Robotic assistance is becoming a standard in Minimally Invasive Surgery.
Despite its clinical benefits and technical potential, surgeons still have to perform manu-
ally a number of monotonous and time-consuming surgical subtasks, like knot-tying or
blunt dissection. Many believe that the next bold step in the advancement of robotic
surgery is the automation of such subtasks. Partial automation can reduce the cogni-
tive load on surgeons, and support them in paying more attention to the critical elements
of the surgical workflow. Our aim was to develop a software framework to ease and
hasten the automation of surgical subtasks. This framework was built alongside the Da
Vinci Research Kit (DVRK), while it can be ported onto other robotic platforms, since
it is based on the Robot Operating System (ROS). The software includes both stereo
vision-based and hierarchical motion planning, with a wide palette of often used surgi-
cal gestures—such as grasping, cutting or soft tissue manipulation—as building blocks to
support the high-level implementation of autonomous surgical subtask execution routines.
This open-source surgical automation framework—named irob-saf—is available at
https://github.com/ABC-iRobotics/irob-saf
