Important challenges in retinal microsurgery include prolonged operating time, inadequate force feedback, and poor depth perception due to a constrained top-down view of the surgery. The introduction of robot-assisted technology could potentially deal with such challenges and improve the surgeon's performance. Motivated by such challenges, this work develops a strategy for autonomous needle navigation in retinal microsurgery aiming to achieve precise manipulation, reduced end-to-end surgery time, and enhanced safety. This is accomplished through real-time geometry estimation and chance-constrained Model Predictive Control (MPC) resulting in high positional accuracy while keeping scleral forces within a safe level. The robotic system is validated using both open-sky and intact (with lens and partial vitreous removal) ex vivo porcine eyes. The experimental results demonstrate that the generation of safe control trajectories is robust to small motions associated with head drift. The mean navigation time and scleral force for MPC navigation experiments are 7.208 s and 11.97 mN, which can be considered efficient and well within acceptable safe limits. The resulting mean errors along lateral directions of the retina are below 0.06 mm, which is below the typical hand tremor amplitude in retinal microsurgery.

翻译：视网膜显微手术面临的重要挑战包括手术时间延长、力反馈不足以及因手术视野受限导致的深度感知困难。机器人辅助技术的引入有望应对这些挑战并提升外科医生的操作性能。受此类问题驱动，本研究开发了一种视网膜显微手术中自主针头导航策略，旨在实现精准操作、缩短全程手术时间并增强安全性。该策略通过实时几何估计与机会约束模型预测控制（MPC）实现高位置精度，同时将巩膜力维持在安全水平。采用离体猪眼进行开放式和完整（晶状体及部分玻璃体切除）两种场景的机器人系统验证。实验结果表明，安全控制轨迹的生成对头部漂移引起的小范围运动具有鲁棒性。MPC导航实验的平均导航时间为7.208秒，平均巩膜力为11.97 mN，可认为兼具高效性与良好安全裕度。沿视网膜横向的平均误差低于0.06毫米，该数值低于视网膜显微手术中典型的手震颤幅度。