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

TL;DR

This paper introduces a swarm-based control algorithm for multi-robot exploration that combines formation maintenance with frontier search, enabling effective coverage of unknown environments while supporting short-range communication.

Contribution

It presents a novel algorithm integrating swarm rules and frontier search, outperforming existing coverage and swarming methods in unknown environments.

Findings

Superior coverage performance compared to recent methods

Effective formation maintenance for communication

Validated on heterogeneous robot groups

Abstract

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.