Multi-robot systems (MRSs) have gained significant momentum as of late in the robotics
community as they find application in tasks such as unknown environment exploration,
distributed surveillance, and search and rescue. Operating robot teams in real world environments introduces a notion of uncertainty into the system, especially when it comes to the
ability of the MRS to reliably communicate. This poses a significant challenge as a stable
communication topology is the backbone of the team's ability to coordinate. Additionally,
as these systems continue to evolve and integrate further into our society, a growing threat
of adversarial attackers pose the risk of compromising nominal operation. As such, this dissertation aims to model the effects of uncertainty in communication on the topology of the
MRS using a probabilistic interaction model. More specifically we are interested in studying
a probabilistic perspective to those topologies that pertain to the security and resilience of
an MRS against adversarial attacks. Having a model that is capable of capturing how probabilistic topologies may evolve over time is essential for secure and resilient planning under
communication uncertainty. As a result, we develop probabilistic models, both exact and
approximate, for the topological properties of system left-invertibility and (r, s)-robustness
that respectively characterize the security and resilience of an MRS. In our modeling, we
use binary decision diagrams, convolutional neural networks, matroid theory and more to
tackle the problems related to probabilistic security and resilience where we find exact solutions,
calculate bounds, solve optimization problems, and compute informative paths for
exploration. / Doctor of Philosophy / When robots coordinate and interact together to achieve a collaborative task as a team,
we obtain what is known as a multi-robot system or MRS for short. MRSs have several
advantages over single robots. These include reliability through redundancy, where several
robots can perform a given task in case one of the robots unexpectedly fails. The ability to
work faster and more efficiently by working in parallel and at different locations. And taking
on more complex tasks that can be too demanding for a single robot to complete. Unfortunately,
the advantages of MRSs come at a cost, they are generally harder to coordinate, the
action of one robot often depends on the action of other robots in the system, and they are
more vulnerable to being attacked or exploited by malicious attackers who want to disrupt
nominal operation. As one would expect, communication plays a very important roles in
coordinating a team of robots. Unfortunately, robots operating in real world environments
are subject to disturbances such as noise, obstacles, and interference that hinders the team's
ability to effectively exchange information. In addition to being crucial in coordination, effective
information exchange plays a major role in detecting and avoiding adversarial robots.
Whenever misinformation is being spread in the team, the best way to counter such adversarial
behavior is to communicate with as much well-behaving robots as possible to identity
and isolate inconsistencies. In this dissertation we try to study how uncertainty in communication
affects a system's ability to detect adversarial behavior, and how we can model such
a phenomenon to help us account for these uncertainties when designing secure and resilient
multi-robot systems.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/113011 |
| Date | 12 July 2021 |
| Creators | Wehbe, Remy |
| Contributors | Electrical Engineering, Williams, Ryan K., Saad, Walid, Woolsey, Craig A., Dhillon, Harpreet Singh, Stilwell, Daniel J. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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