This paper was presented by Caitlin Sands at the 9th International Workshop on New Trends in Medical and Science Robotics (MESROB 2025) Conference in Poitiers, France July 2-4. The paper can be found in the Proceedings accessible via New Trends in Medical and Service Robotics: MESROB 2025 | SpringerLink. The paper itself can also be found via https://link.springer.com/chapter/10.1007/978-3-031-96081-9_4
Abstract. Due to the high demand for ophthalmic surgery and a shortage of surgeons, robot-assisted surgical systems have attracted attention from research communities for their potential to provide superior accuracy, precision, and motion stability, thus reducing the risk of hand tremors associated with manual surgery. However, existing surgical robotic platforms are less adaptable and efficient than traditional manual procedures. Additionally, the design process for these systems is challenging and time-consuming, requiring specialised expertise from multiple stakeholders. To address these challenges, this paper proposes a framework for applying generative design (GD) methods in developing surgical robots for ophthalmic procedures. It aims to generate diverse, feasible solutions, guided by input requirements and system analyses while facilitating continuous improvements to meet future needs. The paper presents the initial implementation of the proposed framework, which includes the development of a library of link geometries and fundamental 1-degree-of-freedom (DoF) mechanisms. These serve as the building blocks for remote centre of motion (RCM) mechanisms, which are critical for minimally invasive surgery (MIS) applications. The paper discusses the future development of the GD framework, aiming to enhance its capabilities for more complex surgical robotic mechanisms. It focuses on refining the framework to address scalability and validation challenges, ultimately improving design efficiency and adaptability for advanced systems
