触觉技术
机制(生物学)
计算机科学
机器人
手术机器人
光学(聚焦)
工作(物理)
模拟
肌腱
过程(计算)
反馈控制
控制(管理)
控制理论(社会学)
控制工程
人工智能
外科
医学
工程类
机械工程
物理
光学
操作系统
量子力学
作者
Fuhao Wang,Ye Wang,Qiqi Pan,Jingjing Luo,Hongbo Wang,Xiaoyang Kang,Xueze Zhang
摘要
ABSTRACT Background Robot‐assisted microsurgery (RAMS) is gradually becoming the preferred method for some delicate surgical procedures. However, the lack of haptic feedback reduces the safety of the surgery. Surgeons are unable to feel the grasping force between surgical instruments and the patient's tissues, which can easily lead to grasping failure or tissue damage. Methods This paper proposes a tendon‐driven grasping force feedback mechanism, consisting of a follower hand and a leader hand, to address the lack of grasping force feedback in flexible surgical robots. Considering the friction in the tendon transmission process, a grasping force estimation model is established for the follower hand. The admittance control model is designed for force/position control of the leader hand. Results Through experimental validation, it has been confirmed that the grasping force sensing range of the follower hand is 0.5–5 N, with a sensing accuracy of 0.3 N. The leader hand is capable of providing feedback forces in the range of 0–5 N, with a static force accuracy of 0.1 N. Conclusions The designed mechanism and control strategy can provide the grasping force feedback function. Future work will focus on improving force feedback performance. Trial Registration This research has no clinical trials.
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