Title:
Specification-Based Task Orchestration for Multi-Robot Aerial Teams

dc.contributor.advisor Egerstedt, Magnus B.
dc.contributor.advisor Coogan, Samuel
dc.contributor.author Banks, Christopher J.
dc.contributor.committeeMember Chernova, Sonia
dc.contributor.committeeMember Hutchinson, Seth
dc.contributor.committeeMember Zhao, Ye
dc.contributor.department Interactive Computing
dc.date.accessioned 2023-01-10T16:21:31Z
dc.date.available 2023-01-10T16:21:31Z
dc.date.created 2022-12
dc.date.issued 2022-08-11
dc.date.submitted December 2022
dc.date.updated 2023-01-10T16:21:31Z
dc.description.abstract As humans begin working more frequently in environments with multi-agent systems, they are presented with challenges on how to control these systems in an intuitive manner. Current approaches tend to limit either the interaction ability of the user or limit the expressive capacity of instructions given to the robots. Applications that utilize temporal logics provide a human-readable syntax for systems that ensures formal guarantees for specification completion. By providing a modality for global task specification, we seek to reduce cognitive load and allow for high-level objectives to be communicated to a multi-agent system. In addition to this, we also seek to expand the capabilities of swarms to understand desired actions via interpretable commands retrieved from a human. In this thesis, we first present a method for specification-based control of a quadrotor. We utilize quadrotors as a highly agile and maneuverable application platform that has a wide variety of uses in complex problem domains. Leveraging specification-based control allows us to formulate a specification-based planning framework that will be utilized throughout the thesis. We then present methods for creating systems which allows us to provide task decomposition, allocation and planning for a team of quadrotors defined as task orchestration of multi-robot systems. Next, the task allocation portion of the task orchestration work is extended in the online case by considering cost agnostic sampling of trajectories from an online optimization problem. Then, we will introduce learning techniques where temporal logic specifications are learned and generated from a set of user given traces. Finally, we will conclude this thesis by presenting an extension to the Robotarium through hardware and software modifications that provides remote users access to control aerial swarms.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/70094
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Multi-agent systems
dc.subject Temporal logic
dc.subject Stochastic optimization
dc.subject Specification-based control
dc.subject Quadrotors
dc.title Specification-Based Task Orchestration for Multi-Robot Aerial Teams
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Coogan, Samuel
local.contributor.advisor Egerstedt, Magnus B.
local.contributor.author Egerstedt, Magnus B.
local.contributor.corporatename College of Computing
local.contributor.corporatename School of Interactive Computing
relation.isAdvisorOfPublication ab44a73e-f0fe-4336-8ffe-18ff4d18a41b
relation.isAdvisorOfPublication dd4872d3-2e0d-435d-861d-a61559d2bcb6
relation.isAuthorOfPublication dd4872d3-2e0d-435d-861d-a61559d2bcb6
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isOrgUnitOfPublication aac3f010-e629-4d08-8276-81143eeaf5cc
thesis.degree.level Doctoral
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
BANKS-DISSERTATION-2022.pdf
Size:
15.71 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
LICENSE.txt
Size:
3.87 KB
Format:
Plain Text
Description: