  This paper proposes a novel swarm-based control algorithm for exploration and
coverage of unknown environments, while maintaining a formation that permits
short-range communication. The algorithm combines two elements: swarm rules for
maintaining a close-knit formation and frontier search for driving exploration
and coverage. Inspired by natural systems in which large numbers of simple
agents (e.g., schooling fish, flocking birds, swarming insects) perform
complicated collective behaviors for efficiency and safety, the first element
uses three simple rules to maintain a swarm formation. The second element
provides a means to select promising regions to explore (and cover) by
minimising a cost function involving robots' relative distance to frontier
cells and the frontier's size. We tested the performance of our approach on
heterogeneous and homogeneous groups of mobile robots in different
environments. We measure both coverage performance and swarm formation
statistics as indicators of the robots' ability to explore effectively while
maintaining a formation conducive to short-range communication. Through a
series of comparison experiments, we demonstrate that our proposed strategy has
superior performance to recently presented map coverage methodologies and
conventional swarming methods.
