Aerospace Engineering Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2737
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Item An Observer for Estimating Translational Velocity from Optic Flow and Radar(2011) Gerardi, Steven Anthony; Humbert, James S; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis presents the development of a discrete time observer for estimating state information from optic flow and radar measurements. It is shown that estimates of translational and rotational speed can be extracted using a least squares inversion for wide fields of view or, with the addition of a Kalman Filter, for small fields of view. The approach is demonstrated in a simulated three dimensional urban environment on an autonomous quadrotor micro-air-vehicle (MAV). A state feedback control scheme is designed, whereby the gains are found via static H∞, and implemented to allow trajectory following. The proposed state estimation scheme and feedback method are shown to be sufficient for enabling autonomous navigation of an MAV. The resulting methodology has the advantages of computational speed and simplicity, both of which are imperative for implementation on MAVs due to stringent size, weight, and power requirements.Item OPTIC FLOW BASED STATION-KEEPING AND WIND REJECTION FOR SMALL FLYING VEHICLES(2010) Patrick, Bryan; Humbert, James S.; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Optic flow and Wide Field Integration (WFI) have shown potential for application to autonomous navigation of Unmanned Air Vehicles (UAVs). In this study the application of these same methods to other tasks, namely station-keeping and wind rejection, is examined. Theory surrounding optic flow, WFI and wind gust modeling is examined to provide a theoretical background. A controller based on a H∞ bounded formulation of the well known Linear Quadratic Regulator in designed to both mitigate wind disturbances and station-keep. The performance of this controller is assessed via simulation to determine both performance and trade-offs in implementation such as the method for optic flow calculation. Furthermore, flight tests are performed to examine the real world effectiveness of the controller. Finally, conclusions about potential improvement to implementation are drawn.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.Item Comparison of Optic Flow in the Visible Light and Infrared Specturms(2008) Chinn, Michael William; Humbert, James S; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Insects use a method of Wide Field Integration (WFI) to navigate efficiently through unknown environments. Using these natural paradigms, various WFI based forms of navigation can be implemented based on electro-mechanical vision devices on robotic vehicles. However, under low light and/or suspended particles in the environment, these methods become less useful. One solution to this problem is to use infrared vision sensors rather than visible light sensors. This would allow insect-like navigation for autonomous vehicles under a variety of lighting conditions, including a total lack of visible light. The results show that, using infrared sensors, it is possible to navigate under a variety of lighting conditions, even where visible light sensors become ineffective.Item Stochastic Properties of Wide Field Integrated Optic Flow Measurements(2009) Owen, Scott; Humbert, James S; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Wide Field Integration (WFI) is a biologically inspired method of spatially decomposing optic flow estimates to extract relevant behavioral cues for navigation. In this thesis, a framework is developed that allows the direct application of a Kalman filter to improve the state information extracted from optic flow measurements. In addition, the noise properties of optic flow measurements are characterized, and an architecture to propagate the uncertainty in optic flow measurements to WFI state estimates is formalized. The closed-loop performance of a ground robot maneuvering in a straight tunnel using WFI outputs is then analyzed using three different algorithms to compute optic flow. The performance of the robot is characterized by its ability to track the tunnel centerline, and the accuracy of the WFI state estimates are compared with the true state estimates using a visual motion capture system. Lastly, the Kalman filter is implemented on a ground robot and the modified closed-loop performance is analyzed.