Hybrid real-time stereo visual odometry for unmanned aerial vehicles

Abstract

A visual localization approach for unmanned aerial vehicles (UAVs) based on the hybrid real-time stereo visual odometry (VO) is presented. The hybrid VO initializes the semidirect visual odometry (SVO) with depth obtained from the stereo camera, which runs with the monocular scheme at 30 Hz. Meanwhile, a feature-based stereo VO runs in a parallel thread to improve the reliability. Considering the robustness of the feature-based VO, we not only are able to estimate the pose of the UAV with the same rate of the incoming images but also to recover the pose of the UAV when the SVO fails. We demonstrate the accuracy and the reliability of the hybrid VO based on a public benchmark dataset and a dataset recorded on our experimental platform. In addition, the autonomous hovering experiment verifies that the estimated result is fast and accurate enough to control the position of the UAV.