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Thesis-2014-Hunt.pdf (2.66 MB)

Task allocation and consensus with groups of cooperating Unmanned Aerial Vehicles

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thesis
posted on 2014-06-23, 11:23 authored by Simon Hunt
The applications for Unmanned Aerial Vehicles are numerous and cover a range of areas from military applications, scientific projects to commercial activities, but many of these applications require substantial human involvement. This work focuses on the problems and limitations in cooperative Unmanned Aircraft Systems to provide increasing realism for cooperative algorithms. The Consensus Based Bundle Algorithm is extended to remove single agent limits on the task allocation and consensus algorithm. Without this limitation the Consensus Based Grouping Algorithm is proposed that allows the allocation and consensus of multiple agents onto a single task. Solving these problems further increases the usability of cooperative Unmanned Aerial Vehicles groups and reduces the need for human involvement. Additional requirements are taken into consideration including equipment requirements of tasks and creating a specific order for task completion. The Consensus Based Grouping Algorithm provides a conflict free feasible solution to the multi-agent task assignment problem that provides a reasonable assignment without the limitations of previous algorithms. Further to this the new algorithm reduces the amount of communication required for consensus and provides a robust and dynamic data structure for a realistic application. Finally this thesis provides a biologically inspired improvement to the Consensus Based Grouping Algorithm that improves the algorithms performance and solves some of the difficulties it encountered with larger cooperative requirements.

Funding

EPSRC

History

School

  • Science

Department

  • Computer Science

Publisher

© Simon James Hunt

Publication date

2014

Notes

A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.

EThOS Persistent ID

uk.bl.ethos.617858

Language

  • en