Learning to Localize, Grasp, and Hand Over Unmodified Surgical Needles
Learning to Localize, Grasp, and Hand Over Unmodified Surgical Needles
复制标题
学习定位、抓握和移交未经改造的手术针
DOI：
10.1109/icra46639.2022.9812393
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Ken Goldberg
中科院分区：
文献类型：
--
作者：
Albert Wilcox;J. Kerr;Brijen Thananjeyan;Jeffrey Ichnowski;M. Hwang;Samuel Paradis;Danyal Fer;Ken Goldberg
机器人手术助理（RSA）通常用于由专家外科医生执行微创手术。然而，充满繁琐和重复性任务的长时间手术（如手术）可能会导致外科医生疲劳，从而促使手术自动化。由于薄反射针的视觉跟踪是极其具有挑战性的，先前的工作已经用非反射对比涂料修改了针。作为在不修改针的情况下自动化操作子任务的一步，我们提出了HOUSTON：未修改的、外科手术的、工具阻塞的针的移交，这是一个问题和算法，它使用学习的主动感测策略与立体相机来迭代地定位和对准针，使其成为另一个夹具的可见和可访问的姿势。为了补偿机器人定位和针感知误差，该算法然后执行使用多个摄像头的高精度抓取运动。使用达芬奇研究工具包（dVRK）进行的物理实验表明，在训练中使用的针头的成功率为96.7%，在训练中看不到的针头的成功率为75 - 92.9%。在顺序的重复测试中，HOUSTON在失败前平均成功执行32.4次重复测试。据我们所知，这项工作是第一个研究移交未经修改的手术针。参见https：/ /tinyurl。com/houston-surgery获取更多资料，包括有关离线数据集和模型架构的详细信息。
Robotic Surgical Assistants (RSAs) are commonly used to perform minimally invasive surgeries by expert surgeons. However, long procedures filled with tedious and repetitive tasks such as suturing can lead to surgeon fatigue, motivating the automation of suturing. As visual tracking of a thin reflective needle is extremely challenging, prior work has modified the needle with nonreflective contrasting paint. As a step towards automation of a suturing subtask without modifying the needle, we propose HOUSTON: Handover of Unmodified, Surgical, Tool-Obstructed Needles, a problem and algorithm that uses a learned active sensing policy with a stereo camera to iteratively localize and align the needle into a visible and accessible pose for the other gripper. To compensate for robot positioning and needle perception errors, the algorithm then executes a high-precision grasping motion that uses multiple cameras. Physical experiments with the da Vinci Research Kit (dVRK) suggest a success rate of 96.7% on needles used in training, and 75 - 92.9% on needles unseen in training. On sequential handovers, HOUSTON successfully executes 32.4 handovers on average before failure. To our knowledge, this work is the first to study handover of unmodified surgical needles. See https: / /tinyurl. com/houston-surgery for additional materials including details about offline datasets and model architectures.
RAVEN-II 手术机器人末端执行器位置的实时数据驱动精度估计器
DOI：
10.1109/icra40945.2020.9196915
发表时间：
2020
期刊：
IEEE International Conference on Robotics and Automation
影响因子：
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作者：
Peng, Haonan;Yang, Xingjian;Su, Yun-Hsuan;Hannaford, Blake
通讯作者：
Hannaford, Blake
协作缝合：一种强化学习方法，用于自动化手术机器人缝合中的交接任务
DOI：
10.1109/ro-man47096.2020.9223543
发表时间：
2020
期刊：
2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN
影响因子：
--
作者：
Varier, Vignesh Manoj;Rajamani, Dhruv Kool;Goldfarb, Nathaniel;Tavakkolmoghaddam, Farid;Munawar, Adnan;Fischer, Gregory S
通讯作者：
Fischer, Gregory S