  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.
