手术器械
校准
管(容器)
信号(编程语言)
刚度
弯曲
仪表(计算机编程)
侵入性外科
机器人
声学
工程类
模拟
机械工程
计算机科学
结构工程
物理
人工智能
外科
程序设计语言
操作系统
医学
量子力学
作者
Amir Hossein Hadi Hosseinabadi,Septimiu E. Salcudean
出处
期刊:Cornell University - arXiv
日期:2021-03-20
标识
DOI:10.48550/arxiv.2103.11116
摘要
This paper presents a novel multi-axis force-sensing approach in robotic minimally invasive surgery with no modification to the surgical instrument. Thus, it is adaptable to different surgical instruments. A novel 6-axis optical force sensor, with local signal conditioning and digital electronics, was mounted onto the proximal shaft of a da Vinci EndoWrist instrument. A new cannula design comprising an inner tube and an outer tube was proposed. The inner tube is attached to the cannula interface to the robot base through a compliant leaf spring with adjustable stiffness. It allows bending of the instrument shaft due to the tip forces. The outer tube mechanically filters out the body forces from affecting the instrument bending behavior. A mathematical model of the sensing principle was developed and used for model-based calibration. A data-driven calibration based on a shallow neural network architecture comprising a single 5-nodes hidden layer and a 5x1 output layer is discussed. Extensive testing was conducted to validate that the sensor can successfully measure the lateral forces and moments and the axial torque applied to the instruments distal end within the desired resolution, accuracy, and range requirements.
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