Robot Assisted Surgery

Robot-assisted surgery (RAS) aims to improve surgical precision, safety, and efficiency through robotic systems. Current research heavily focuses on enhancing autonomy through advancements in computer vision (e.g., using transformers and neural radiance fields for 3D scene reconstruction and instrument tracking), machine learning (e.g., employing deep reinforcement learning for task automation and semi-supervised learning for skill assessment), and haptic feedback systems. These improvements are significant because they have the potential to reduce surgeon workload, improve surgical outcomes, and expand access to complex procedures.