Dual-game based UAV swarm obstacle avoidance algorithm in multi-narrow type obstacle scenarios

Abstract

Due to the advantages of rapid deployment, flexible response and strong invulnerability, unmanned aerial vehicle (UAV) swarm has been widely applied in collaborative warfare and emergency communication. However, UAV swarm in complex environments is prone to chaotic collapse due to obstructions. A UAV swarm obstacle avoidance system model for multi-narrow type obstacles is established. Due to the fact that only one UAV is allowed to pass through each small hole at any given moment, addressing the issue of congestion caused by swarming effects becomes crucial in addition to managing the competitive allocation of multiple UAVs to multiple holes. Aiming at this problem, a dual-game real-time obstacle avoidance scheme is proposed for UAV swarm with multi-narrow type obstacle scenarios, which divides the flight process of the UAV swarm into two stages: maintaining the flight state of the UAV swarm unchanged when no obstacles are encountered, and implementing matching separation and motion state switching by means of dual-game strategy when facing multi-narrow type obstacles, ultimately achieving orderly passage after multiple rounds of games. For the proposed scheme, a dual-game based Flocking (DGF) obstacle avoidance algorithm is proposed. Specifically, the motion state of each UAV obtained from the game is parameterized and integrated with the Flocking algorithm to calculate the motion control input for each UAV. The solution is iteratively obtained until the UAV swarm completes the obstacle avoidance. Simulation results demonstrate that the proposed DGF algorithm not only enables smooth obstacle avoidance for the UAV swarm in multi-narrow type obstacle scenarios, but also effectively resolves the internal chaos problem in the UAV swarm, thereby preventing rigid collisions.