Chief Supervisor

Dr SHI Danli

Project Title

Synopsis

The growing demand for ophthalmic services has increased the workload associated with routine examinations, while shortages of trained clinical personnel continue to limit the accessibility and efficiency of eye care. Although artificial intelligence has demonstrated strong capabilities in ophthalmic image analysis and clinical decision support, most existing systems remain confined to digital tasks and cannot independently perform the physical procedures required to acquire diagnostic information. Ophthalmic examinations involve a sequence of interdependent activities, including navigating between examination stations, positioning patients and equipment, operating diagnostic instruments, monitoring image quality, and responding to unexpected changes. These activities are particularly challenging for robots because ophthalmic devices are designed for human operators, clinical environments are dynamic and shared with patients and staff, and physical interactions must satisfy strict requirements for accuracy and safety.
This project aims to develop an embodied robotic system capable of understanding clinical instructions and autonomously completing essential ophthalmic examination tasks. The research will address the integration of environmental perception, mobile navigation, precise instrument manipulation, long-horizon task coordination, and safe human–robot interaction. The system will be progressively evaluated using diagnostic device mock-ups, model eyes, and controlled clinical scenarios. Its performance will be assessed in terms of task completion, operational accuracy, adaptability to environmental and device variations, recovery from execution failures, and compliance with safety constraints. The project will provide a foundation for robotic assistants that can support routine ophthalmic examinations under professional supervision and improve the efficiency and accessibility of ophthalmic care.