Date of Award:

5-2014

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Electrical and Computer Engineering

Committee Chair(s)

YangQuan Chen

Committee

YangQuan Chen

Committee

Mac McKee

Committee

David Geller

Committee

Edmund Spencer

Committee

Ryan Gerdes

Abstract

In the coming 20 years, unmanned aerial data collection will be of great importance to many sectors of civilian life. Of these systems, Personal Remote Sensing (PRS) Small Unmanned Aerial Systems (sUASs), or “data drones,” will need special attention due to their low cost and high value for farming, scientific, and search-and-rescue uses, among countless others. Cyber-physical systems (large-scale, pervasive automated systems that tightly couple sensing and actuation through technology and the environment) can use sUASs as sensors and actuators, leading to even greater possibilities for benefit from sUASs. However, this nascent robotic technology of small unmanned aerial systems (sUASs) presents as many problems as new possibilities due to the challenges surrounding the abilities of these systems to perform safely and effectively for personal, academic, and business use. For these systems, whose missions are defined by the data they are sent to collect, safe and reliable mission quality is of highest importance. Much like the dawning of civil manned aviation, civilian sUAS flights demand privacy, accountability, and other ethical factors for societal integration, while safety of the civilian National Airspace (NAS) is always of utmost importance. While the growing popularity of this technology will drive a great effort to integrate sUASs into the NAS, the only long-term solution to this integration problem is one of proper architecture. In this research, a set of architectural requirements for this integration is presented: the Architecture for Ethical Aerial Information Sensing or AERIS. AERIS provides a cohesive set of requirements for any architecture or set of architectures designed for safe, ethical, accurate aerial data collection.

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