论文标题
RGB-D语义大满贯，用于手术室的手术机器人导航
RGB-D Semantic SLAM for Surgical Robot Navigation in the Operating Room
论文作者
论文摘要
获得手术机器人系统手术室（或）的空间意识是一项关键技术，可以实现旨在改善或工作流程的智能应用程序。在这项工作中，我们提出了一种使用多个附加并注册到Da Vinci XI手术系统的RGB-D摄像机对或场景进行语义密集重建的方法。我们开发了一种新颖的SLAM方法，用于在动态或环境中的机器人姿势跟踪以及静态或表对象的密集重建。我们通过模拟或通过相应的光跟踪轨迹作为地面真理和手动注释100帧分割掩码来验证了我们的技术。平均绝对轨迹错误为$ 11.4 \ pm1.9 $ mm，平均相对姿势错误为$ 1.53 \ pm0.48 $度每秒。与单帧相比，使用我们的SLAM系统将分割骰子得分从0.814提高到0.902。我们的方法有效地在动态临床环境中产生了密集或表的重建，并在单个图像框架上改善了语义分割。
Gaining spatial awareness of the Operating Room (OR) for surgical robotic systems is a key technology that can enable intelligent applications aiming at improved OR workflow. In this work, we present a method for semantic dense reconstruction of the OR scene using multiple RGB-D cameras attached and registered to the da Vinci Xi surgical system. We developed a novel SLAM approach for robot pose tracking in dynamic OR environments and dense reconstruction of the static OR table object. We validated our techniques in a mock OR by collecting data sequences with corresponding optical tracking trajectories as ground truth and manually annotated 100 frame segmentation masks. The mean absolute trajectory error is $11.4\pm1.9$ mm and the mean relative pose error is $1.53\pm0.48$ degrees per second. The segmentation DICE score is improved from 0.814 to 0.902 by using our SLAM system compared to single frame. Our approach effectively produces a dense OR table reconstruction in dynamic clinical environments as well as improved semantic segmentation on individual image frames.
