Swarm path planning for the deployment of drones in emergency response missions

The rapid development of Unmanned Aerial Vehicles (UAV) technologies over the recent years has been decisive for their integration in emergency response missions. While initial use by first responders focused on manual operations, the need to improve utilization necessitates higher levels of automation. Contributing towards that end-goal, this work derives swarm path planning algorithms that can effectively and efficiently be employed to search and monitor the operating field. A swarm is composed by two or more units, that coordinate to achieve the mission objectives including minimizing search time while ensuring coverage of the field. A graph theoretic approach is followed to model the underlying swarm path planning problem and mathematical programming is employed to describe a number of important variants of the cooperative strategies that arise. Thereafter, 4 algorithms are derived to solve the swarm path planning problem that are computationally efficient to implement and use in practice. A thorough performance evaluation is conducted to understand the advantages and disadvantages of each heuristic using a number of key performance metrics