  Retinal surgery is a complex medical procedure that requires exceptional
expertise and dexterity. For this purpose, several robotic platforms are
currently being developed to enable or improve the outcome of microsurgical
tasks. Since the control of such robots is often designed for navigation inside
the eye in proximity to the retina, successful trocar docking and inserting the
instrument into the eye represents an additional cognitive effort, and is,
therefore, one of the open challenges in robotic retinal surgery. For this
purpose, we present a platform for autonomous trocar docking that combines
computer vision and a robotic setup. Inspired by the Cuban Colibri
(hummingbird) aligning its beak to a flower using only vision, we mount a
camera onto the endeffector of a robotic system. By estimating the position and
pose of the trocar, the robot is able to autonomously align and navigate the
instrument towards the Trocar's Entry Point (TEP) and finally perform the
insertion. Our experiments show that the proposed method is able to accurately
estimate the position and pose of the trocar and achieve repeatable autonomous
docking. The aim of this work is to reduce the complexity of robotic setup
preparation prior to the surgical task and therefore, increase the
intuitiveness of the system integration into the clinical workflow.
