Sensorless force estimation using a neuro-vision-based approach for robotic-assisted surgery

Angelica I. Avilés, Samar M. Alsaleh, P. Sobrevilla, A. Casals
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引用次数: 25

Abstract

This paper addresses the issue of lack of force feedback in robotic-assisted minimally invasive surgeries. Force is an important measure for surgeons in order to prevent intra-operative complications and tissue damage. Thus, an innovative neuro-vision based force estimation approach is proposed. Tissue surface displacement is first measured via minimization of an energy functional. A neuro approach is then used to establish a geometric-visual relation and estimate the applied force. The proposed approach eliminates the need of add-on sensors, carrying out biocompatibility studies and is applicable to tissues of any shape. Moreover, we provided an improvement from 15.14% to 56.16% over other approaches which demonstrate the potential of our proposal.
基于神经视觉的机器人辅助手术无传感器力估计方法
本文解决了机器人辅助微创手术中缺乏力反馈的问题。用力是外科医生预防术中并发症和组织损伤的重要措施。因此,提出了一种新颖的基于神经视觉的力估计方法。组织表面位移首先通过能量函数的最小化来测量。然后使用神经方法建立几何视觉关系并估计施加的力。提出的方法消除了附加传感器的需要,进行生物相容性研究,适用于任何形状的组织。此外,与其他方法相比,我们提供了从15.14%到56.16%的改进,这表明了我们建议的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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