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Smart Shepherding: Towards Transparent Artificial Intelligence Enabled Human-Swarm Teams Read chapter Read first chapter

2021 | OriginalPaper | Chapter

2. Shepherding Autonomous Goal-Focused Swarms in Unknown Environments Using Hilbert Space-Filling Paths

Authors : Nathan K. Long, Matthew Garratt, Karl Sammut, Daniel Sgarioto, Hussein A. Abbass

Published in: Shepherding UxVs for Human-Swarm Teaming

Publisher: Springer International Publishing

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Abstract

A novel technique has been developed for autonomous swarm-based unknown environment scouting. A control method known as swarm shepherding was employed, which replicates the behaviour seen when a sheepdog guides a herd of sheep to an objective location. The guidance of the swarm agents was implemented using low computation cost, force-based behaviours. The exploration task was augmented by introducing swarm member role assignments, including a role which imposes a localised covering area for agents which stray too far from the swarm global centre of mass. The agents then proceeded to follow a Hilbert space-filling curve (HSFC) path within their localised region. The simulation results demonstrated that the inclusion of the HSFC paths improved the efficiency of goal-based exploration of the environment, which became more prominent with an increase in the density of the number of goals in the environment.

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previous chapter Smart Shepherding: Towards Transparent Artificial Intelligence Enabled Human-Swarm Teams
next chapter Simulating Single and Multiple Sheepdogs Guidance of a Sheep Swarm
Appendix
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Metadata
Title
Shepherding Autonomous Goal-Focused Swarms in Unknown Environments Using Hilbert Space-Filling Paths
Authors
Nathan K. Long
Matthew Garratt
Karl Sammut
Daniel Sgarioto
Hussein A. Abbass
Copyright Year
2021
Book
Shepherding UxVs for Human-Swarm Teaming

Print ISBN: 978-3-030-60897-2

Electronic ISBN: 978-3-030-60898-9

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-60898-9_2

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