VR Isle Academy：一种用于机器人手术技能培养的 VR 数字孪生方法
VR Isle Academy: A VR Digital Twin Approach for Robotic Surgical Skill Development
AI总结：
本文提出 VR Isle Academy，一种便携、设备无关且支持手脚追踪的超逼真 VR 数字孪生系统，用于低成本训练手术机器人操作技能，实验证明其能显著降低操作误差并缩短学习曲线。
摘要：
当代机器人领域的进展以效率和稳定性的提升为标志，为手术机器人系统（SRS）的全球普及铺平了道路。尽管这些系统通过提供更精确、创伤更小的手术方式增强了外科医生的技能，但其成本相当高昂。此外，SRS 组件通常涉及重型机械，由于对此类设备的访问受限，培训过程面临挑战。本文提出了一种经济高效的方法，通过便携式、设备无关、超逼真的仿真来辅助 SRS 模拟器培训，并支持手部追踪和脚部追踪。误差评估支持实时和离线两种方式，从而能够监测和追踪用户表现。该 VR 应用已由多名未经训练的测试者进行了客观评估，结果表明随着训练次数增加，误差指标显著下降。这表明所提出的名为 VR Isle Academy 的 VR 应用运行高效，以直观和沉浸式的方式提升了测试者的机器人控制技能，从而以最低成本缩短学习曲线。
英文摘要：
Contemporary progress in the field of robotics, marked by improved efficiency and stability, has paved the way for the global adoption of surgical robotic systems (SRS). While these systems enhance surgeons' skills by offering a more accurate and less invasive approach to operations, they come at a considerable cost. Moreover, SRS components often involve heavy machinery, making the training process challenging due to limited access to such equipment. In this paper we introduce a cost-effective way to facilitate training for a simulator of a SRS via a portable, device-agnostic, ultra realistic simulation with hand tracking and feet tracking support. Error assessment is accessible in both real-time and offline, which enables the monitoring and tracking of users' performance. The VR application has been objectively evaluated by several untrained testers showcasing significant reduction in error metrics as the number of training sessions increases. This indicates that the proposed VR application denoted as VR Isle Academy operates efficiently, improving the robot - controlling skills of the testers in an intuitive and immersive way towards reducing the learning curve at minimal cost.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
