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基于术中 3D 图像反馈的机器人辅助微创胸腔手术中的动态虚拟夹具生成。

Dynamic Virtual Fixture Generation Based on Intra-Operative 3D Image Feedback in Robot-Assisted Minimally Invasive Thoracic Surgery.

机构信息

ZJU-UIUC Institute, International Campus, Zhejiang University, Haining 314400, China.

School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.

出版信息

Sensors (Basel). 2024 Jan 12;24(2):492. doi: 10.3390/s24020492.

Abstract

This paper proposes a method for generating dynamic virtual fixtures with real-time 3D image feedback to facilitate human-robot collaboration in medical robotics. Seamless shared control in a dynamic environment, like that of a surgical field, remains challenging despite extensive research on collaborative control and planning. To address this problem, our method dynamically creates virtual fixtures to guide the manipulation of a trocar-placing robot arm using the force field generated by point cloud data from an RGB-D camera. Additionally, the "view scope" concept selectively determines the region for computational points, thereby reducing computational load. In a phantom experiment for robot-assisted port incision in minimally invasive thoracic surgery, our method demonstrates substantially improved accuracy for port placement, reducing error and completion time by 50% (p=1.06×10-2) and 35% (p=3.23×10-2), respectively. These results suggest that our proposed approach is promising in improving surgical human-robot collaboration.

摘要

本文提出了一种利用实时 3D 图像反馈生成动态虚拟夹具的方法,以促进医疗机器人中的人机协作。尽管在协作控制和规划方面进行了广泛的研究,但在像手术领域这样的动态环境中实现无缝共享控制仍然具有挑战性。为了解决这个问题,我们的方法使用来自 RGB-D 相机的点云数据生成的力场,动态创建虚拟夹具来引导套管放置机器人臂的操作。此外,“视图范围”概念选择性地确定用于计算点的区域,从而降低计算负载。在微创胸部手术中机器人辅助端口切口的幻影实验中,我们的方法显著提高了端口放置的准确性,将误差和完成时间分别降低了 50%(p=1.06×10-2)和 35%(p=3.23×10-2)。这些结果表明,我们提出的方法有望改善手术中的人机协作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0020/10820968/7a58d75ff88a/sensors-24-00492-g001.jpg

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