filter-based method provides comprehensive estimates of position and attitude with notable efficiency and robustness. The flight evaluation indicates that the incorporation of keyframes significantly minimizes the estimation drift while retaining accurate estimates of flight velocity. Compared to state-of-the-art methods, the proposed work provides rivalling performance at substantially lower computational cost by taking the advantage of the assumed single planar structure.