Target Enclosing Control of Symmetric Unmanned Aerial Vehicle Swarms Based on Crowd Entropy

Drone swarms often need to fly cooperatively in complex spaces filled with multiple obstacles. In such scenarios, they must meet the requirements of both external obstacle avoidance and internal collision avoidance while maintaining a certain topological configuration among individuals. This easily leads to problems such as congestion, oscillation, and poor stability, including being out of control. Thus, it is essential to measure system-wide stability, regulate the autonomous cooperative evolution of swarms, and enhance their adaptation to environmental changes. To solve this problem, using the symmetric unmanned aerial vehicle (UAV) swarm as the research object, a group entropy measurement theory for the stability of drone swarms is proposed. We introduce an entropy-based metric for group motion consistency. This metric serves as a fitness index for individual collaboration, enabling adaptive adjustment of drone swarm coherence under multi-obstacle conditions. Finally, simulation experiments are conducted to verify the effectiveness of the established theory and algorithm.