Knowledge Commons of Institute of Automation,CAS
Autonomous path planning for robot-assisted pelvic fracture closed reduction with collision avoidance | |
Pan, Mingzhang1; Chen, Yuan1; Li, Zhen2,3; Liao, Xiaolan1; Deng, Yawen1; 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 A*algorithm'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 | |
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. |
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