Integration of potential field theory and proportional navigation theory to autonomously guide an unmanned aerial vehicle.

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dc.contributor.advisorKoziol, Scott M.
dc.creatorFriudenberg, Patrick L.
dc.date.accessioned2016-01-14T16:54:01Z
dc.date.available2016-01-14T16:54:01Z
dc.date.created2015-12
dc.date.issued2015-11-10
dc.date.submittedDecember 2015
dc.date.updated2016-01-14T16:54:01Z
dc.description.abstractIndustrial 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.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/2104/9555
dc.language.isoen
dc.rights.accessrightsWorldwide access.
dc.subjectPotential fields. Proportional navigation. Guidance. Control. Unmanned aerial vehicle. Quad rotor. UAV. Path planning. Autonomous. Autonomy. Velocity control.
dc.titleIntegration of potential field theory and proportional navigation theory to autonomously guide an unmanned aerial vehicle.
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentBaylor University. Dept. of Electrical & Computer Engineering.
thesis.degree.grantorBaylor University
thesis.degree.levelMasters
thesis.degree.nameM.S.E.C.E.

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