Automating multi-throw multilateral surgical suturing with a mechanical needle guide and sequential convex optimization

Abstract

Abstract-For supervised automation of multi-throw suturing in Robot-Assisted Minimally Invasive Surgery, we present a novel mechanical needle guide and a framework for optimizing needle size, trajectory, and control parameters using sequential convex programming. The Suture Needle Angular Positioner (SNAP) results in a 3x error reduction in the needle pose estimate in comparison with the standard actuator. We evaluate the algorithm and SNAP on a da Vinci Research Kit using tissue phantoms and compare completion time with that of humans from the JIGSAWS dataset [5]. Initial results suggest that the dVRK can perform suturing at 30% of human speed while completing 86% suture throws attempted. Videos and data are available at: berkeleyautomation.github.io/amts

Using intermittent synchronization to compensate for rhythmic body motion during autonomous surgical cutting and debridement

“…We use the da Vinci Research Kit (dVRK) [15,16] as our RSA, which is a research platform based on Intuitive Surgical's da Vinci surgical system [17] and which has been frequently used in surgical robotics research [3,7,[18][19][20].…”

“…Automation of surgical sub-tasks has the potential to reduce surgeon tedium and fatigue, operating time, and enable supervised tele-surgery over high-latency networks. Several recent papers have proposed techniques for introducing limited autonomy in surgery almost all in static environments [2][3][4][5][6][7][8].…”

Virtual Fixture Assistance for Suturing in Robot-Aided Pediatric Endoscopic Surgery

“…One of those methodologies is task automation [6], [9], which has been so far demonstrated in an unobstructed space, which is not the case in pediatric endoscopy. Moreover, although the future potential of such techniques is clear, currently they are still outperformed by human-operated robots and are unable to leverage surgical skill efficiently.…”

Manipulating Soft Tissues by Deep Reinforcement Learning for Autonomous Robotic Surgery

“…The use of robot-assisted surgery allows doctors to automate a complicated task with minimal errors and effort. A number of automation levels have been discussed extensively in the literature [15]- [21]. Specifically, early approaches required the existence of experts to create a model trajectory that is used to teach a robot to automatically complete a designated task.…”