Autonomous path planning for robot-assisted pelvic fracture closed reduction with collision avoidance

doi:10.1002/rcs.2483

	Autonomous path planning for robot-assisted pelvic fracture closed reduction with collision avoidance
	Pan, Mingzhang 1; Chen, Yuan 1; Li, Zhen2,3 ; Liao, Xiaolan 1; Deng, Yawen 1; Bian, Gui-Bin3
发表期刊	INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY
ISSN	1478-5951
	2022-11-30
页码	12
通讯作者	Bian, Gui-Bin(guibin.bian@ia.ac.cn)
摘要	BackgroundRobot-assisted pelvic fracture closed reduction (RPFCR) positively contributes to patient treatment. However, the current path planning suffers from incomplete obstacle avoidance and long paths. MethodA collision detection method is proposed for applications in the pelvic environment to improve the safety of RPFCR surgery. Meanwhile, a defined orientation planning strategy (OPS) and linear sampling search (LSS) are coupled into the A* algorithm to optimise the reduction path. Subsequently, pelvic in vitro experimental platform is built to verify the augmented Aalgorithm's feasibility. ResultsThe augmented A algorithm planned the shortest path for the same fracture model, and the paths planned by the A* algorithm and experience-based increased by 56.12% and 89.02%, respectively. ConclusionsThe augmented A* algorithm effectively improves surgical safety and shortens the path length, which can be adopted as an effective model for developing RPFCR path planning.
关键词	A* algorithm collision detection path planning pelvic closed reduction
DOI	10.1002/rcs.2483
关键词[WOS]	SYSTEM
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China ; National Natural Science Foundation of China ; CAS Interdisciplinary Innovation Team ; Beijing Science Fund for Distinguished Young Scholars ; [2020YFB1313800] ; [62027813] ; [U20A20196] ; [62176266] ; [JCTD-2019-07] ; [JQ21016]
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China ; CAS Interdisciplinary Innovation Team ; Beijing Science Fund for Distinguished Young Scholars
WOS研究方向	Surgery
WOS类目	Surgery
WOS记录号	WOS:000892360000001
出版者	WILEY
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/50804
专题	复杂系统认知与决策实验室_先进机器人
通讯作者	Bian, Gui-Bin
作者单位	1.Guangxi Univ, Sch Mech Engn, Nanning, Guangxi, Peoples R China 2.Tongji Univ, Sch Elect & Informat Engn, Shanghai, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing, 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	Pan, Mingzhang,Chen, Yuan,Li, Zhen,et al. Autonomous path planning for robot-assisted pelvic fracture closed reduction with collision avoidance[J]. INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY,2022:12.
APA	Pan, Mingzhang,Chen, Yuan,Li, Zhen,Liao, Xiaolan,Deng, Yawen,&Bian, Gui-Bin.(2022).Autonomous path planning for robot-assisted pelvic fracture closed reduction with collision avoidance.INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY,12.
MLA	Pan, Mingzhang,et al."Autonomous path planning for robot-assisted pelvic fracture closed reduction with collision avoidance".INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY (2022):12.