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

Performing intricate eye microsurgery, such as 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 has to do with 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 address crucial safety considerations, such as minimizing contact force between the surgical instrument and the sclera surface to prevent tissue damage. An adaptive sclera force control algorithm was proposed to address this limitation using an FBG-based force-sensing tool to measure and minimize the tool-sclera interaction force. Additionally, features like haptic feedback or hand motion scaling, which can improve the safety and precision of surgery, require a teleoperation control framework. We implemented a bimanual adaptive teleoperation (BMAT) control mode using SHER 2.0 and SHER 2.1 and compared its performance with a bimanual adaptive cooperative (BMAC) mode. Both BMAT and BMAC modes were tested in sitting and standing postures during a vessel-following experiment under a surgical microscope. It is shown, for the first time to the best of our knowledge in robot-assisted retinal surgery, that integrating the adaptive sclera force control algorithm with the bimanual teleoperation framework enables surgeons to safely perform bimanual telemanipulation of the eye without over-stretching it, even in the absence of registration between the two robots.