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，将穿刺针对准预先规划的路径，随后执行穿刺操作。目前该手术通过超声或X射线透视成像进行手动穿刺引导，这种方法精度有限且可重复性低。本研究将增强现实（AR）可视化技术与光学透视式头戴显示器（OST-HMD）及人机协作（HRC）框架相结合，以提升外科医生的手术任务完成效能。具体而言，通过执行"眼-手"标定、系统配准和全息模型配准实现视觉引导，同时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。通过实验验证系统性能，并与传统手动穿刺流程及二维监视器可视化界面进行对比。结果表明，本框架在所有实验组中实现了最低的中位数误差和标准差。此外，NASA-TLX用户评估结果显示，相比其他实验设置，本框架在任务完成过程中所需的工作负荷评分最低。本框架在PCNL任务中展现出显著的临床应用潜力，可增强外科医生的感知能力，促进无碰撞穿刺路径规划，并减少任务执行中的误差。