A Situation-Aware Autonomous Camera Alignment for Enhanced Suturing in Robot-Assisted Minimally Invasive Surgery

In robot-assisted minimally invasive surgery, optimal camera positioning is crucial for effective visualization and manipulation of tissues, which impacts the success of procedures. Traditional camera control can increase cognitive workload, lead to suboptimal camera viewpoints, and complicate surgical tasks. We propose an autonomous camera system that uses situational awareness and real-time prediction of user intent from kinematic data, and adjusts the camera position dynamically during a simulated suturing task. Such a system reduces the need to manually adjust the camera, allowing users to stay focused on the procedure. We demonstrated the framework in a user study with eight non-expert participants. They used the da Vinci Research Kit to control a simulated camera and instruments in a suturing task. We compared the performances in the suturing task with the autonomous and the teleoperated camera control. The autonomous system reduced execution time by 43% , shortened path length by 30% , and decreased completion cost by 35%. These results serve as a proof of concept for a situationally aware camera system and suggest that autonomous camera control can improve efficiency and simplify surgical workflow.