双手操纵稳手眼睛机器人与自适应性Sclera力控制:合作与远程操作策略
Mojtaba Esfandiari1, Peter Gehlbach2, Russell H Taylor3
1Mojtaba Esfandiari and Iulian Iordachita are with the Department of Mechanical Engineering and also the Laboratory for Computational Sensing and Robotics at the Johns Hopkins University, Baltimore, MD, 21218, USA.
概括
这项研究引入了一个新的机器人控制框架,用于更安全的眼睛手术. 它最大限度地减少了视网膜静脉通风过程中的破坏力,提高了外科医生的精度和安全性.
科学领域:
- 眼科医生 眼科 眼科
- 机器人技术 机器人技术 机器人技术
- 生物医学工程 生物医学工程
背景情况:
- 视网膜静脉管 (RVC) 视网膜静脉封闭 (RVO) 具有挑战性,因为外科医生手.
- 现有的机器人系统,如稳定手眼机器人 (SHER),可以减少震动,但缺乏安全的力量控制.
- 需要远程操作框架来增强手术功能,如触觉反.
研究的目的:
- 为机器人辅助视网膜微手术提供一种新的无需注册的双手自适应远程操作 (BMAT) 控制框架.
- 整合一个自适应力控制 (AFC) 算法,以最大限度地减少工具-sclera相互作用力.
- 使用SHER 2.0和SHER 2.1系统评估BMAT框架的安全性和有效性.
主要方法:
- 开发并实施了一种无需注册的双手自适应远程操作 (BMAT) 控制框架.
- 与SHER 2.0和SHER 2.1机器人系统集成了一个自适应力控制 (AFC) 算法.
- 使用基于纤维布拉格格 (FBG) 的力感应工具来测量关力.
主要成果:
- 在安全的范围内,BMAT框架成功地将工具-sclera相互作用力降到最低.
- 实验结果显示,BMAT框架能够实现安全的双手远程操作,而不会过度拉伸眼睛.
- 在船舶跟踪实验中,对双手自适应合作 (BMAC) 框架进行了性能评估.
结论:
- 拟议的BMAT控制框架提高了机器人辅助视网膜微手术的安全性和精度.
- 这种新的方法通过结合自适应力控制来解决以前的合作控制模式的局限性.
- BMAT框架为微妙的眼内外科手术程序提供了一个有希望的进步.
相关概念视频
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