During Percutaneous Nephrolithotomy (PCNL) operations, the surgeon is required to define the incision point on the patient's back, align the needle to a pre-planned path, and perform puncture operations afterward. The procedure is currently performed manually using ultrasound or fluoroscopy imaging for needle orientation, which, however, implies limited accuracy and low reproducibility. This work incorporates Augmented Reality (AR) visualization with an optical see-through head-mounted display (OST-HMD) and Human-Robot Collaboration (HRC) framework to empower the surgeon's task completion performance. In detail, Eye-to-Hand calibration, system registration, and hologram model registration are performed to realize visual guidance. A Cartesian impedance controller is used to guide the operator during the needle puncture task execution. Experiments are conducted to verify the system performance compared with conventional manual puncture procedures and a 2D monitor-based visualisation interface. The results showed that the proposed framework achieves the lowest median and standard deviation error across all the experimental groups, respectively. Furthermore, the NASA-TLX user evaluation results indicate that the proposed framework requires the lowest workload score for task completion compared to other experimental setups. The proposed framework exhibits significant potential for clinical application in the PCNL task, as it enhances the surgeon's perception capability, facilitates collision-free needle insertion path planning, and minimises errors in task completion.

翻译：在经皮肾镜取石术（PCNL）操作中，外科医生需要在患者背部确定切口点，将穿刺针与预设路径对齐，随后执行穿刺操作。目前该过程依赖超声或荧光镜成像进行手动穿刺引导，存在精度有限且可重复性低的问题。本研究结合增强现实（AR）可视化技术（采用光学透视头戴式显示器OST-HMD）与人机协作（HRC）框架，以提升外科医生的任务执行效能。具体通过眼手标定、系统配准及全息模型注册实现视觉引导，并采用笛卡尔阻抗控制器在穿刺任务执行过程中引导操作者。通过与传统手动穿刺及基于二维监视器的可视化界面进行对比实验，验证了系统性能。结果表明：所提框架在所有实验组中均实现了最低的中值误差与标准差误差。此外，NASA-TLX用户评估结果显示，相较于其他实验设置，该框架完成任务所需的工作负荷评分最低。本框架通过增强外科医生的感知能力、辅助规划无碰撞穿刺路径并最小化任务执行误差，在PCNL任务中展现出显著的临床应用潜力。