Frontier-led Swarming: Robust Multi-Robot Coverage of Unknown Environments
This addresses the problem of efficient and robust environmental coverage for robotics applications, though it appears incremental as it combines existing swarm and frontier concepts.
The paper tackles the problem of multi-robot exploration and coverage of unknown environments while maintaining formation for communication, proposing a swarm-based control algorithm that combines formation rules with frontier search. The result demonstrates superior performance compared to existing methods in coverage and formation metrics.
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.