Multi‐narrow type obstacle avoidance algorithm for UAV swarm based on game theory
Ye Lin, Zhenyu Na, Jialiang Liu, Yun Lin · Advanced Control for Applications · 2023
Abstract A Flocking obstacle avoidance algorithm based on the extensive game with perfect information is proposed for the blockage problem of UAV swarm in front of multi‐narrow type obstacles. The two UAVs closest to the target are selected as participants of the game, and the game tree is defined to determine the combination of the motion strategies of the two UAVs to obtain the payoff matrix. Determine the subgame perfect Nash equilibrium to get the optimal strategy, and give the UAVs different motion states respectively so as to ensure that the UAVs can successfully pass multi‐narrow type obstacles. Simulation results demonstrate that the proposed algorithm has a higher over‐hole rate in the case of the multi‐narrow type obstacle compared to the static game‐based Flocking obstacle avoidance algorithm.