Cooperative Hunting by UAV Swarm in 3D Unknown Complex Environment

To address the challenge of cooperative hunting by unmanned aerial vehiclel (UAV) swarms in 3D unknown complex environments, we present a hunting algorithm that combines an expansion algorithm with a 3D simplified virtual force hunting model (3D-ESVFH). First, we develop a UAV individual motion model. For navigating non-convex obstacles in 3D unknown complex environments, we employ an expansion algorithm that combines hemispherical and spherical expansion. This process abstracts natural hunting behavior into a 3D simplified virtual force hunting model. We then use the Lyapunov function to analyze system stability. Simulation results under different conditions show that our method maintains effective hunting formations while avoiding obstacles. Compared to the following obstacle algorithm and the loose-preference rule, the proposed method reduces time and path consumption by 12.72%, 9.79%, and 20.05%, 8.35%, respectively.