Flying insects and birds are able to fly smartly in an unpredictable environment. Many animals have been found to rely mainly on optic flow. Optic flow can be defined as the vector field of the apparent motion of objects, surfaces, and edges in a visual scene generated by the relative motion between an observer (an eye or a camera) and the scene. Optic flow is particularly useful for short-range navigation because it depends on the ratio between (i) the relative linear speed of the visual scene with respect to the observer and (ii) the distance of the observer from obstacles in the surrounding environment. However, this does not require any actual measurement of either speed or distance. Optic flow is therefore suitable for various navigational tasks, such as takeoff or landing along vertical or longitudinal axes, terrain following, speed control in a cluttered environment, lateral and frontal obstacle avoidance, and visual odometry. This article focuses on feedback loops that use optic flow to control robots in the same way as the Gibsonian approach, which sometimes enhances robot perception, by a distance or speed measurement, even though the direct measurement of distance or linear speed does not exist in flying insects and birds. Optic flow is likely to be one of the most important visual cues that could be used during the next decade to enhance robot reactivity in unpredictable environments. Conversely, the biorobotic approach can therefore help to better understand how flying animals can move smartly in such an environment.