Network Analysis of Decentralized Fault-Tolerant UAV Swarm Coordination in critical Missions

Unmanned Aerial Vehicles (UAVs) have gained prominence across various sectors for their versatile applications. While their advantages are evident, addressing concerns associated with their deployment is essential to ensure reliability. This study presents an innovative approach for coordinating a group of UAVs in aerial survey missions. The decentralized strategy presented in this article allow UAVs to self-organize into linear formation, optimize their coverage paths, and adapt to agent failures, thereby ensuring efficient and adaptive mission execution. The strategy has been tested and validated on two different platforms: the inter-UAV communication performance is evaluated on NS-3 simulator to measure metrices such as packet delivery ratio, throughput, delay, and routing overhead within the UAV swarms, while mission efficiency and fault tolerance is analyzed on ROS framework, and visualized on Gazebo simulator with real-time parameters. Through experimental results, we show that, after proper tuning of control parameters, the approach succeeds in flock formation with high level of fault tolerance, offering higher efficiency in terms of mission time, transmission delay, packet delivery rate, and control overhead, when compared to the benchmark approaches.