Knowledge Commons of Institute of Automation,CAS
Discrete soft actor-critic with auto-encoder on vascular robotic system | |
Li, Hao1,2; Zhou, Xiao-Hu1,2![]() ![]() ![]() ![]() ![]() ![]() | |
发表期刊 | ROBOTICA
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ISSN | 0263-5747 |
2022-11-17 | |
页码 | 12 |
摘要 | Instrument delivery is critical part in vascular intervention surgery. Due to the soft-body structure of instruments, the relationship between manipulation commands and instrument motion is non-linear, making instrument delivery challenging and time-consuming. Reinforcement learning has the potential to learn manipulation skills and automate instrument delivery with enhanced success rates and reduced workload of physicians. However, due to the sample inefficiency when using high-dimensional images, existing reinforcement learning algorithms are limited on realistic vascular robotic systems. To alleviate this problem, this paper proposes discrete soft actor-critic with auto-encoder (DSAC-AE) that augments SAC-discrete with an auxiliary reconstruction task. The algorithm is applied with distributed sample collection and parameter update in a robot-assisted preclinical environment. Experimental results indicate that guidewire delivery can be automatically implemented after 50k sampling steps in less than 15 h, demonstrating the proposed algorithm has the great potential to learn manipulation skill for vascular robotic systems. |
关键词 | surgical robots vascular robotic system automation reinforcement learning deep neural network |
DOI | 10.1017/S0263574722001527 |
关键词[WOS] | INTERVENTIONAL CARDIOLOGISTS ; STAFF ; RISK |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[62003343] ; National Natural Science Foundation of China[62222316] ; National Natural Science Foundation of China[U1913601] ; National Natural Science Foundation of China[62073325] ; National Natural Science Foundation of China[61720106012] ; National Natural Science Foundation of China[U20A20224] ; National Natural Science Foundation of China[U1913210] ; Beijing Natural Science Foundation[M22008] ; Youth Innovation Promotion Association of ChineseAcademy of Sciences (CAS)[2020140] ; Strategic Priority Research Program of CAS[XDB32040000] |
项目资助者 | National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Youth Innovation Promotion Association of ChineseAcademy of Sciences (CAS) ; Strategic Priority Research Program of CAS |
WOS研究方向 | Robotics |
WOS类目 | Robotics |
WOS记录号 | WOS:000889895900001 |
出版者 | CAMBRIDGE UNIV PRESS |
七大方向——子方向分类 | 机器人感知与决策 |
国重实验室规划方向分类 | 认知决策知识体系 |
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/173211/50798 |
专题 | 复杂系统认知与决策实验室_先进机器人 |
通讯作者 | Zhou, Xiao-Hu; Xie, Xiao-Liang |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 3.China Univ Min & Technol, Sch Mech Elect & Informat Engn, Beijing, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
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 | Li, Hao,Zhou, Xiao-Hu,Xie, Xiao-Liang,et al. Discrete soft actor-critic with auto-encoder on vascular robotic system[J]. ROBOTICA,2022:12. |
APA | Li, Hao.,Zhou, Xiao-Hu.,Xie, Xiao-Liang.,Liu, Shi-Qi.,Gui, Mei-Jiang.,...&Hou, Zeng-Guang.(2022).Discrete soft actor-critic with auto-encoder on vascular robotic system.ROBOTICA,12. |
MLA | Li, Hao,et al."Discrete soft actor-critic with auto-encoder on vascular robotic system".ROBOTICA (2022):12. |
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