A small low-cost motion detector would have widespread applications in visual control systems such as miniature unmanned aerial vehicles and collision avoidance systems. In the last 20 years a number of analog VLSI chips have been developed which incorporate both photodetection and motion computation on the same chip. Nevertheless, artificial real-time vision and simple seeing systems remain a massive challenge mainly because the environment greatly impacts on their performance. On the other hand, biological systems have, through years of evolution, come up with a number of simple but clever solutions. The Reichardt Correlator is a biologically inspired model for motion detection. However, the basic model is not a robust estimator of velocity. The accuracy and reliability of this model can be significantly improved through various elaborations. VLSI is ideally suited to the parallel processing seen in nature because it allows for high device integration density and complex implementation of complex functions. Howsoever, VLSI poses some serious bounds on the types of elaborations that can be implemented. We have explored this problem and will present a number of improved models with robust outputs that are practical in terms of real time implementation in microchips.
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