无需相同机器人配置，专家演示可自动适配新手训练
Setup-Invariant Augmented Reality for Teaching by Demonstration with Surgical Robots
- 通过姿态估计实现不同配置下专家示范的精准对齐
- 用户研究显示任务完成速度提升，碰撞减少，成功率提高
- 适合外科手术初学者在非手术场景接受专家指导
增强现实（AR）在机器人手术教学中具有优势，能结合三维引导与探索性学习。然而现有系统需专家监督，且不支持导师与学员机器人配置差异。为使初学者可在手术室外获得专家指导，我们提出dV-STEAR：一个开源系统，可在不假设导师与学员机器人关节位置一致的前提下回放任务对齐的专家示范。姿态估计验证显示注册误差为3.86±2.01mm。用户研究（N=24）表明，dV-STEAR显著提升新手在腹腔镜手术基础任务中的表现：单手环过导线任务中完成速度更快（p=0.03），碰撞时间更短（p=0.01）；抓取放置任务成功率更高（p=0.004）。两个任务中，使用dV-STEAR的参与者手部使用更均衡，主观沮丧感更低。本研究基于da Vinci Research Kit构建新教学工具，证明其有效性，并为未来机器人辅助手术中AR集成奠定基础。
原文摘要 · Abstract (English)
Augmented reality (AR) is an effective tool in robotic surgery education as it combines exploratory learning with three-dimensional guidance. However, existing AR systems require expert supervision and do not account for differences in the mentor and mentee robot configurations. To enable novices to train outside the operating room while receiving expert-informed guidance, we present dV-STEAR: an open-source system that plays back task-aligned expert demonstrations without assuming identical setup joint positions between expert and novice. Pose estimation was rigorously quantified, showing a registration error of 3.86 (SD=2.01)mm. In a user study (N=24), dV-STEAR significantly improved novice performance on tasks from the Fundamentals of Laparoscopic Surgery. In a single-handed ring-over-wire task, dV-STEAR increased completion speed (p=0.03) and reduced collision time (p=0.01) compared to dry-lab training alone. During a pick-and-place task, it improved success rates (p=0.004). Across both tasks, participants using dV-STEAR exhibited significantly more balanced hand use and reported lower frustration levels. This work presents a novel educational tool implemented on the da Vinci Research Kit, demonstrates its effectiveness in teaching novices, and builds the foundation for further AR integration into robot-assisted surgery.
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