Biologically-inspired visual stabilization of a rotorcraft UAV in unknown outdoor environments

This paper presents the development and flight testing of a novel and efficient view-based method for the navigation and control of rotorcraft unmanned aerial vehicles (UAVs) in unknown, GPS-denied, outdoor environments. At the core of our system is the Image Coordinates Extrapolation (ICE) algorithm which estimates the UAV 3D position and velocity in real-time by computing the pixel-wise difference between the current view (panoramic image) and a snapshot taken at a reference location (e.g., the hovering position). When combined with a PID flight controller, this simple, but effective algorithm allows a rotorcraft UAV to achieve stable and drift-free hover using image differences only, without the need to track features or to compute optic flow. The performance of our approach is evaluated in closed-loop flight tests on a custom-built quadrotor equipped with an onboard panoramic vision system and flight computer.