AIRS: Autonomous Intraoperative Robotic Suturing Based on Surgeon-Like Operation and Path Quantification in Keratoplasty

Automating surgical subtasks holds vast potential in robot-assisted surgeries, able to reduce surgeon fatigue and improve autonomy level. In this article, we propose an Autonomous Intraoperative Robotic Suturing (AIRS) system to imitate ophthalmologists to deliver a whole keratoplasty suturing including needle manipulation and knot tying. We introduce an autonomous strategy with a high-level task planner to generate quantified surgical paths and a low-level robotic controller to execute the paths. We first decompose the human keratoplasty into eight surgical phases and quantify the path primitives for each phase. Then two seven-DoF surgeon-like keratoplasty robots are built and the kinematics are deduced to execute surgical paths. To compute the changing motion parameters, a stereo vision algorithm is also developed to reconstruct 3-D features. Finally, to test the effectiveness of AIRS system, we perform autonomous robotic keratoplasty with single-interrupted sutures in phantom. With a desired threshold of 1 mm for position accuracy and 1$<^>{\circ }$ for needle pose adaptation, AIRS is able to complete interrupted sutures at eight equally distributed suturing planes around the incision. Experimental results demonstrate the potential of AIRS system to accomplish complex tasks with full autonomy and improve surgical consistency.