Snapshot-based control of UAS hover in outdoor environments

With the emergence of rotorcraft unmanned aerial systems (UAS) in civilian applications, the capability of accurate visual hovering is required in near-ground, GPS-denied, flying operations. Optic flow is commonly used for vision-based guidance and control of UAS, enabling autonomous obstacle avoidance, speed regulation, odometry, etc. This paper presents an optic flow-based method that uses a bio-inspired concept of image matching for the control of drift-free hover in natural environments. Our approach uses a reference snapshot (panoramic image) taken at the desired hover location and, through optic flow measurements, it estimates the rotorcraft´s 3D position and velocity relative to that location by matching the current and reference views at each time step. These position and velocity signals are fed to a hover controller. Sensing and control are performed in real-time, at camera frame rate (25Hz) onboard a small-size, custom-built quadrotor, and without additional sensor fusion. Results from outdoor closed-loop flight tests demonstrate robustness against long-term drift, as well as improved hover accuracy when compared to techniques that use frame-to-frame integration of egomotion vectors derived from optic flow.