Abstract
This paper presents an artificial neural network that detects and tracks an object moving within its field of view. This novel network is inspired by processing functions observed in the fly visual system. The network detects changes in input light intensities, determines motion on both the local and the wide-field levels, and outputs displacement information necessary to control pursuit tracking. Software simulations demonstrate the current prototype successfully follows a moving target within specified radiance and motion constraints. The paper reviews these limiting constraints and suggests future network augmentations to remove them. Despite its current limitations, the existing prototype serves as a solid foundation for a future network that promises to provide machines with the improved abilities to do high-speed pursuit tracking, interception, and collision avoidance.
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