Drone Swarms in Forest Firefighting: A Local Development Case Study of Multi-Level Human-Swarm Interaction

Abstract

Swarms of autonomous and coordinating Unmanned Aerial Vehicles (UAVs) are rapidly being developed to enable simultaneous control of multiple UAVs. In the field of Human-Swarm Interaction (HSI), researchers develop and study swarm algorithms and various means of control and evaluate their cognitive and task performance. There is, however, a lack of research describing how UAV swarms will fit into future real-world domain contexts. To remedy this, this paper describes a case study conducted within the community of firefighters, more precisely two Swedish fire departments that regularly deploy UAVs in fire responses. Based on an initial description of how their UAVs are used in a forest firefighting context, participating UAV operators and unit commanders envisioned a scenario that showed how the swarm and its capabilities could be utilized given the constraints and requirements of a forest firefighting mission. Based on this swarm scenario description we developed a swarm interaction model that describes how the operators’ interaction traverses multiple levels ranging from the entire swarm, via subswarms and individual UAVs, to specific sensors and equipment carried by the UAVs. The results suggest that human-in-the-loop simulation studies need to enable interaction across multiple swarm levels as this interaction may exert additional cognitive strain on the human operator.