Persistent Area Coverage for Swarms Utilizing Deployment Entropy with Potential Fields

Abstract

Our work focuses on persistent area coverage using a large number of agents. This is a valuable capability for multi-agent and swarm-based systems. Specifically, we strive to effectively disperse the agents throughout an area of interest such that it is sufficiently and persistently covered by the sensing sweeps of the agents. This capability can be applied toward tasks such as surveillance, target tracking, search and rescue, and exploration of unknown areas. Many methods can be implemented as behaviors for the agents to accomplish this. One strategy involves measuring area coverage using a measure known as deployment entropy, which relies on the area being divided into regions. Deployment entropy expresses the coverage of the area as the uniformity of agents per region across all regions. This strategy is useful due to its low computational complexity, scalability, and potential implementation on decentralized systems. Though previous results are promising, they focus on instantaneous area coverage and are not persistent. It is proposed in this paper that combining the split region strategy with the implementation of potential fields can retain the benefits of the split region strategy while increasing the spread of agents and therefore the total area that is persistently covered by the agents’ sensors. This approach is implemented and demonstrated to be effective through simulations of various numbers and densities of agents. Ultimately, these studies showed that a greater spread of agents and increased sensor coverage is obtained when compared to previous results not using potential fields with deployment entropy.