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Insects and birds have been in the sensory-motor control business for more than 100 million years. The manned aircraft developed over the last 100 years rely on a similar lift to that generated by birds’ wings. Aircraft designers have paid little attention, however, to the pilot’s visual sensor that finely controls these wings, although it is definitely the most sophisticated avionic sensors ever known to exist. For this reason, the thinking that prevails in the field of aeronautics does not help us much grasp the visuo-motor contol laws that animals and humans bring into play to control their flight. To control an aircraft, it has been deemed essential to measure state variables such as barometric altitude, groundheight, groundspeed, descent speed, etc. Yet the sensors developed for this purpose usually emissive sensors such as Doppler radars, radar-altimeters or forward-looking infrared sensors, in particular are far too cumbersome for insects or even birds to carry and to power. Natural flyers must therefore have developed other systems for controlling their flight. Flying insects are agile creatures that navigate swiftly through most unpredictable environments. Equipped with “only” about one million neurons and only 3000 pixels in each eye, the housefly, for example, achieves 3D navigation at an impressive 700 bodylengths per second. The lightness of the processing system at work onboard a fly makes us turn pale when we realize that this creature actually achieves just what is being sought for in the field of aerial robotics: dynamic stabilization, 3D autonomous navigation, ground avoidance, collision avoidance with stationary and nonstationary obstacles, tracking, docking, autonomous takeoff and landing, etc. Houseflies add insult to injury by being able to land gracefully on ceilings. The last seven decades have provided evidence that flying insects guide themselves through their environments by processing the optic flow (OF) that is generated on their eyes as a consequence of their locomotion. In the animal’s reference frame, the translational OF is the angular speed ω at which contrasting objects in the environment move past the animal (Kennedy, 1939; Gibson, 1950; Lee, 1980; Koenderink, 1986). In the present chapter, it is proposed to summarize our attempts to model the visuomotor control system that provides flying insects with a means of autonomous guidance at close range. The aim of these studies was not (yet) to produce a detailed neural circuit but rather to obtain a more functional overall picture, that is, a picture that abstracts some basic control

Optic Flow Based Visual Guidance: From Flying Insects to Miniature Aerial Vehicles