Research of multiple UAVs pursuit evasion based on PER IDQN

DOI:	10.11809/bqzbgcxb2023.09.003
Keywords:	maneuvering target; multiple UAVs; pursuit evasion; deep reinforcement learning; cooperative decision
Abstract:	Aiming at the problem of the limited capability of a single UAV and the inability to suppress enemy maneuvering targets in complex military scenarios, a novel approach of multiple UAVs pursuit evasion based on deep reinforcement learning is proposed. Based on the pursuit evasion game, a rasterized scene is constructed and the specific environment is explained. In the framework of deep reinforcement learning, factors such as the proximity of multiple UAVs to the target and the safe avoidance of obstacles are considered, and the state variables, action outputs, and reward functions of each UAV are designed pertinently. The simulation results show that the multiple UAVs trained based on deep reinforcement learning PER IDQN algorithm can make cooperative decision and achieve threat avoidance, and complete the task of pursuing the maneuvering target.
Published:	2023-09-28
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