CASIA OpenIR  > 学术期刊  > 自动化学报
无人机反应式扰动流体路径规划
吴健发; 王宏伦; 王延祥; 刘一恒
Source Publication自动化学报
ISSN0254-4156
2023
Volume49Issue:2Pages:272-287
Abstract针对复杂三维障碍环境,提出一种基于深度强化学习的无人机(Unmanned aerial vehicles, UAV)反应式扰动流体路径规划架构.该架构以一种受约束扰动流体动态系统算法作为路径规划的基本方法,根据无人机与各障碍的相对状态以及障碍物类型,通过经深度确定性策略梯度算法训练得到的动作网络在线生成对应障碍的反应系数和方向系数,继而可计算相应的总和扰动矩阵并以此修正无人机的飞行路径,实现反应式避障.此外,还研究了与所提路径规划方法相适配的深度强化学习训练环境规范性建模方法.仿真结果表明,在路径质量大致相同的情况下,该方法在实时性方面明显优于基于预测控制的在线路径规划方法.
Keyword无人机 反应式路径规划 受约束扰动流体动态系统 深度强化学习 训练环境
DOI10.16383/j.aas.c210231
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/56191
Collection学术期刊_自动化学报
Recommended Citation
GB/T 7714
吴健发,王宏伦,王延祥,等. 无人机反应式扰动流体路径规划[J]. 自动化学报,2023,49(2):272-287.
APA 吴健发,王宏伦,王延祥,&刘一恒.(2023).无人机反应式扰动流体路径规划.自动化学报,49(2),272-287.
MLA 吴健发,et al."无人机反应式扰动流体路径规划".自动化学报 49.2(2023):272-287.
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