Autonomous navigation is a major challenge in the development of Micro Aerial Vehicles (MAVs). Especially when an algorithm has to be efficient, insect intelligence can be a source of inspiration. An elementary navigation task is homing, which means autonomously returning to the initial location. A promising approach uses learned visual familiarity of a route to determine reference headings during homing. In this paper an existing biological proof-of-concept is transferred to an algorithm for micro drones, using vision-in-the-loop experiments in indoor environments. An artificial neural network determines which control actions to take.