UAV Swarm Communication Aware Formation Control via Deep Q Network

Chengtao Xu, Kai Zhang, H. Song
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引用次数: 3

Abstract

We propose a DQN based reinforcement learning method in swarm communication constraint based formation control with target searching function. A decentralized communication performance indicator is applied in evaluating the UAV’s formation control in simulating a more realistic wireless communication environment between each UAV. A target searching model based on communication aware formation control is presented. The simulation results show that the trained model with state observation space and one thrust action space could be applied in the larger swarm system’s group formation and target point tracking.
基于深度Q网络的无人机群通信感知编队控制
提出了一种基于DQN的强化学习方法,用于具有目标搜索功能的群体通信约束编队控制。为了模拟更真实的无人机间无线通信环境,采用分散式通信性能指标评价无人机的编队控制能力。提出了一种基于通信感知编队控制的目标搜索模型。仿真结果表明,该模型具有状态观测空间和单推力作用空间,可以应用于大型群系统的编队和目标点跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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