  State-of-the-art forward facing monocular visual-inertial odometry algorithms
are often brittle in practice, especially whilst dealing with initialisation
and motion in directions that render the state unobservable. In such cases
having a reliable complementary odometry algorithm enables robust and resilient
flight. Using the common local planarity assumption, we present a fast, dense,
and direct frame-to-frame visual-inertial odometry algorithm for downward
facing cameras that minimises a joint cost function involving a homography
based photometric cost and an IMU regularisation term. Via extensive evaluation
in a variety of scenarios we demonstrate superior performance than existing
state-of-the-art downward facing odometry algorithms for Micro Aerial Vehicles
(MAVs).
