导航

ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2022, Vol. 43 ›› Issue (5): 325311.doi: 10.7527/S1000-6893.2021.25311

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

Cooperative pursuit strategy for multi-UAVs based on DE-MADDPG algorithm

FU Xiaowei, WANG Hui, XU Zhe   

  1. School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China
  • Received:2021-01-22 Revised:2021-03-06 Published:2021-03-26
  • Supported by:
    Aeronautical Science Foundation of China (202023053001)

Abstract: To solve the problem of pursuit-evasion game in multi-UAVs confronting the fast target, we study the cooperative pursuit strategy of multi-UAVs. We train the strategy using the DE composed Multi-Agent Deep Deterministic Policy Gradient (DE-MADDPG) algorithm, and design two reward functions:global reward function, and local reward function. The trained multi-UAVs can effectively carry out the cooperative pursuit mission. Simulation results show the effectiveness of the proposed method. The multi-UAVs can take advantage of numbers and cooperative work to complete a rounding up of the fast target. It is also verified that the proposed method can achieve faster convergence effect than the basic MADDPG algorithm.

Key words: multi-UAVs, cooperative pursuit, DE-MADDPG, multi-agent deep reinforcement learning, confront strategy

CLC Number: