Revisiting BEECLUST: Aggregation of Swarm Robots with Adaptiveness to Different Light Settings

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 ex-tend 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.