摘要
水下无人航行器(UUV)作为海洋勘探与军事任务的核心装备,其路径规划技术直接影响任务执行效率与安全性。本文阐述了路径规划算法的发展,首先将UUV路径规划算法进行分类,分为传统规划算法、智能规划算法和强化学习算法。其次分析了算法的基本原理,通过文献分析与对比的方法,讨论每种算法的优缺点并进行总结分析,同时给出相应的算法优化思路和例子。最后基于现有的发展趋势,对水下无人航行器路径规划未来的发展方向进行展望。
Underwater Unmanned Vehicles(UUVs),as core equipment for marine exploration and military missions,have their path planning technology directly impacting the efficiency and safety of mission execution.This paper elaborates on the development of path planning algorithms,first classifying UUV path planning algorithms into traditional planning algorithms,intelligent planning algorithms,and reinforcement learning algorithms.Secondly,it analyzes the basic principles of the algorithms,discussing the advantages and disadvantages of each algorithm through literature analysis and comparison,and provides a summary analysis,as well as optimization ideas and examples for the corresponding algorithms.Finally,based on the current development trends,it looks forward to the future development directions of UUV path planning.
作者
常满
王征
屈新雨
李厚朴
Chang Man;Wang Zheng;Qu Xinyu;Li Houpu(School of Electrical Engineering,Wuhan 430033,China)
出处
《船电技术》
2025年第12期90-95,共6页
Marine Electric & Electronic Engineering
关键词
水下无人航行器
路径规划
传统规划算法
智能规划算法
强化学习
underwater unmanned vehicle
path planning
traditional planning algorithm
intelligent planning algorithm
reinforcement learning
