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Bioinspired minimal machine multiaperture apposition vision system.

John D. Davis, Steven F. Barrett, Cameron Wright, Michael Wilcox

发表年份
2008
引用次数
4

摘要

Traditional machine vision systems have an inherent data bottleneck that arises because data collected in parallel must be serialized for transfer from the sensor to the processor. Furthermore, much of this data is not useful for information extraction. This project takes inspiration from the visual system of the house fly, Musca domestica, to reduce this bottleneck by employing early (up front) analog preprocessing to limit the data transfer. This is a first step toward an all analog, parallel vision system. While the current implementation has serial stages, nothing would prevent it from being fully parallel. A one-dimensional photo sensor array with analog pre-processing is used as the sole sensory input to a mobile robot. The robot's task is to chase a target car while avoiding obstacles in a constrained environment. Key advantages of this approach include passivity and the potential for very high effective "frame rates."

关键词

BottleneckComputer scienceFrame (networking)RobotPreprocessorComputer visionComputer hardwareMachine visionArtificial intelligenceReal-time computing

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