Dynamic Frontier-Led Swarming: Multi-Robot Repeated Coverage in Dynamic Environments

Abstract

A common assumption of coverage path planning research is a static environment. Such environments require only a single visit to each area to achieve coverage. However, some real-world environments are characterised by the presence of unexpected, dynamic obstacles. They require areas to be revisited periodically to maintain an accurate coverage map, as well as reactive obstacle avoidance. This paper proposes a novel swarm-based control algorithm for multi-robot exploration and repeated coverage in environments with unknown, dynamic obstacles. The algorithm combines two elements: frontier-led swarming for driving exploration by a group of robots, and pheromone-based stigmergy for controlling repeated coverage while avoiding obstacles. We tested the performance of our approach on heterogeneous and homogeneous groups of mobile robots in different environments. We measure both repeated coverage performance and obstacle avoidance ability. Through a series of comparison experiments, we demonstrate that our proposed strategy has superior performance to recently presented multi-robot repeated coverage methodologies.