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Advancements in UAV Path Planning:A Deep Reinforcement Learning Approach with Soft Actor-Critic for Enhanced Navigation

Jingrui Guo Guanzhong Zhou Hailong Huang Chao Huang

无人系统（英文）2025，Vol.13Issue(4)：1065-1084,20.

无人系统（英文）2025，Vol.13Issue(4)：1065-1084,20.DOI:10.1142/S2301385025500669

Advancements in UAV Path Planning:A Deep Reinforcement Learning Approach with Soft Actor-Critic for Enhanced Navigation

Jingrui Guo ¹Guanzhong Zhou ²Hailong Huang ²Chao Huang¹

作者信息

1. Department of Industrial and Systems Engineering,The Hong Kong Polytechnic University,Hung Hom,Hong Kong 999077,P.R.China
2. Department of Aeronautical and Aviation Engineering,The Hong Kong Polytechnic University,Hung Hom,Hong Kong 999077,P.R.China
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摘要

关键词

Unmanned aerial vehicles(UAVs)/reinforcement learning/soft actor-critic algorithm

Key words

Unmanned aerial vehicles(UAVs)/reinforcement learning/soft actor-critic algorithm

引用本文复制引用

Jingrui Guo,Guanzhong Zhou,Hailong Huang,Chao Huang..Advancements in UAV Path Planning:A Deep Reinforcement Learning Approach with Soft Actor-Critic for Enhanced Navigation[J].无人系统（英文）,2025,13(4):1065-1084,20.

基金项目

This work was supported by the Hong Kong Polytechnic University via Project P0038447. （）

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