Increasing Operational Resiliency of UAV Swarms: An Agent-Focused Search and Rescue Framework

Abstract

Resilient UAV (Unmanned Aerial Vehicle) swarm operations are a complex research topic where the dynamic environments in which they work significantly increase the chance of systemic failure due to disruptions. Most existing SAR (Search and Rescue) frameworks for UAV swarms are application-specific, focusing on rescuing external non-swarm agents, but if an agent in the swarm is lost, there is inadequate research to account for the resiliency of the UAV swarm itself. This study describes the design and deployment of a Swarm Specific SAR (SS-SAR) framework focused on UAV swarm agents. This framework functions as a resilient mechanism by locating and attempting to reconnect communications with lost UAV swarm agents. The developed framework was assessed over a series of performance tests and environments, both real-world hardware and simulation experiments. Experimental results showed successful recovery rates in the range of 40%–60% of all total flights conducted, indicating that UAV swarms can be made more resilient by including methods to recover distressed agents. Decision-based modular frameworks such as the one proposed here lay the groundwork for future development in attempts to consider the swarm agents in the search and rescue process.