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

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.

Name thesis:degree_name

M.S.E.C.E.

Level thesis:degree_level

Masters

Grantor

Baylor University.

Year dc:date.issued

2015

Author dc:creator

• Friudenberg, Patrick L.

Advisor dc:contributor.advisor

• Koziol, Scott M.

• Potential fields.
• Proportional navigation.
• Quad rotor.
• Unmanned aerial vehicles (UAVs)
• Path planning.
• Missile guidance.
• Velocity control.

Statement dc:rights

• Baylor University works are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact libraryquestions@baylor.edu for inquiries about permission.

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/2104/9555

OAI identifier oai:identifier

oai:baylor-ir.tdl.org:2104/9555