在虚拟现实中教授用户指定的逆运动学,减少了手动引导冗余手术机器人的时间和精力。

Murali Karnam, Marek Zelechowski, Philippe C Cattin, Georg Rauter, Nicolas Gerig
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引用次数: 0

摘要

在医疗过程中,医疗机器人不应与附近的障碍物碰撞,如灯具、屏幕或医务人员。冗余机器人具有比手术中移动内窥镜工具所需的更多自由度,并且可以通过纯粹在这些额外自由度的空间(零空间)中移动来重塑以避开障碍物。尽管最先进的机器人允许外科医生手动引导内窥镜工具,但对外科医生来说,在零空间中重塑机器人并不直观。在这里,我们提出了一种学习任务空间控制,允许外科医生直观地教授首选的机器人配置(形状),在模拟中使用基于vr的规划器来避开障碍物。在手术后期,外科医生用一只手控制内窥镜工具和机器人的结构(形状)。在一项用户研究中,我们发现学习任务空间控制在所有测量的性能指标(时间、工作量和用户感知的工作量)中都优于最先进的朴素任务空间控制。我们的解决方案允许用户在VR中直观地与机器人交互,并在医疗和工业应用中移动工具时重塑机器人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
User-specified inverse kinematics taught in virtual reality reduce time and effort to hand-guide redundant surgical robots.

Medical robots should not collide with close by obstacles during medical procedures, such as lamps, screens, or medical personnel. Redundant robots have more degrees of freedom than needed for moving endoscopic tools during surgery and can be reshaped to avoid obstacles by moving purely in the space of these additional degrees of freedom (null space). Although state-of-the-art robots allow surgeons to hand-guide endoscopic tools, reshaping the robot in null space is not intuitive for surgeons. Here we propose a learned task space control that allows surgeons to intuitively teach preferred robot configurations (shapes) that avoid obstacles using a VR-based planner in simulation. Later during surgery, surgeons control both the endoscopic tool and robot configuration (shape) with one hand. In a user study, we found that learned task space control outperformed state-of-the-art naive task space control in all the measured performance metrics (time, effort, and user-perceived effort). Our solution allowed users to intuitively interact with robots in VR and reshape robots while moving tools in medical and industrial applications.

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