Visual–Inertial Combined Odometry System for Aerial Vehicles

The requirement to operate aircraft in GPS‐denied environments can be met by using visual odometry. Aiming at a full‐scale aircraft equipped with a high‐accuracy inertial navigation system (INS), the proposed method combines vision and the INS for odometry estimation. With such an INS, the aircraft orientation is accurate with low drift, but it contains high‐frequency noise that can affect the vehicle motion estimation, causing position estimation to drift. Our method takes the INS orientation as input and estimates translation. During motion estimation, the method virtually rotates the camera by reparametrizing features with their depth direction perpendicular to the ground. This partially eliminates error accumulation in motion estimation caused by the INS high‐frequency noise, resulting in a slow drift. We experiment on two hardware configurations in the acquisition of depth for the visual features: 1) the height of the aircraft above the ground is measured by an altimeter assuming that the imaged ground is a local planar patch, and 2) the depth map of the ground is registered with a two‐dimensional laser in a push‐broom configuration. The method is tested with data collected fr