双手机器人眼睛操纵使用自适应性结核力控制:朝着安全的视网膜静脉注射
Mojtaba Esfandiari1, Ji Woong Kim1, Peiyao Zhang1
1Department of Mechanical Engineering and also the Laboratory for Computational Sensing and Robotics at the Johns Hopkins University, Baltimore, MD, 21218, USA.
IEEE transactions on medical robotics and bionics
|January 26, 2026
概括
机器人辅助视网膜静脉管使用一种新的双手自适应合作控制框架. 这种系统最大限度地降低了刀具-骨架力,在微妙的眼睛手术中提高了患者的安全性.
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
- 手术技术 手术技术
背景情况:
- 视网膜静脉通道 (RVC) 是一种复杂的微手术,需要精确的双手仪器控制.
- 由于视网膜血管的大小小,手在自由手RVC中构成重大挑战.
- 机器人辅助手术为RVC提供了更高的精度和减轻震.
研究的目的:
- 开发和验证用于机器人辅助视网膜手术的新型双手自适应合作 (BMAC) 控制框架.
- 通过在双手机器人操纵过程中最大限度地减少膜相互作用力来确保患者的安全.
- 为了克服传统的基于运动学的控制和机器人注册的局限性.
主要方法:
- 实施了BMAC控制框架,具有独立的机器人控制.
- 为每个机器人使用混合适应性位置力控制算法.
- 采用基于纤维布拉格格的强力传感手术仪器,用于精确的强力监测.
- 通过一项试点研究与五名用户在眼睛幻影上验证了该系统.
主要成果:
- 该BMAC框架成功地将工具-sclera交互力降到最低.
- 粘膜力保持在安全的值内,防止过度伸展.
- 该系统在对眼睛幻影进行的血管跟踪实验中证明了它的有效性.
- 试点研究参与者在手术显微镜可视化下成功执行了任务.
结论:
- 开发的BMAC控制框架提高了机器人辅助视网膜静脉管的安全性.
- 这种方法有效地管理了无需传统RCM约束或注册的关相互作用力.
- 该系统有望在具有挑战性的眼科微手术中提高精度和安全性.
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