Visual Homing for Micro Aerial Vehicles Using Scene Familiarity

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. One of the elementary navigation tasks of insects and robots is “homing”, which is the task of returning to an initial starting position. 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 place.