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This paper proposes a novel swarm-based control algorithm for exploration andcoverage of unknown environments, while maintaining a formation that permitsshort-range communication. The algorithm combines two elements: swarm rules formaintaining a close-knit formation and frontier search for driving explorationand coverage. Inspired by natural systems in which large numbers of simpleagents (e.g., schooling fish, flocking birds, swarming insects) performcomplicated collective behaviors for efficiency and safety, the first elementuses three simple rules to maintain a swarm formation. The second elementprovides a means to select promising regions to explore (and cover) byminimising a cost function involving robots' relative distance to frontiercells and the frontier's size. We tested the performance of our approach onheterogeneous and homogeneous groups of mobile robots in differentenvironments. We measure both coverage performance and swarm formationstatistics as indicators of the robots' ability to explore effectively whilemaintaining a formation conducive to short-range communication. Through aseries of comparison experiments, we demonstrate that our proposed strategy hassuperior performance to recently presented map coverage methodologies andconventional swarming methods.

Frontier-led Swarming: Robust Multi-Robot Coverage of Unknown Environments