abstract: This work describes an approach for distance computation between agents in a
multi-agent swarm. Unlike other approaches, this work relies solely on signal Angleof-
Arrival (AoA) data and local trajectory data. Each agent in the swarm is able
to discretely determine distance and bearing to every other neighbor agent in the
swarm. From this information, I propose a lightweight method for sensor coverage
of an unknown area based on the work of Sameera Poduri. I also show that this
technique performs well with limited calibration distances. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2020
Identifer | oai:union.ndltd.org:asu.edu/item:62755 |
Date | January 2020 |
Contributors | Mulford, Philip (Author), Das, Jnaneshwar (Advisor), Takahashi, Timothy (Committee member), Phelan, Patrick (Committee member), Arizona State University (Publisher) |
Source Sets | Arizona State University |
Language | English |
Detected Language | English |
Type | Masters Thesis |
Format | 53 pages |
Rights | http://rightsstatements.org/vocab/InC/1.0/ |
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