基于图像的微尺度连续导丝机器人力定位和估算

IF 3.4 Q2 ENGINEERING, BIOMEDICAL IEEE transactions on medical robotics and bionics Pub Date : 2024-01-04 DOI:10.1109/TMRB.2024.3349598
Timothy A. Brumfiel;Ronghuai Qi;Sharan Ravigopal;Jaydev P. Desai
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引用次数: 0

摘要

许多血管内手术都需要先放置一根细长的导丝。这些导丝的转向面临着远端控制方面的挑战,同时还可能损伤血管壁,甚至造成致命的穿孔。为此,利用机器人导丝可以提高转向能力,并通过内在力传感实现力反馈。实现力传感面临着各种挑战,如在连续结构中离散放置传感器,以及给定挠度下的非唯一力分布。在这项工作中,我们利用图像反馈和 Cosserat 杆模型来估计和定位微尺度肌腱驱动导丝机器人身体上的力。这包括对摩擦和滞后的额外建模,而摩擦和滞后通常在力传感中被忽略。该模型在重力加载下对各种缺口镍钛诺管进行了测试,形状预测的平均 RMSE 为 0.46 毫米。与未补偿模型(RMSE ${=}$ 1.62 mm)相比,利用摩擦和滞后模型对大约 180° 弯曲进行形状预测时,RMSE 为 1.22 mm。所介绍的方法能够定位力,平均误差为 4.79 mm(长度的 5.15%),而力大小的估计平均误差为 13.03 mN。
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Image-Based Force Localization and Estimation of a Micro-Scale Continuum Guidewire Robot
Many intravascular procedures are prefaced by the placement of a slender wire called a guidewire. Steering these guidewires is met with challenges in controlling the distal end along with the possibility of damaging vessel walls, or even perforation, which can be fatal. To this end, utilizing robotic guidewires can improve steerability and enable force feedback through intrinsic force sensing. Enabling force sensing contains challenges such as discrete sensor placements in continuous structures and non-unique force distributions for a given deflection. In this work, we utilize image feedback and a Cosserat rod model to estimate and localize forces along the body of a micro-scale tendon-driven guidewire robot. This includes additional modeling of friction and hysteresis that is often neglected for force sensing. The model is tested on a variety of notched nitinol tubes under gravity loading with the shape predictions having an average RMSE of 0.46 mm. Utilization of friction and hysteresis models provide shape predictions with an RMSE of 1.22 mm compared to an uncompensated model (RMSE ${=}$ 1.62 mm) for approximately 180° bends. The methods presented are able to localize forces with an average error of 4.79 mm (5.15% of the length) while force magnitudes are estimated with an average error of 13.03 mN.
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Table of Contents IEEE Transactions on Medical Robotics and Bionics Publication Information Guest Editorial Joining Efforts Moving Faster in Surgical Robotics IEEE Transactions on Medical Robotics and Bionics Society Information IEEE Transactions on Medical Robotics and Bionics Information for Authors
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