水下无人系统学报2025，Vol.33Issue(2)：194-203,10.DOI:10.11993/j.issn.2096-3920.2025-0034
无人艇集群路径规划研究综述:深度强化学习
A Review of Research on Path Planning of Unmanned Surface Vessel Swarm:Deep Reinforcement Learning
摘要
Abstract
An unmanned surface vessel(USV)swarm has shown significant advantages in complex marine missions,but its path planning faces high-dimensional,dynamic,and multi-constraint challenges.Traditional path planning algorithms are difficult to meet increasingly complex needs due to weak coordination mechanisms and insufficient adaptability,while the development of deep reinforcement learning(DRL)technology provides a new research direction for the path planning of USV swarms.This paper systematically reviewed the technical framework and typical algorithms for collaborative path planning of USV swarms based on DRL.Firstly,the technical evolution context and multi-dimensional constraints of path planning of USV swarms were sorted out,and the applicable scenarios and limitations of centralized and distributed decision frameworks were analyzed.Secondly,the principle,application scenarios,and improvement directions of various typical DRL algorithms were discussed,and their advantages and disadvantages were analyzed.Finally,the main challenges and development directions in this field were summarized.This paper aims to provide a reference for the research on DRL-based collaborative path planning of USV swarms.关键词
无人艇集群/协同路径规划/深度强化学习Key words
unmanned surface vessel swarm/collaborative path planning/deep reinforcement learning分类
武器工业引用本文复制引用
侯玉立,王宁,邱赤东,翁永鹏..无人艇集群路径规划研究综述:深度强化学习[J].水下无人系统学报,2025,33(2):194-203,10.基金项目
国家自然科学基金项目(U23A20680,52271306) （U23A20680,52271306）
国家拔尖人才专项支持计划项目(SQ2022QB00329) （SQ2022QB00329）
辽宁省领军人才项目(XLYC2202005) （XLYC2202005）
大连市科技创新基金重大基础研究项目(2023JJ11CG009) （2023JJ11CG009）
中央高校基本科研业务费专项资金资助(3132023501). （3132023501）
