Role Partitioned Swarm Intelligence for Resilient UAV Coordination in Contested Electromagnetic Environments: A Soccer Field Swarm Formation Framework

Abstract Autonomous unmanned aerial vehicle (UAV) swarms must coordinate asset protection, threat interception, and collision avoidance even when electronic warfare degrades inter-agent communication. This paper presents Role-Partitioned Swarm Intelligence (RPSI) and its Soccer Field Swarm Formation (SFSF) implementation, which organise agents into Defender, Midfielder, and Forward roles for asset shielding, interception and relay, and outer-layer engagement. The proposed architecture combines rigid-body dynamics on SE(3), Covariance Intersection (CI) for distributed estimation, role-conditioned artificial potential fields, a decentralised High-Order Control Barrier Function (HO-CBF) quadratic-program safety filter, and a communication-health-triggered resilience mode that freezes role assignments and continues with local sensing. A dwell-time-constrained switched-system analysis is provided under stated feasibility and bounded-switching assumptions. In the PX4-based Software-in-the-Loop (SITL) evaluation, RPSI-SFSF achieved 92.7% asset-protection effectiveness (APE) under nominal communication, compared with 86.1% for distributed model predictive control, and 79.8% versus 57.6% under the C5 condition with 0% packet availability. In the 120-run reduced-order packet-drop experiment, RPSI exceeded the homogeneous controller by 8.75, 3.75, and 23.75 percentage points at 100%, 50%, and 0% target-state update packet delivery, respectively. Across-run standard deviations ranged from 10.26 to 20.32 points, and some runs at 100% and 50% delivery fell below the 5.0 m design threshold.