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Dissertation/Thesis Abstract

A Distributed, Probabilistic Method for Robot Swarm Localization
by Anderson, Zach, M.S., Southern Illinois University at Edwardsville, 2020, 78; 28259902
Abstract (Summary)

Multi-robot systems (MRS) have been show to be very effective for applications requiring unskilled agents collecting simple information from a large number of points. Such applications fundamentally require a global coordinate frame which is common to all robots in the swarm to share information. This work proposes a distributed, probabilistic approach to localizing the nodes of a swarm and suggests a control system architecture built on top of it that takes full advantage of it. The resulting localization mechanism is robust to node failures and under/over-constrained networks.

Indexing (document details)
Advisor: Weinberg, Jerry
Commitee: Lotfi, Nima, Matta, John
School: Southern Illinois University at Edwardsville
Department: Computer Science
School Location: United States -- Illinois
Source: MAI 82/7(E), Masters Abstracts International
Subjects: Robotics, Information Technology, Technical Communication, Artificial intelligence, Remote sensing
Keywords: Multi-robot systems (MRS) , Unskilled agents, Global coordinate frame, Robot swarms, Information sharing, Under-constrained networks, Over-constrained networks
Publication Number: 28259902
ISBN: 9798569924417
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