  Small flying robots can perform landing maneuvers using bio-inspired optical
flow by maintaining a constant divergence. However, optical flow is typically
estimated from frame sequences recorded by standard miniature cameras. This
requires processing full images on-board, limiting the update rate of
divergence measurements, and thus the speed of the control loop and the robot.
Event-based cameras overcome these limitations by only measuring pixel-level
brightness changes at microsecond temporal accuracy, hence providing an
efficient mechanism for optical flow estimation. This paper presents, to the
best of our knowledge, the first work integrating event-based optical flow
estimation into the control loop of a flying robot. We extend an existing
'local plane fitting' algorithm to obtain an improved and more computationally
efficient optical flow estimation method, valid for a wide range of optical
flow velocities. This method is validated for real event sequences. In
addition, a method for estimating the divergence from event-based optical flow
is introduced, which accounts for the aperture problem. The developed
algorithms are implemented in a constant divergence landing controller on-board
of a quadrotor. Experiments show that, using event-based optical flow, accurate
divergence estimates can be obtained over a wide range of speeds. This enables
the quadrotor to perform very fast landing maneuvers.
