基于深度强化学习的UAV航路自主引导机动控制决策算法

V249.4; 针对无人机(unmanned aerial vehicle,UAV)航路终端约束情况下航路自主引导机动控制决策问题,采用Markov决策过程模型建立UAV自主飞行机动模型,基于深度确定性策略梯度提出UAV航路自主引导机动控制决策算法,拟合UAV航路自主引导机动控制决策函数与状态动作值函数,生成最优决策网络,开展仿真验证.仿真结果表明,该算法实现了UAV在任意位置/姿态的初始条件下,向航路目标点的自主飞行,可有效提高UAV机动控制的自主性....

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Published in系统工程与电子技术 Vol. 42; no. 7; pp. 1567 - 1574
Main Authors 张堃, 李珂, 时昊天, 张振冲, 刘泽坤
Format Journal Article
LanguageChinese
Published 西北工业大学电子信息学院,陕西西安710072 01.07.2020
光电控制技术重点实验室,河南洛阳471000%西北工业大学电子信息学院,陕西西安,710072
Subjects
Markov决策过程
深度确定性策略梯度法
机动控制决策
深度强化学习
自主引导
Online AccessGet full text
ISSN1001-506X
DOI10.3969/j.issn.1001-506X.2020.07.19

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Abstract V249.4; 针对无人机(unmanned aerial vehicle,UAV)航路终端约束情况下航路自主引导机动控制决策问题,采用Markov决策过程模型建立UAV自主飞行机动模型,基于深度确定性策略梯度提出UAV航路自主引导机动控制决策算法,拟合UAV航路自主引导机动控制决策函数与状态动作值函数,生成最优决策网络,开展仿真验证.仿真结果表明,该算法实现了UAV在任意位置/姿态的初始条件下,向航路目标点的自主飞行,可有效提高UAV机动控制的自主性.
AbstractList V249.4; 针对无人机(unmanned aerial vehicle,UAV)航路终端约束情况下航路自主引导机动控制决策问题,采用Markov决策过程模型建立UAV自主飞行机动模型,基于深度确定性策略梯度提出UAV航路自主引导机动控制决策算法,拟合UAV航路自主引导机动控制决策函数与状态动作值函数,生成最优决策网络,开展仿真验证.仿真结果表明,该算法实现了UAV在任意位置/姿态的初始条件下,向航路目标点的自主飞行,可有效提高UAV机动控制的自主性.
Author 张堃
李珂
张振冲
时昊天
刘泽坤
AuthorAffiliation 西北工业大学电子信息学院,陕西西安710072;光电控制技术重点实验室,河南洛阳471000%西北工业大学电子信息学院,陕西西安,710072
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Author_FL ZHANG Kun
ZHANG Zhenchong
SHI Haotian
LI Ke
LIU Zekun
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DocumentTitle_FL Autonomous guidance maneuver control and decision-making algorithm based on deep reinforcement learning UAV route
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Keywords Markov决策过程
深度确定性策略梯度法
机动控制决策
深度强化学习
自主引导
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Publisher 西北工业大学电子信息学院,陕西西安710072
光电控制技术重点实验室,河南洛阳471000%西北工业大学电子信息学院,陕西西安,710072
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Snippet V249.4; 针对无人机(unmanned aerial vehicle,UAV)航路终端约束情况下航路自主引导机动控制决策问题,采用Markov决策过程模型建立UAV自主飞行机动模型,基于深度确定性策略...
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Title 基于深度强化学习的UAV航路自主引导机动控制决策算法
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