| 引用本文: |
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费陈,贺拥亮,陈硕,等.面向海上复杂环境的无人艇集群航迹规划发展综述[J].电讯技术,2025,(12):2173 - 2180. [点击复制]
- FEI Chen,HE Yongliang,CHEN Shuo,et al.Development of Unmanned Boat Cluster Trajectory Planning for Complex Marine Environments:an Overview[J].,2025,(12):2173 - 2180. [点击复制]
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| 摘要: |
| 随着海洋战略地位的不断提升,无人艇集群展现出巨大效能和应用潜力,其中以海上环境下无人艇集群应用最具有前景。以海上复杂环境为背景,首先梳理了国内外无人艇的发展现状,并阐述基于海上复杂环境下的三维刻画、敌情动态分析、无人艇机动性约束等特点,然后重点剖析基于机器人模拟仿真软件(Robot Operating System Gazebo,ROSG)仿真的三维建模分析、基于数学建模的无人艇机动性约束及威胁区域分析、基于迁移强化学习的无人艇集群航迹规划等关键技术,最后展望了无人艇集群航迹规划的发展趋势,以期为无人艇集群航迹规划应用提供借鉴。 |
| 关键词: 海上环境 无人艇集群 航迹规划 强化学习 数学建模 |
| DOI:10.20079/j.issn.1001-893x.240511001 |
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| 基金项目:某科技创新项目(ZZKY20253139) |
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| Development of Unmanned Boat Cluster Trajectory Planning for Complex Marine Environments:an Overview |
| FEI Chen,HE Yongliang,CHEN Shuo,ZHANG Fan,LU Ye,XIN Jin |
| (1.Nocommssioned Officer Academy of PAP,Hangzhou 311400,China;2.School of Earth Sciences,Zhejiang University,Hangzhou 310014,China) |
| Abstract: |
| With the continuous improvement of maritime strategic status,unmanned boat clusters have shown tremendous efficiency and application potential,among which the application of unmanned boat clusters in marine environments is the most promising.By taking the complex marine environment as the research background,the current research status of unmanned boats at home and abroad is introduced,and the characteristics of three-dimensional characterization,enemy dynamic analysis,and unmanned boat machine mobility constraints based on the complex marine environment are analyzed.Then,key technologies are discussed including three-dimensional modeling analysis of Robot Operating System Gazebo(ROSG) simulation,analysis of maneuverability constraints and threat areas of unmanned boats based on mathematical modeling,and trajectory planning of unmanned boat clusters based on transfer reinforcement learning.Finally,the development trend of trajectory planning of unmanned boat clusters is given in hope of providing direction for research on unmanned boat cluster trajectory planning. |
| Key words: marine environment unmanned boat cluster track planning reinforcement learning mathematical modeling |