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

doi:10.1016/j.eswa.2023.120134

CORC > 自动化研究所 > 中国科学院自动化研究所 > 多模态人工智能系统全国重点实验室

	Learning surgical skills under the RCM constraint from demonstrations in robot-assisted minimally invasive surgery
	Bian, Gui-Bin 5; Chen, Zhang 4,5; Li, Zhen 3,5; Wei, Bing-Ting 5; Liu, Wei-Peng 4; da Silva, Daniel Santos 1; Wu, Wan-Qing 2; de Albuquerque, Victor Hugo C.1
刊名	EXPERT SYSTEMS WITH APPLICATIONS
	2023-09-01
卷号	225 页码:9
关键词	Surgical robotics Learning from demonstrations Robot-assisted surgery Minimally invasive surgery Remote center of motion
ISSN号	0957-4174
DOI	10.1016/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.
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关键词	TASK
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
内容类型	期刊论文
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.Univ Fed Ceara, Dept Teleinformat Engn, BR-60455970 Fortaleza, Ceara, Brazil 2.Sun Yat Sen Univ, Sch Biomed Engn, Guangzhou 510275, Peoples R China 3.Tongji Univ, Sch Elect & Informat Engn, Shanghai 201804, Peoples R China 4.Hebei Univ Technol, Sch Artificial Intelligence & Data Sci, Tianjin 300131, Peoples R China 5.Chinese Acad Sci, Inst Automat, Beijing 100190, 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.