柔性手术机器人抓取力反馈机制的设计与研究

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-08-09 DOI:10.1002/rcs.2667

Fuhao Wang, Ye Wang, Qiqi Pan, Jingjing Luo, Hongbo Wang, Xiaoyang Kang, Xueze Zhang

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引用次数: 0

摘要

背景：机器人辅助显微外科手术（RAMS）逐渐成为一些精细外科手术的首选方法。然而，触觉反馈的缺乏降低了手术的安全性。外科医生无法感受到手术器械与患者组织之间的抓取力，这很容易导致抓取失败或组织损伤：本文针对柔性手术机器人缺乏抓取力反馈的问题，提出了一种由跟随手和领导手组成的肌腱驱动抓取力反馈机制。考虑到肌腱传输过程中的摩擦，建立了从动手抓取力估计模型。结果：通过实验验证，确认从动手的抓取力感应范围为 0.5-5 N，感应精度为 0.3 N：结论：所设计的机构和控制策略能够提供抓取力反馈功能。今后的工作重点是提高力反馈性能：本研究没有临床试验。

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Design and Research of the Grasping Force Feedback Mechanism of Flexible Surgical Robots

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.