中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 多模态人工智能系统全国重点实验室
A Survey on Reinforcement Learning Methods in Bionic Underwater Robots

文献类型：期刊论文

作者Tong, Ru1,3; Feng, Yukai1,3; Wang, Jian1,3; Wu, Zhengxing1,3; Tan, Min1,3; Yu, Junzhi1,2
刊名BIOMIMETICS
出版日期2023-06-01
卷号8期号:2页码:29
关键词bionic underwater robot reinforcement learning robotic fish intelligent control
DOI10.3390/biomimetics8020168
通讯作者Yu, Junzhi(junzhi.yu@ia.ac.cn)
英文摘要Bionic robots possess inherent advantages for underwater operations, and research on motion control and intelligent decision making has expanded their application scope. In recent years, the application of reinforcement learning algorithms in the field of bionic underwater robots has gained considerable attention, and continues to grow. In this paper, we present a comprehensive survey of the accomplishments of reinforcement learning algorithms in the field of bionic underwater robots. Firstly, we classify existing reinforcement learning methods and introduce control tasks and decision making tasks based on the composition of bionic underwater robots. We further discuss the advantages and challenges of reinforcement learning for bionic robots in underwater environments. Secondly, we review the establishment of existing reinforcement learning algorithms for bionic underwater robots from different task perspectives. Thirdly, we explore the existing training and deployment solutions of reinforcement learning algorithms for bionic underwater robots, focusing on the challenges posed by complex underwater environments and underactuated bionic robots. Finally, the limitations and future development directions of reinforcement learning in the field of bionic underwater robots are discussed. This survey provides a foundation for exploring reinforcement learning control and decision making methods for bionic underwater robots, and provides insights for future research.
WOS关键词FISH ; GAME ; GO
资助项目National Natural Science Foundation of China[62233001] ; National Natural Science Foundation of China[T2121002] ; National Natural Science Foundation of China[62073196] ; Ministry of Education for Equipment Pre-Research[8091B022134] ; Postdoctoral Innovative Talent Support Program[BX20220001]
WOS研究方向Engineering ; Materials Science
语种英语
出版者MDPI
WOS记录号WOS:001017078100001
资助机构National Natural Science Foundation of China ; Ministry of Education for Equipment Pre-Research ; Postdoctoral Innovative Talent Support Program
源URL[http://ir.ia.ac.cn/handle/173211/53525]  
专题多模态人工智能系统全国重点实验室
通讯作者Yu, Junzhi
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Peking Univ, Coll Engn, Dept Adv Mfg & Robot, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Tong, Ru,Feng, Yukai,Wang, Jian,et al. A Survey on Reinforcement Learning Methods in Bionic Underwater Robots[J]. BIOMIMETICS,2023,8(2):29.
APA Tong, Ru,Feng, Yukai,Wang, Jian,Wu, Zhengxing,Tan, Min,&Yu, Junzhi.(2023).A Survey on Reinforcement Learning Methods in Bionic Underwater Robots.BIOMIMETICS,8(2),29.
MLA Tong, Ru,et al."A Survey on Reinforcement Learning Methods in Bionic Underwater Robots".BIOMIMETICS 8.2(2023):29.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。