Dynamic Self-Organization and Safe Navigation for Hierarchical Embodied Swarms

This paper is concerned with cooperative multi-UAV navigation in a planar obstacle environment. A hierarchical embodied swarm framework with leader, subleader, and follower roles is proposed. At the high level, a passable-corridor-driven decision layer is developed to perform split–merge reconfiguration and navigate/encircle mode switching. At the low level, a multi-term force synthesis controller is constructed for formation maintenance, inter-agent collision avoidance, obstacle avoidance, and sub-swarm cohesion. To accommodate both rule-based and local large language model (LLM) decisions, a feasibility projection operator is introduced so that only kinematically admissible structural actions are executed. In addition, a LiDAR-based obstacle-repulsion term and an occlusion-attenuated attraction mechanism are incorporated to improve navigation safety in cluttered environments. A Lyapunov analysis of the smooth controller core further certifies that, for a known (possibly time-varying) cruise velocity compensated by feedforward, the formation tracking error is uniformly bounded by the initial energy. Finally, multi-seed numerical simulations verify the proposed framework in standard, ablated, and complex scenarios. In the hardest alternating-gate scenario, the LLM-assisted variant raises mission success from 0.000 to 0.100, increases the goal-reaching ratio from 0.025 to 0.125, and reduces the mean terminal error from 44.738m to 39.851m, showing the value of semantic high-level reconfiguration under tight passage constraints.