  Drawing inspiration from honeybee swarms' nest-site selection process, we
assess the ability of a kilobot robot swarm to replicate this captivating
example of collective decision-making. Honeybees locate the optimal site for
their new nest by aggregating information about potential locations and
exchanging it through their waggle-dance. The complexity and elegance of
solving this problem relies on two key abilities of scout honeybees:
self-discovery and imitation, symbolizing independence and interdependence,
respectively. We employ a mathematical model to represent this nest-site
selection problem and program our kilobots to follow its rules. Our experiments
demonstrate that the kilobot swarm can collectively reach consensus decisions
in a decentralized manner, akin to honeybees. However, the strength of this
consensus depends not only on the interplay between independence and
interdependence but also on critical factors such as swarm density and the
motion of kilobots. These factors enable the formation of a percolated
communication network, through which each robot can receive information beyond
its immediate vicinity. By shedding light on this crucial layer of complexity
--the crowding and mobility conditions during the decision-making--, we
emphasize the significance of factors typically overlooked but essential to
living systems and life itself.
