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We propose a novel visual-inertial odometry approach that adopts structuralregularity in man-made environments. Instead of using Manhattan worldassumption, we use Atlanta world model to describe such regularity. An Atlantaworld is a world that contains multiple local Manhattan worlds with differentheading directions. Each local Manhattan world is detected on-the-fly, andtheir headings are gradually refined by the state estimator when newobservations are coming. With fully exploration of structural lines thataligned with each local Manhattan worlds, our visual-inertial odometry methodbecome more accurate and robust, as well as much more flexible to differentkinds of complex man-made environments. Through extensive benchmark tests andreal-world tests, the results show that the proposed approach outperformsexisting visual-inertial systems in large-scale man-made environments

StructVIO : Visual-inertial Odometry with Structural Regularity of Man-made Environments