Dynamic Modeling of Cable Driven Elongated Surgical Instruments for Sensorless Grip Force Estimation.
Dynamic Modeling of Cable Driven Elongated Surgical Instruments for Sensorless Grip Force Estimation.
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DOI：
10.1109/icra.2016.7487605
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发表时间：
2016-05
期刊：
影响因子：
--
通讯作者：
Hannaford B
中科院分区：
文献类型：
--
作者：
Li Y;Miyasaka M;Haghighipanah M;Cheng L;Hannaford B
触觉反馈在外科手术中起着关键作用，但它仍然是机器人微创外科手术中缺少的组件。本文提出了一种基于动态模型的无传感器握力估计方法，以解决常用的细长电缆驱动的手术器械的触觉感知问题。电缆和电缆滑轮的性能进行了研究，动态建模;夹持力，沿着与驱动电机和夹爪爪的位置和速度联合估计与无迹卡尔曼滤波器，只有电机编码器读数和电机输出扭矩被假定为已知的。边界滤波器用于补偿模型的不准确性，并提高方法的鲁棒性。所提出的方法进行了验证的10毫米夹持器，这是由乌鸦II手术机器人驱动。夹具配备了一维力传感器，作为地面实况数据。实验结果表明，所提出的方法提供了足够好的抓地力估计，而只有电机编码器和电机转矩作为观察。
Haptic feedback plays a key role in surgeries, but it is still a missing component in robotic Minimally Invasive Surgeries. This paper proposes a dynamic model-based sensorless grip force estimation method to address the haptic perception problem for commonly used elongated cable-driven surgical instruments. Cable and cable-pulley properties are studied for dynamic modeling; grip forces, along with driven motor and gripper jaw positions and velocities are jointly estimated with Unscented Kalman Filter and only motor encoder readings and motor output torques are assumed to be known. A bounding filter is used to compensate for model inaccuracy and to improve method robustness. The proposed method was validated on a 10mm gripper which is driven by a Raven-II surgical robot. The gripper was equipped with 1-dimensional force sensors which served as ground truth data. The experimental results showed that the proposed method provides sufficiently good grip force estimation, while only motor encoder and the motor torques are used as observations.
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