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Background: Refractive surgery has evolved into a highly technology-driven discipline in which automation, precision engineering, and artificial intelligence converge to optimize visual outcomes. Robotic principles – defined by computer-guided motion control, closed-loop feedback, and image-integrated automation – are increasingly embedded within contemporary laser and lens-based platforms. This review synthesizes the current state of the art of robotics in refractive surgery, delineating established clinical applications and emerging autonomous technologies.

Methods: A structured narrative review of peer-reviewed literature and clinical outcome studies was conducted, focusing on robotic integration in corneal laser refractive surgery and lens-based refractive procedures. Particular emphasis was placed on femtosecond and excimer laser platforms, image-guided systems, AI-enhanced planning algorithms, and investigational microsurgical robotic devices.

Results: Modern femtosecond laser systems and excimer laser platforms represent de facto robotic systems, incorporating micron-level depth control, high-frequency multidimensional eye tracking, automated centration, and closed-loop laser–tissue interaction. In small-incision lenticule extraction (SMILE), advanced high-speed femtosecond platforms enable highly automated intrastromal lenticule creation with improved procedural efficiency and enhanced biomechanical preservation. In lens-based refractive surgery, femtosecond laser-assisted cataract platforms employ image-guided robotic capsulotomy and lens fragmentation to enhance intraocular lens centration and improve refractive predictability. Contemporary systems further integrate topography-guided and wavefront-optimized treatment algorithms, combining AI-driven nomogram refinement with real-time ocular tracking and adaptive laser delivery. Beyond corneal ablation, investigational microsurgical robotic devices demonstrate submillimeter motion scaling, tremor filtration, and image-guided precision, illustrating the translational potential of robotic manipulators for future refractive applications.

Conclusions: The current state of the art in refractive surgery is characterized by advanced laser automation functioning as highly specialized robotic systems augmented by AI-based planning and multimodal imaging. While fully autonomous refractive surgical robots have not yet entered routine clinical practice, ongoing integration of machine learning, real-time biomechanical modeling, and microsurgical robotics suggests a trajectory toward increasingly adaptive, semi-autonomous refractive platforms.