Embedded Force Sensor for Soft Robots With Deep Transformation Calibration

IF 3.4 Q2 ENGINEERING, BIOMEDICAL IEEE transactions on medical robotics and bionics Pub Date : 2024-10-14 DOI:10.1109/TMRB.2024.3479878
Navid Masoumi;Andrés C. Ramos;Tannaz Torkaman;Liane S. Feldman;Jake Barralet;Javad Dargahi;Amir Hooshiar
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Abstract

A novel soft sensor calibration method is proposed for minimally invasive surgery, based on our developed gelatin-graphite sensor with high compliance and adaptability. This approach uses convolutional deep learning that accounts for a sensor’s non-linear behavior and reduces noise amplification. This technique offers a smaller minimum detectable force than other approaches and is particularly useful in sensitive surgical scenarios. The sensor’s performance is characterized by its fine resolution ( $\leq 1$ mN) and accurate force estimation, especially for forces below 400 mN of amplitude. The best calibration (Morse) scheme provides high performance, with a Mean Absolute Error of $\leq 7.9$ mN. This work was validated through comparison among other representative studies and offered a path toward future directions for optimizing and implementing soft robotic sensors in minimally invasive surgeries. The application of this sensor can revolutionize surgical procedures and capitalize on the benefits of soft robotics, potentially enhancing precision and reducing trauma in surgeries.
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具有深度变换校准功能的嵌入式软机器人力传感器
基于我们开发的具有高顺应性和适应性的明胶石墨传感器,为微创手术提出了一种新型软传感器校准方法。这种方法使用卷积深度学习,可考虑传感器的非线性行为并减少噪声放大。与其他方法相比,该技术的最小可探测力更小,尤其适用于敏感的手术场景。该传感器的性能特点是分辨率高(1 mN)和力估算准确,尤其是对于振幅低于 400 mN 的力。最佳校准(莫尔斯)方案提供了高性能,平均绝对误差为 7.9 mN。这项工作通过与其他代表性研究的比较得到了验证,并为微创手术中软性机器人传感器的优化和实施提供了未来发展方向。这种传感器的应用可以彻底改变外科手术程序,并充分利用软机器人技术的优势,有可能提高手术的精确度并减少创伤。
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Table of Contents IEEE Transactions on Medical Robotics and Bionics Society Information Guest Editorial Special section on the Hamlyn Symposium 2023—Immersive Tech: The Future of Medicine IEEE Transactions on Medical Robotics and Bionics Publication Information IEEE Transactions on Medical Robotics and Bionics Information for Authors
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