Research on Multi-UAV Aggregation Task Based on GA-TD3 Algorithm - Zhang, Yaozhong; Ding, Meiyan; Yuan, Yao; Zhang, Jiandong; Shi, Guoqing; Yang, Qiming (Chinese Control Conference, 2024)
The aggregation task is one of the typical tasks of Unmanned A erial Vehicle (UAV) operations and has always been a hot research topic. With the development of technology and the continuous proves of war, multi-UAV have significant advantages in combat compared to single UAV. To address the intelligent control problem of multi-UAV aggregation task, this paper proposes a Twin Delayed Deep Deterministic policy gradient (TD3) algorithm based on an evolutionary algorithm and introduces an evolutionary reinforcement learning framework. A learning cross operator is proposed to make offspring inherit parent features through training. To avoid high interaction costs, a critic network-assisted evaluation mechanism is proposed, and a response control decision is designed to combine real and virtual fitness to improve accuracy. Therefore, a Twin Delayed Deep Deterministic policy gradient algorithm combining Genetic Algorithm enhanced by learning cross factors and auxiliary evaluation (GA-TD3) is proposed. Simulation results show that GA-TD3 has better training effects and generalization.