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

Edgar Buchanan Berumen; Kieran James Alden; Andy Pomfret; Jon Timmis; Andy Tyrrell

doi:10.3389/frobt.2022.904341

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

Edgar Buchanan Berumen, Kieran James Alden, Andy Pomfret, Jon Timmis, Andy Tyrrell

Electronic Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

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 behaviours. 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 expected swarm behaviour.

Original language	English
Number of pages	30
Journal	Frontiers in Robotics and AI
Volume	9
DOIs	https://doi.org/10.3389/frobt.2022.904341
Publication status	Published - 4 Jan 2023

Bibliographical note

This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

Keywords

swarm robotics
fault-tolerance
error diversity
Task partitioning
foraging

Access to Document

10.3389/frobt.2022.904341Licence: CC BY

Draft of the paper
This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details
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Cite this

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