Robust UAV Swarm Coordination in IoT-Constrained Wireless Environments: A Comparative Study

Abstract

Unmanned Aerial Vehicle (UAV) swarms are being increasingly integrated into Internet of Things (IoT) applications, such as disaster response, environmental monitoring, and cooperative sensing. In practical wireless environments, however, packet loss and communication delay may significantly affect coordination quality and swarm stability. This study investigates the robustness of two representative decentralized swarm coordination approaches, namely, the Olfati-Saber (OS) algorithm and the Vásárhelyi (V) algorithm, under IoT-constrained wireless communication conditions. Packet loss is modelled using a Bernoulli process, while communication delay is approximated through a first-order lag model. Simulations are conducted in obstacle-rich environments with different swarm sizes to evaluate motion smoothness, stability, and connectivity under both ideal and non-ideal communication conditions. Simulation results show that the Vásárhelyi algorithm consistently maintains smoother trajectories and stronger coordination stability under packet loss and communication delay, whereas the Olfati-Saber algorithm achieves faster motion at the expense of increased oscillations. The comparison provides practical insight into how different decentralized coordination principles respond to communication degradation, offering guidance for selecting swarm algorithms in IoT-enabled UAV applications.