机器人2026，Vol.48Issue(1)：196-216,21.DOI:10.13973/j.cnki.robot.240176
基于深度强化学习的路径规划算法综述
A Survey of Path Planning Algorithms Based on Deep Reinforcement Learning
摘要
Abstract
Traditional path planning methods have obvious limitations in complex and changing environments.Firstly,the shortcomings of these traditional methods are discussed,and then deep reinforcement learning as a new solution is introduced.The principles,advantages and disadvantages of 3 deep reinforcement learning methods including value function based,strategy based and hybrid value based strategies,as well as their representative research results in various application fields in recent years are summarized.The representative algorithms are tested on a unified platform,and actual comparative analysis is performed.Finally,the challenges and research prospects of path planning techniques based on deep reinforcement learning are summarized.关键词
路径规划/深度学习/强化学习/深度强化学习Key words
path planning/deep learning/reinforcement learning/deep reinforcement learning引用本文复制引用
黄鑫,张志佳,孙平,唐延东,刘云鹏..基于深度强化学习的路径规划算法综述[J].机器人,2026,48(1):196-216,21.基金项目
辽宁省人工智能领域应用基础研究计划(2023JH26/10300006) （2023JH26/10300006）
辽宁省应用基础研究计划(2023JH2/101300237). （2023JH2/101300237）
