Robot Soccer using Optical Analog VLSI Sensors
In this paper we show how a combination of low dimensional vision sensors can be used to aid the higher level visual processing task of colour blob tracking, carried out by a conventional vision system. The processing elements are neuromorphic analog VLSI (aVLSI) vision sensors capable of computing motion and estimating the spatial position of high-contrast moving targets. In these devices both sensing and processing is done on the chip’s focal plane. The neuromorphic sensors can calculate optical flow, position of sharpest edge, and motion of sharpest edge, in real-time. The processing capability of the system is investigated in a mobile robotics application. Firstly, for visualization and evaluation purposes, a correlation analysis is performed between the data collected from the neuromorphic vision sensors and the standard vision system of the autonomous robot, then, we process the multiple neuromorphic sensory signals with a standard auto-regression method in order to achieve a higher level vision processing task at a much higher update rate. At the end we argue why this result is of great relevance for the application domain of reactive and lightweight mobile robotics, at the hands of a soccer robot, where the fastest sensory-motor feedback loop is imperative for a successful participation in a RoboCup soccer competition.