Knowledge Commons of Institute of Automation,CAS
Target-Following Control of a Biomimetic Autonomous System Based on Predictive Reinforcement Learning | |
Wang, Yu1![]() ![]() ![]() | |
发表期刊 | BIOMIMETICS
![]() |
2024 | |
卷号 | 9期号:1页码:19 |
摘要 | Biological fish often swim in a schooling manner, the mechanism of which comes from the fact that these schooling movements can improve the fishes' hydrodynamic efficiency. Inspired by this phenomenon, a target-following control framework for a biomimetic autonomous system is proposed in this paper. Firstly, a following motion model is established based on the mechanism of fish schooling swimming, in which the follower robotic fish keeps a certain distance and orientation from the leader robotic fish. Second, by incorporating a predictive concept into reinforcement learning, a predictive deep deterministic policy gradient-following controller is provided with the normalized state space, action space, reward, and prediction design. It can avoid overshoot to a certain extent. A nonlinear model predictive controller is designed and can be selected for the follower robotic fish, together with the predictive reinforcement learning. Finally, extensive simulations are conducted, including the fix point and dynamic target following for single robotic fish, as well as cooperative following with the leader robotic fish. The obtained results indicate the effectiveness of the proposed methods, providing a valuable sight for the cooperative control of underwater robots to explore the ocean. |
关键词 | biomimetic motion biomimetic autonomous system target following deep reinforcement learning predictive control |
DOI | 10.3390/biomimetics9010033 |
关键词[WOS] | TRACKING |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China |
项目资助者 | National Natural Science Foundation of China |
WOS研究方向 | Engineering ; Materials Science |
WOS类目 | Engineering, Multidisciplinary ; Materials Science, Biomaterials |
WOS记录号 | WOS:001149504000001 |
出版者 | MDPI |
七大方向——子方向分类 | 智能机器人 |
国重实验室规划方向分类 | 水下仿生机器人 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/55459 |
专题 | 复杂系统认知与决策实验室_水下机器人 |
通讯作者 | Yu, Junzhi |
作者单位 | 1.Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China 2.Chinese Acad Sci, Inst Automat, Lab Cognit & Decis Intelligence Complex Syst, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 4.Peking Univ, Coll Engn, Dept Adv Mfg & Robot, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Wang, Yu,Wang, Jian,Kang, Song,et al. Target-Following Control of a Biomimetic Autonomous System Based on Predictive Reinforcement Learning[J]. BIOMIMETICS,2024,9(1):19. |
APA | Wang, Yu,Wang, Jian,Kang, Song,&Yu, Junzhi.(2024).Target-Following Control of a Biomimetic Autonomous System Based on Predictive Reinforcement Learning.BIOMIMETICS,9(1),19. |
MLA | Wang, Yu,et al."Target-Following Control of a Biomimetic Autonomous System Based on Predictive Reinforcement Learning".BIOMIMETICS 9.1(2024):19. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
biomimetics-09-00033(1553KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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。
修改评论