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A study of error diversity in robotic swarms for task partitioning in foraging tasks

Often in swarm robotics, an assumption is made that all robots in the swarm behave the same and will have a similar (if not the same) error model. However, in reality, this is not the case, and this lack of uniformity in the error model, and other operations, can lead to various emergent behaviors....

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Detalles Bibliográficos
Autores principales: Buchanan, Edgar, Alden, Kieran, Pomfret, Andrew, Timmis, Jon, Tyrrell, Andy M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9845931/
https://www.ncbi.nlm.nih.gov/pubmed/36686209
http://dx.doi.org/10.3389/frobt.2022.904341
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author Buchanan, Edgar
Alden, Kieran
Pomfret, Andrew
Timmis, Jon
Tyrrell, Andy M.
author_facet Buchanan, Edgar
Alden, Kieran
Pomfret, Andrew
Timmis, Jon
Tyrrell, Andy M.
author_sort Buchanan, Edgar
collection PubMed
description Often in swarm robotics, an assumption is made that all robots in the swarm behave the same and will have a similar (if not the same) error model. However, in reality, this is not the case, and this lack of uniformity in the error model, and other operations, can lead to various emergent behaviors. This paper considers the impact of the error model and compares robots in a swarm that operate using the same error model (uniform error) against each robot in the swarm having a different error model (thus introducing error diversity). Experiments are presented in the context of a foraging task. Simulation and physical experimental results show the importance of the error model and diversity in achieving the expected swarm behavior.
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spelling pubmed-98459312023-01-19 A study of error diversity in robotic swarms for task partitioning in foraging tasks Buchanan, Edgar Alden, Kieran Pomfret, Andrew Timmis, Jon Tyrrell, Andy M. Front Robot AI Robotics and AI Often in swarm robotics, an assumption is made that all robots in the swarm behave the same and will have a similar (if not the same) error model. However, in reality, this is not the case, and this lack of uniformity in the error model, and other operations, can lead to various emergent behaviors. This paper considers the impact of the error model and compares robots in a swarm that operate using the same error model (uniform error) against each robot in the swarm having a different error model (thus introducing error diversity). Experiments are presented in the context of a foraging task. Simulation and physical experimental results show the importance of the error model and diversity in achieving the expected swarm behavior. Frontiers Media S.A. 2023-01-04 /pmc/articles/PMC9845931/ /pubmed/36686209 http://dx.doi.org/10.3389/frobt.2022.904341 Text en Copyright © 2023 Buchanan, Alden, Pomfret, Timmis and Tyrrell. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Robotics and AI
Buchanan, Edgar
Alden, Kieran
Pomfret, Andrew
Timmis, Jon
Tyrrell, Andy M.
A study of error diversity in robotic swarms for task partitioning in foraging tasks
title A study of error diversity in robotic swarms for task partitioning in foraging tasks
title_full A study of error diversity in robotic swarms for task partitioning in foraging tasks
title_fullStr A study of error diversity in robotic swarms for task partitioning in foraging tasks
title_full_unstemmed A study of error diversity in robotic swarms for task partitioning in foraging tasks
title_short A study of error diversity in robotic swarms for task partitioning in foraging tasks
title_sort study of error diversity in robotic swarms for task partitioning in foraging tasks
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9845931/
https://www.ncbi.nlm.nih.gov/pubmed/36686209
http://dx.doi.org/10.3389/frobt.2022.904341
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