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Understanding the role of recruitment in collective robot foraging

Understanding the role of recruitment in collective robot foraging
Understanding the role of recruitment in collective robot foraging
When is it profitable for robots to forage collectively? Here we compare the ability of swarms of simulated bio-inspired robots to forage either collectively or individually. The conditions under which recruitment (where one robot alerts another to the location of a resource) is profitable are characterised, and explained in terms of the impact of three types of interference between robots (physical, environmental, and informational). Key factors determining swarm performance include resource abundance, the reliability of shared information, time limits on foraging, and the ability of robots to cope with congestion around discovered resources and around the base location. Additional experiments introducing odometry noise indicate that collective foragers are more susceptible to odometry error.
MIT Press
Pitonakova, Lenka
ef806152-a9c0-4075-806d-c75f0d3f7bbb
Crowder, Richard
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3
Lipson, Hod
Sayama, Hiroki
Rieffel, John
Risi, Sebastian
Doursat, Rene
Pitonakova, Lenka
ef806152-a9c0-4075-806d-c75f0d3f7bbb
Crowder, Richard
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3
Lipson, Hod
Sayama, Hiroki
Rieffel, John
Risi, Sebastian
Doursat, Rene

Pitonakova, Lenka, Crowder, Richard and Bullock, Seth (2014) Understanding the role of recruitment in collective robot foraging. Lipson, Hod, Sayama, Hiroki, Rieffel, John, Risi, Sebastian and Doursat, Rene (eds.) In ALIFE 14: The Fourteenth International Conference on the Synthesis and Simulation of Living Systems. MIT Press. 8 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

When is it profitable for robots to forage collectively? Here we compare the ability of swarms of simulated bio-inspired robots to forage either collectively or individually. The conditions under which recruitment (where one robot alerts another to the location of a resource) is profitable are characterised, and explained in terms of the impact of three types of interference between robots (physical, environmental, and informational). Key factors determining swarm performance include resource abundance, the reliability of shared information, time limits on foraging, and the ability of robots to cope with congestion around discovered resources and around the base location. Additional experiments introducing odometry noise indicate that collective foragers are more susceptible to odometry error.

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More information

Published date: 2014
Venue - Dates: Fourteenth International Conference on Artificial Life, 2014-01-01
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 364829
URI: https://eprints.soton.ac.uk/id/eprint/364829
PURE UUID: ba75eea6-d56f-45e6-b7de-d3fcd0121fb9
ORCID for Lenka Pitonakova: ORCID iD orcid.org/0000-0003-3633-7302

Catalogue record

Date deposited: 12 May 2014 09:11
Last modified: 13 Aug 2018 16:32

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Contributors

Author: Lenka Pitonakova ORCID iD
Author: Richard Crowder
Author: Seth Bullock
Editor: Hod Lipson
Editor: Hiroki Sayama
Editor: John Rieffel
Editor: Sebastian Risi
Editor: Rene Doursat

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