Many robotics and navigation systems utilizing stereopsis to determine depth have rigid size and power constraints and require direct physical implementation of the stereo algorithm. The main challenges lie in managing the communication between image sensor and image processor arrays, and in parallelizing the computation to determine stereo correspondence between image pixels in real-time. This paper describes the first comprehensive system level demonstration of a dedicated low-power analog VLSI (very large scale integration) architecture for stereo correspondence suitable for real-time implementation. The inputs to the implemented chip are the ordered pixels from a stereo image pair, and the output is a two-dimensional disparity map. The approach combines biologically inspired silicon modeling with the necessary interfacing options for a complete practical solution that can be built with currently available technology in a compact package. Furthermore, the strategy employed considers multiple factors that may degrade performance, including the spatial correlations in images and the inherent accuracy limitations of analog hardware, and augments the design with countermeasures.
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