Research Article
Revisiting BEECLUST: Aggregation of Swarm Robots with Adaptiveness to Different Light Settings
@ARTICLE{10.4108/eai.3-12-2015.2262877, author={Mostafa Wahby and Alexander Weinhold and Heiko Hamann}, title={Revisiting BEECLUST: Aggregation of Swarm Robots with Adaptiveness to Different Light Settings}, journal={EAI Endorsed Transactions on Collaborative Computing}, volume={2}, number={9}, publisher={ACM}, journal_a={CC}, year={2016}, month={5}, keywords={beeclust, adaptive behavior, collective decision making, aggregation, swarm robots}, doi={10.4108/eai.3-12-2015.2262877} }- Mostafa Wahby
Alexander Weinhold
Heiko Hamann
Year: 2016
Revisiting BEECLUST: Aggregation of Swarm Robots with Adaptiveness to Different Light Settings
CC
EAI
DOI: 10.4108/eai.3-12-2015.2262877
Abstract
Aggregation is a crucial task in swarm robotics to ensure cooperation. We investigate the task of aggregation on an area specified indirectly by certain environmental features, here it is a light distribution. We extend the original BEECLUST algorithm, that implements an aggregation behavior, to an adaptive variant that automatically adapts to any light conditions. We compare these two control algorithms in a number of swarm robot experiments with different light conditions. The improved, adaptive variant is found to be significantly better in the tested setup.
Copyright © 2015 M. Wahby et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
