Void reduction in self-healing swarms
Eliot, Neil, Kendall, David, Moon, Alun, Brockway, Michael and Amos, Martyn (2019) Void reduction in self-healing swarms. Artificial Life Conference Proceedings, 9. pp. 87-94.
Item Type: | Article |
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Abstract
Swarms consist of many agents that interact according to a
simple set of rules, giving rise to emergent global behaviours.
In this paper, we consider swarms of mobile robots or drones.
Swarms can be tolerant of faults that may occur for many
reasons, such as resource exhaustion, component failure, or
disruption from an external event. The loss of agents reduces
the size of a swarm, and may create an irregular structure in
the swarm topology. A swarm’s structure can also be irregular due to initial conditions, or the existence of an obstacle.
These changes in the structure or size of a swarm do not stop
it from functioning, but may adversely affect its efficiency or
effectiveness. In this paper, we describe a self-healing mechanism to counter the effect of agent loss or structural irregularity. This method is based on the reduction of concave
regions at swarm perimeter regions. Importantly, this method
requires no expensive communication infrastructure, relying
only on agent proximity information. We illustrate the application of our method to the problem of surrounding an oil
slick, and show that void reduction is necessary for full and
close containment, before concluding with a brief discussion
of its potential uses in other domains.
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Depositing User: Neil Eliot |
Identifiers
Item ID: 17507 |
Identification Number: https://doi.org/10.1162/isal_a_00146 |
URI: http://sure.sunderland.ac.uk/id/eprint/17507 | Official URL: https://direct.mit.edu/isal/isal2019/volume/31 |
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Catalogue record
Date Deposited: 19 Apr 2024 14:27 |
Last Modified: 19 Apr 2024 14:30 |
Author: | Neil Eliot |
Author: | David Kendall |
Author: | Alun Moon |
Author: | Michael Brockway |
Author: | Martyn Amos |
University Divisions
Faculty of Technology > School of Computer ScienceSubjects
Computing > Artificial IntelligenceActions (login required)
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