Collision Avoidance and Local Guidance Based on Insect Visual Motion Processing

Tanner Research proposes to apply technology based on visual motion processing and flight control in insects to collision avoidance and guidance in autonomous vehicles and robots. The visual processing mimics adaptive motion detection as observed in flies, which has the effect of reducing detector dependence on non-motion-related parameters of visual stimuli, improving estimates of optic flow. The control theory is modeled after wide-field neurons (tangential cells) that spatially integrate local optic flow estimates. The outputs of these integrators are applied as feedback signals for direct control of vehicle dynamics. This control paradigm is capable of robust collision avoidance in complex, cluttered environments. We will investigate integration of the two technologies, and develop a roadmap for implementation in a miniature flying platform, including trade studies for implementation technologies, and integration and resource-sharing with other functions, such as bomb damage indication, that are required of the payload in miniature- and micro-unmanned aerial vehicles.