Bio-Inspired Visuomotor Convergence in Navigation and Flight Control Systems
J. Sean Humbert
PhD Dissertation, Control and Dynamical Systems
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 developed, representing the spatial decompositions performed by LPTCs in the insect visuomotor system. A rigorous characterization of the information available from this visuomotor convergence technique for motion within environments exhibiting non-omogeneous spatial distributions is performed, establishing the connection between retinal motion sensitivity shape and closed loop behavior. The proposed output feedback methodology is shown to be sufficient to give rise to experimentally observed insect navigational heuristics, including forward speed regulation, obstacle avoidance, hovering, and terrain following behaviors. Hence, extraction of global retinal motion cues through computationally efficient wide-field integration process- ing provides a novel and promising methodology for utilizing visual sensory information in autonomous robotic navigation and flight control applications.
- PhD Dissertation: http://www.cds.caltech.edu/~murray/preprints/jsh05-phd.pdf
- Project(s): Template:HTDB funding::ARO/ICB