A robot outperformed a seasoned surgeon in completing a common training task with equal precision during a study conducted by a multinational team of researchers. Researchers at South Korea's Daegu Gyeongbuk Institute of Science and Technology tracked the arm movements of a da Vinci robotic surgical assistant using 3D printed markers.
Analysis via a machine-learning algorithm suggested the trained model can reduce the mean tracking error by 78%, from 2.96 millimeters (mm) to 0.65 mm. An experienced surgeon and nine volunteers with no surgical experience used a da Vinci system to complete three variations of a peg transfer task. The fully automated robot performed the bilateral tasks faster and more accurately than the surgeon.
More information:
https://spectrum.ieee.org/robot-outperforms-a-surgeon-in-a-precision-training-task