Aerospace Engineering Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2737
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Item Biologically Inspired Navigational Strategies Using Atmospheric Scattering Patterns(2015) Ashkanazy, Julia; Humbert, James S; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A source of accurate and reliable heading is vital for the navigation of autonomous systems such as micro-air vehicles (MAVs). It is desirous that a passive computationally efficient measure of heading is available even when magnetic heading is not. To confront this scenario, a biologically inspired methodology to determine heading based on atmospheric scattering patterns is proposed. A simplified model of the atmosphere is presented, and a hardware analog to the insect Dorsal Rim Area (DRA) photodetection is introduced. Several algorithms are developed to map the patterns of polarized and unpolarized celestial light to heading relative to the sun. Temporal information is used to determine current solar position, and then merged with solar relative heading resulting in absolute heading. Simulation and outdoor experimentation are used to validate the proposed heading determination methodology. Celestial heading measurements are shown to provide closed loop heading control of a ground based robot.Item Bio-Inspired Information Extraction In 3-D Environments Using Wide-Field Integration Of Optic Flow(2010) Hyslop, Andrew Maxwell; Humbert, James S; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A control theoretic framework is introduced to analyze an information extraction approach from patterns of optic flow based on analogues to wide-field motion-sensitive interneurons in the insect visuomotor system. An algebraic model of optic flow is developed, based on a parameterization of simple 3-D environments. It is shown that estimates of proximity and speed, relative to these environments, can be extracted using weighted summations of the instantaneous patterns of optic flow. Small perturbation techniques are utilized to link weighting patterns to outputs, which are applied as feedback to facilitate stability augmentation and perform local obstacle avoidance and terrain following. Weighting patterns that provide direct linear mappings between the sensor array and actuator commands can be derived by casting the problem as a combined static state estimation and linear feedback control problem. Additive noise and environment uncertainties are incorporated into an offline procedure for determination of optimal weighting patterns. Several applications of the method are provided, with differing spatial measurement domains. Non-linear stability analysis and experimental demonstration is presented for a wheeled robot measuring optic flow in a planar ring. Local stability analysis and simulation is used to show robustness over a range of urban-like environments for a fixed-wing UAV measuring in orthogonal rings and a micro helicopter measuring over the full spherical viewing arena. Finally, the framework is used to analyze insect tangential cells with respect to the information they encode and to demonstrate how cell outputs can be appropriately amplified and combined to generate motor commands to achieve reflexive navigation behavior.