文献类型： 会议论文
第一作者： Tamás Haidegger
作者： Tamás Haidegger 1 ; Tamás D. Nagy 2 ;
作者机构： 1.Antal Bejczy Center for Intelligent Robotics, EKIK, óbuda University, Bécsi út 96/B, Budapest, Hungary|Austrian Center for Medical Innovation and Technology (ACMIT), Viktor-Kaplan-Stra?e 2, Wiener Neustadt, Austria
2.Antal Bejczy Center for Intelligent Robotics, EKIK, óbuda University, Bécsi út 96/B, Budapest, Hungary|Doctoral School of Applied Informatics and Applied Mathematics, óbuda University|Biomatics Institute, John von Neumann Faculty of Informatics, óbuda University
关键词： Training;Automation;Minimally invasive surgery;Medical services;Benchmark testing;Cameras;Complexity theory
会议名称： IEEE Jubilee International Conference on Computational Cybernetics and Cyber-Medical Systems
主办单位：
页码： 69-76
摘要： The appearance and global spread of Robot-Assisted Minimally Invasive Surgery (RAMIS) induced a revolution in healthcare during the last few decades. Many believe that the next step in the advancement of surgery will be subtask-level automation. Currently, a number of research groups are working on the automation of surgical subtasks, and in the last few years, the automation of simple surgical training exercises received more and more attention. At present, the most intensively researched of those training exercises is the peg transfer, probably due to its simplicity, enabling to elaborate the basic principles and best algorithms for automation. This paper presents an overview of the current state of the research in this particular area, emphasizing benchmarks and different variations of the peg transfer training exercise. An example implementation of autonomous peg transfer on the research-enhanced da Vinci Surgical System, the da Vinci Research Kit (DVRK), utilizing RGB-D camera stream, is also shown. Finally, advanced variations on the peg transfer training exercise, suitable as future research directions are proposed, gradually increasing challenge in the process of automation.
分类号： tp3-53
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