Obstacle avoidance control for large-scale loitering munition swarm formation based on improved β agents

Considering the environmental obstacles in real battlefields, it is essential to establish an obstacle avoidance algorithm for a large-scale loitering munition cluster to ensure overall stability and an orderly formation while performing formation flight tasks in complex environments. Building upon an established detector-based obstacle model, the generation mechanism, force fields, and virtual velocity specifically of the β agent for large-scale loitering munition swarm are designed. Crucially, the improved β agent is incorporated into the local interaction rules, leading to the innovative proposal of the obstacle avoidance control algorithm. Meanwhile, the stability and effectiveness are rigorously proven. Simulation results further demonstrate that the improved β agent-based obstacle avoidance algorithm enables the large-scale loitering munition swarm to avoid detected obstacles while preventing internal collisions, control divergence, and other issues arising from disorder and chaos within the swarm.