Abstract
This paper presents a method to improve the localization accuracy for visual inertial odometry (VIO) by combining the ultra-wideband (UWB) positioning technology. The overall architecture is mainly divided into two stages. In the first stage, the constraint on UWB short-term position change is adopted to improve the pose estimation results of the VIO system. It is also used to solve the translation error caused by the lack of visual features and vibration during the flight. In the second stage, a loose coupling method based on nonlinear optimization is utilized to fuse the local pose estimator of the VIO system with the global constraints from the UWB positioning. At the beginning of each optimization, the alignment between the VIO and UWB frames is estimated to avoid the influence of the coordinate transformation caused by the cumulative error of the VIO system. Since there are no public datasets available for comparison, we have established several datasets containing large vibration amplitudes and weak feature points. In the experiment, the performance evaluation of the proposed technique is carried out using the Apriltag approach for verification.
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