  Important challenges in retinal microsurgery include prolonged operating
time, inadequate force feedback, and poor depth perception due to a constrained
top-down view of the surgery. The introduction of robot-assisted technology
could potentially deal with such challenges and improve the surgeon's
performance. Motivated by such challenges, this work develops a strategy for
autonomous needle navigation in retinal microsurgery aiming to achieve precise
manipulation, reduced end-to-end surgery time, and enhanced safety. This is
accomplished through real-time geometry estimation and chance-constrained Model
Predictive Control (MPC) resulting in high positional accuracy while keeping
scleral forces within a safe level. The robotic system is validated using both
open-sky and intact (with lens and partial vitreous removal) ex vivo porcine
eyes. The experimental results demonstrate that the generation of safe control
trajectories is robust to small motions associated with head drift. The mean
navigation time and scleral force for MPC navigation experiments are 7.208 s
and 11.97 mN, which can be considered efficient and well within acceptable safe
limits. The resulting mean errors along lateral directions of the retina are
below 0.06 mm, which is below the typical hand tremor amplitude in retinal
microsurgery.
