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.