Bimanual Manipulation of Steady-Hand Eye Robots with Adaptive Sclera Force Control: Cooperative vs. Teleoperation Strategies.

Performing retinal vein cannulation (RVC) as a potential treatment for retinal vein occlusion (RVO) without the assistance of a surgical robotic system is very challenging to do safely. The main limitation is the physiological hand tremor of surgeons. Robot-assisted eye surgery technology may resolve the problems of hand tremors and fatigue and improve the safety and precision of RVC. The Steady-Hand Eye Robot (SHER) is an admittance-based robotic system that can filter out hand tremors and enables ophthalmologists to manipulate a surgical instrument inside the eye cooperatively. However, the admittance-based cooperative control mode does not safely minimize the contact force between the surgical instrument and the sclera to prevent tissue damage. In addition, features such as haptic feedback or hand motion scaling, which can improve the safety and precision of surgery, require a teleoperation control framework. This work presents, for the first time in the field of robot-assisted retinal microsurgery research, a registration-free bimanual adaptive teleoperation (BMAT) control framework using SHER 2.0 and SHER 2.1 robotic systems. Both SHERs are integrated with an adaptive force control (AFC) algorithm that dynamically and automatically minimizes the tool-sclera interaction forces, enforcing them within a safe limit. The scleral forces are measured using two fiber Bragg grating (FBG)-based force-sensing tools. The performance of the proposed BMAT control framework is evaluated by comparison with a bimanual adaptive cooperative (BMAC) framework in a vessel-following experiment conducted under a surgical microscope. Experimental results demonstrate the effectiveness of the BMAT control framework in performing a safe bimanual telemanipulation of the eye without over-stretching it, even in the absence of registration between the two robots.