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Kernel Design and Distributed, Self-Triggered Control for Coordination of Autonomous Multi-Agent Configurations

Published online by Cambridge University Press:  27 March 2018

Levi DeVries,
Aaron Sims and
Michael D. M. Kutzer
Levi DeVries*
Affiliation:
Department of Weapons and Systems Engineering, United States Naval Academy, Annapolis, Maryland, 21402, USA. E-mails: amsims93@gmail.com, kutzer@usna.edu
Aaron Sims
Affiliation:
Department of Weapons and Systems Engineering, United States Naval Academy, Annapolis, Maryland, 21402, USA. E-mails: amsims93@gmail.com, kutzer@usna.edu
Michael D. M. Kutzer
Affiliation:
Department of Weapons and Systems Engineering, United States Naval Academy, Annapolis, Maryland, 21402, USA. E-mails: amsims93@gmail.com, kutzer@usna.edu
*
*Corresponding author. E-mail: devries@usna.edu
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Summary

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Autonomous multi-agent systems show promise in countless applications, but can be hindered in environments where inter-agent communication is limited. In such cases, this paper considers a scenario where agents communicate intermittently through a cloud server. We derive a graph transformation mapping the kernel of a graph's Laplacian to a desired configuration vector while retaining graph topology characteristics. The transformation facilitates derivation of a self-triggered controller driving agents to prescribed configurations while regulating instances of inter-agent communication. Experimental validation of the theoretical results shows the self-triggered approach drives agents to a desired configuration using fewer control updates than traditional periodic implementations.

Keywords

Consensus-based controlSelf-triggered controlMulti-agent controlGraph transformationAsynchronous control

Information

Type
Articles
Information
Robotica , Volume 36 , Issue 7 , July 2018, pp. 1077 - 1097
Creative Commons
This is a work of the U.S. Government and is not subject to copyright protection in the United States.
Copyright
Copyright © Cambridge University Press 2018

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