Surgical task-space optimisation of the CYCLOPS robotic system
This work addresses the need for procedure- and patient-specific optimization in surgical robotics, though it appears incremental as it builds on existing systems with a new method for data collection.
The paper tackled the problem of optimizing the CYCLOPS robotic system for minimally invasive surgery by developing a task-space optimization method and a simulation-based data collection approach, demonstrating successful optimization for Endoscopic Submucosal Dissection.
The CYCLOPS is a cable-driven parallel mechanism used for minimally invasive applications, with the ability to be customised to different surgical needs; allowing it to be made procedure- and patient-specific. For adequate optimisation, however, appropriate data on clinical constraints and task-space is required. Whereas the former can be provided through preoperative planning and imaging, the latter remains a problem, primarily for highly dexterous MIS systems. The current work focuses on the development of a task-space optimisation method for the CYCLOPS system and the development of a data collection method in a simulation environment for minimally invasive task-spaces. The same data collection method can be used for the development of other minimally invasive platforms. A case-study is used to illustrate the developed method for Endoscopic Submucosal Dissection (ESD). This paper shows that using this method, the system can be succesfully optimised for this application.