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Learning surgical skills under the RCM constraint from demonstrations in robot-assisted minimally invasive surgery

文献类型：期刊论文

作者Bian, Gui-Bin2; Chen, Zhang2,5; Li, Zhen1,2; Wei, Bing-Ting2; Liu, Wei-Peng5; da Silva, Daniel Santos3; Wu, Wan-Qing4; de Albuquerque, Victor Hugo C.3
刊名EXPERT SYSTEMS WITH APPLICATIONS
出版日期2023-09-01
卷号225页码:9
ISSN号0957-4174
关键词Surgical robotics Learning from demonstrations Robot-assisted surgery Minimally invasive surgery Remote center of motion
DOI10.1016/j.eswa.2023.120134
通讯作者Liu, Wei-Peng(liuweipeng@hebut.edu.cn)
英文摘要Learning surgical skills from trained surgeons can increase the level of autonomy of surgical robots and provide assistance for surgeons in an appropriate way during surgery. However, the remote center of motion (RCM) constraint is a tricky problem while most other works only consider the task performed in the lesion area. This study aims to transfer the minimally invasive surgical skills demonstrated by surgeons to the surgical robot while satisfying the RCM constraint. In this paper, the implicit constraints of manipulation skills are modeled into a probabilistic model to maintain the variability and flexibility of the surgeon's operations. A novel method is proposed to address the inconsistency between the RCM constraint space and surgical task space. The generalization of the learned skills under the RCM constraint has also been improved. We validated the proposed method in a physical experiment with a tracking task under the RCM constraint. An original measurement method based on shape similarity is proposed to compute the tracking errors of trajectories that have nonhomogeneous temporal and spatial distortions. The root means square error of the trajectory was 1.8 mm, which exceeded the average for operator demonstrations.
WOS关键词TASK
资助项目National Natural Science Foundation of China[62027813] ; National Natural Science Foundation of China[U20A20196] ; National Natural Science Foundation of China[62176266] ; CAS Interdisciplinary Innovation Team[JCTD-2019-07] ; Beijing Science Fund for Distinguished Young Scholars[JQ21016] ; Natural Science Foundation of Hebei Province,China[F2020202009] ; CNPq[305517/2022-8]
WOS研究方向Computer Science ; Engineering ; Operations Research & Management Science
语种英语
出版者PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号WOS:001033088900001
资助机构National Natural Science Foundation of China ; CAS Interdisciplinary Innovation Team ; Beijing Science Fund for Distinguished Young Scholars ; Natural Science Foundation of Hebei Province,China ; CNPq
源URL[http://ir.ia.ac.cn/handle/173211/53738]  
专题多模态人工智能系统全国重点实验室
通讯作者Liu, Wei-Peng
作者单位1.Tongji Univ, Sch Elect & Informat Engn, Shanghai 201804, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.Univ Fed Ceara, Dept Teleinformat Engn, BR-60455970 Fortaleza, Ceara, Brazil
4.Sun Yat Sen Univ, Sch Biomed Engn, Guangzhou 510275, Peoples R China
5.Hebei Univ Technol, Sch Artificial Intelligence & Data Sci, Tianjin 300131, Peoples R China
推荐引用方式
GB/T 7714		 Bian, Gui-Bin,Chen, Zhang,Li, Zhen,et al. Learning surgical skills under the RCM constraint from demonstrations in robot-assisted minimally invasive surgery[J]. EXPERT SYSTEMS WITH APPLICATIONS,2023,225:9.
APA Bian, Gui-Bin.,Chen, Zhang.,Li, Zhen.,Wei, Bing-Ting.,Liu, Wei-Peng.,...&de Albuquerque, Victor Hugo C..(2023).Learning surgical skills under the RCM constraint from demonstrations in robot-assisted minimally invasive surgery.EXPERT SYSTEMS WITH APPLICATIONS,225,9.
MLA Bian, Gui-Bin,et al."Learning surgical skills under the RCM constraint from demonstrations in robot-assisted minimally invasive surgery".EXPERT SYSTEMS WITH APPLICATIONS 225(2023):9.

入库方式： OAI收割

来源：自动化研究所

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