Recent progress, challenges and future prospects of applied deep reinforcement learning : A practical perspective in path planning-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Recent progress, challenges and future prospects of applied deep reinforcement learning : A practical perspective in path planning

Published:2024-12 Issue: Volume:608 Page:128423
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zhang Ye,Zhao Wang^ORCID,Wang Jingyu,Yuan Yuan

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference159 articles.

1. Path planning techniques for mobile robots: Review and prospect;Liu;Expert Syst. Appl.,2023

2. Routing optimization of cross-regional collaborative emergency rescue considering efficiency and fairness;Zhu;Control Decis.,2021

3. Programming model and optimization algorithm for the mixed fleet vehicle routing problem in urban logistics distribution;Liu;Control Decis.,2023

4. Deep reinforcement learning for autonomous driving: A survey;Kiran;IEEE Trans. Intell. Transp. Syst.,2022

5. FNPG-NH: A reinforcement learning framework for flexible needle path generation with nonholonomic constraints;Shah;IEEE Robot. Autom. Lett.,2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP