Date of Award

6-10-2020

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2020.

Departments

Computer Science and Engineering; Electrical and Computer Engineering

First Advisor

Christopher Kitts

Second Advisor

Sally Wood

Abstract

The current infrastructure for drone piloting involves drones flying in a predetermined path to find an object, source, or target with a known location. Drones should be able to determine an optimal flight path mid-flight in order to find an undefined source or target given existing parameters that can be analyzed from incoming sensor data. However, a framework for such a feat is almost non-existent. Our project aims to build such a framework that allows for the control of and communication among multiple drones, called a cluster, and allows for in-flight analysis and processing of sensor information to determine how to progress towards finding a source. This second objective of adaptive navigation is when the cluster of drones report their sensor data to a central ground station, allowing for a gradient calculation to be executed. The cluster of drones can follow this gradient to progress towards a source with a previously unknown specific location or path to the location.

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