Optomotor flight control in houseflies shows bandwidth fractionation such that steering responses to an oscillating large-field rotating panorama peak at low frequency, whereas responses to small-field objects peak at high frequency. In fruit flies, steady-state large-field translation generates steering responses that are three times larger than large-field rotation. Here, we examine the optomotor steering reactions to dynamically oscillating visual stimuli consisting of large-field rotation, large-field expansion, and small-field motion. The results show that, like in larger flies, large-field optomotor steering responses peak at low frequency, whereas small-field responses persist under high frequency conditions. However, in fruit flies large-field expansion elicits higher magnitude and tighter phase-locked optomotor responses than rotation throughout the frequency spectrum, which may suggest a further segregation within the large-field pathway. An analysis of wing beat frequency and amplitude reveals that mechanical power output during flight varies according to the spatial organization and motion dynamics of the visual scene. These results suggest that, like in larger flies, the optomotor control system is organized into parallel large-field and small-field pathways, and extends previous analyses to quantify expansion-sensitivity for steering reflexes and flight power output across the frequency spectrum.

Flying insects are remarkable examples of sophisticated sensory-motor control systems. Insects have solved the fundamental challenge facing the field of mobile robots: robust sensory-motor mapping. Control models based on insects can contribute much to the design of robotic control systems. We present our work on a preliminary robotic control system inspired by current behavioural and physiological models of the fruit fly, Drosophila melanogaster. We designed a five-degrees-of-freedom robotic system that serves as a novel simulation/mobile robot hybrid. This design has allowed us to implement a fly-inspired control system that uses visual and mechanosensory feedback. Our results suggest that a simple control scheme can yield surprisingly robust fly-like robotic behaviour.