A Neuromorphic Visual Motion Sensor For Real-World Robots

Sensing visual motion gives a creature valuable information about its interactions with the environment. Flies in particular use visual motion information to navigate through turbulent air, avoid obstacles, and land safely. Mobile robots are ideal candidates for using this sensory modality to enhance their performance, but so far have been limited by the computational expense of processing video in realtime. Also, the complex structure of natural visual scenes poses an algo-rithmic challenge for extracting useful information in a robust manner. We address both issues by creating a small, low-power visual sensor with integrated ana-log parallel processing to extract motion in real-time. Because our architecture is based on biological motion detectors, we gain the advantages of this highly evolved system: A design that contains an implicit model of the statistical structure of natural dynamic scenes. We show that this sensor is suitable for use in the real world, and suggest robotic applications.