Abstract

Insects exhibit incredibly robust closed loop flight dynamics in the face of uncertainties. A fundamental principle contributing to this unparalleled behavior is rapid processing and convergence of visual sensory information to flight motor commands via spatial wide-field integration, accomplished by retinal motion pattern sensitive interneurons (LPTCs) in the lobula plate portion of the visual ganglia. Within a control-theoretic framework, an inner product model for wide-field integration of retinal image flow is presented, representing the spatial decompositions performed by LPTCs in the insect visuomotor system. The correspondence between image flow kernels and the output feedback terms they represent is developed, establishing the connection between LPTC motion sensitivity shape and closed loop behavior. It is shown that these outputs are sufficient to stabilize pitch and altitude flight modes for obstacle avoidance and terrain following navigational tasks. Hence, extraction of global retinal motion cues through computationally efficient wide-field integration processing provides a novel and promising methodology for utilizing visual sensory information in autonomous robotic navigation and flight control applications.

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