Analog VLSI implementation of the Help If Needed Stereopsis Algorithm

Abstract

This work introduces a novel clocked analog VLSI hardware system with an optical input that performs stereopsis. An algorithm called the Help If Needed Algorithm, developed previously, is readily mapped onto an analog VLSI platform. The system fits into the cellular neural network (CNN) paradigm. The circuit components that make up the cells of the CNN are designed with the constraint that they must function effectively and fit into the space available. In order to clarify the processing pathway, the system is described at the component and system levels. Each cell has an optical input, while the output is electrical. By utilizing an optical input, an analog VLSI silicon retina first stage can be connected to the stereopsis processor completely in parallel, creating a multi-stage artificial visual system. The physical system is composed of 2.0 /spl mu/m Tinychips fabricated through MOSIS. Experimental data are presented that verify that the system performs as desired and successfully implements the Help If Needed Stereopsis Algorithm. The novel stereopsis processor is ideally suited for autonomous robots, or any application that requires a low power visual processing system.