{"id":{"repo_id":"baylor","oai_identifier":"oai:baylor-ir.tdl.org:2104/9555"},"canonical_url":"https://search.dev.ndltd.org/etd/baylor/oai:baylor-ir.tdl.org:2104/9555","repository":{"repo_id":"baylor","name":"Baylor University","base_url":"https://baylor-ir.tdl.org/server/oai/request"},"display":{"title":"Integration of potential field theory and proportional navigation theory to autonomously guide an unmanned aerial vehicle.","abstract":"Industrial robotics, military, surveying, and delivery applications have laid a foundation for research into full autonomy of machines, including Unmanned Aerial Vehicles (UAV). This thesis supports this research by surveying the methods used to guide UAVs, and developing a new method by combining potential fields, typically used for obstacle avoidance, and proportional navigation, a popular missile guidance algorithm. The new algorithm modifies the old algorithms to allow a UAV to track an optimal path to, and rendezvous with, a moving target while avoiding obstacles in its path. A model for a quad rotor style UAV is developed and controlled using feedback linearization. A simulator is built for deploying a number of environments and taking performance measurements. Aspects of the hardware implementation are introduced.","abstract_html":"Industrial robotics, military, surveying, and delivery applications have laid a foundation for research into full autonomy of machines, including Unmanned Aerial Vehicles (UAV). This thesis supports this research by surveying the methods used to guide UAVs, and developing a new method by combining potential fields, typically used for obstacle avoidance, and proportional navigation, a popular missile guidance algorithm. 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