Date of Award

6-13-2017

Document Type

Thesis - SCU Access Only

Publisher

Santa Clara : Santa Clara University, 2017.

Departments

Computer Engineering; Mechanical Engineering

First Advisor

Christopher A. Kitts

Second Advisor

Michael Taylor

Abstract

This report details the development of a prototype unmanned aircraft system (UAS) to aid in scouting and surveillance missions conducted by civil service agencies. These agencies, like the Thousand Oaks Police Department and California State Parks Department, are looking to use UAS technology to survey large areas of land at an affordable cost with limited need for human interaction for increased agent safety. To meet some of the needs of these agencies, the project team developed two critical subsystems: a pneumatic launch system for fixed-wing unmanned aircraft vehicles (UAVs) and companion software with vegetation feature recognition and autonomous flight firmware and hardware. These subsystems were demonstrated with the use of an o↵-the-shelf UAV that was modified to interface with the launch system and to house all the necessary electronics for flight and data gathering. The UAS was developed to be easily transported, to be setup and operable by a small team, and to be produced for a cost below $5000. The project team was able to demonstrate prototypical functionality of the launch and software systems. The pneumatic launcher is capable of accelerating the projected weight of a UAV to its necessary lift velocity, 25 ft/s for the UAV used in this project, to achieve flight. The feature recognition software is capable of identifying vegetation and calculating real-world locations to use in planning future missions. The work done for this project is prototypical and can benefit from improvements to the subsystems. The project team recommends making further design iterations to the launch system to be compatible with more fixed-wing UAVs and to increase the safety of the pressure system. Further testing is necessary to prove the functionality of the launcher to reliably launch a full-scale fixed-wing UAV. The feature recognition software can be improved to detect specific types of vegetation and to execute during flight for more advanced autonomous control of the UAV.

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