The computation of optical flow
ACM Computing Surveys (CSUR)
A Robust Analog VLSI Motion Sensor Based on the Visual System of the Fly
Autonomous Robots
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Tomorrow's Micro-Air-Vehicles (MAVs) could be used as scouts in many civil and military missions without any risk to human life. MAVs have to be equipped with sensors of several kinds for stabilization and guidance purposes. Many recent findings have shown, for example, that complex tasks such as 3-D navigation can be performed by insects using optic flow (OF) sensors although insects' eyes have a rather poor spatial resolution. At our Laboratory, we have been performing electrophysiological, micro-optical, neuroanatomical and behavioral studies for several decades on the housefly's visual system, with a view to understanding the neural principles underlying OF detection and establishing how OF sensors might contribute to performing basic navigational tasks. Based on these studies, we developed a functional model for an Elementary Motion Detector (EMD), which we first transcribed into electronic terms in 1986 and subsequently used onboard several terrestrial and aerial robots. Here we present a Field Programmable Gate Array (FPGA) implementation of an EMD array, which was designed for estimating the OF in various parts of the visual field of a MAV. FPGA technology is particularly suitable for applications of this kind, where a single Integrated Circuit (IC) can receive inputs from several photoreceptors of similar (or different) shapes and sizes located in various parts of the visual field. In addition, the remarkable characteristics of present-day FPGA applications (their high clock frequency, large number of system gates, embedded RAM blocks and Intellectual Property (IP) functions, small size, light weight, low cost, etc.) make for the flexible design of a multi-EMD visual system and its installation onboard MAVs with extremely low permissible avionic payloads.