Connectivity and Safety Analysis of Large Scale UAV Swarms: Based on Flight Scheduling

Unmanned Aerial Vehicle (UAV) swarms are increasingly being used to conduct different military missions. However, highly varying environmental factors affect the inter-UAV minimum safe distance creating collision, and those at the edge of the swarm more vulnerable to connectivity loss. In this paper, novel scheduling algorithm for updating UAV positions to keep the safe separation distance between individual UAVs in the swarm is presented. In addition, an extensive study of the effect of flight and maneuvering tactics choice on the connectivity and safety of a large-scale swarm is presented. Our analysis demonstrates that in windy environmental conditions, the proposed algorithm is successful in optimally and adaptively selecting the UAVs speed so that the swarm reaches the target destination with the minimum/desired flight time while maintaining the safety of most (all, if possible) of the UAVs. By taking three different tactics, the proposed algorithm achieved an increase of nearly 30%, 56%, and 86% separation distance with tactics 1, 2, and 3 respectively compared to previous work. On the other hand, it is observed that under ideal communications scenarios, inter-UAV connectivity and safety are inversely related. A swarm algorithm that provides good connectivity may lead to high probability of inter-swarm UAV collision. On the contrary, when an algorithm tries to give enough separation between UAVs, the connectivity outage probability is seen to increase. Overall, these results show that the proposed model is satisfactory and outperforms the other approaches of updating positions randomly despite the extent of change in environmental factors.