Michael Yip

Associate Professor of Electrical and Computer Engineering at UC San Diego, Director of the Advanced Robotics and Controls Laboratory, and Director of the Healthcare and Medical Robotics Collaboratory at the UCSD Contextual Robotics Institute. His work focuses on surgical robotics, biomimetic robots, robot learning, autonomous robotic surgery, and reinforcement learning for robot control.

Autonomous Medical Robots Need Physics Models, Not Just Foundation Models

UC San Diego professor Michael Yip argues in a Stanford Robotics Seminar that medical robotics must move beyond teleoperation if it is to address healthcare labor shortages. Current surgical robots can improve precision but still depend on a surgeon’s skill, while surgery’s scarce data, deformable tissue, safety constraints, and need for millimeter accuracy make end-to-end learning an inadequate answer on its own. Yip makes the case for a hybrid path: modern perception where it works, explicit physics and control where contact demands it, and humanoid platforms where broader hospital tasks require more general embodiment.

Stanford OnlineMay 12, 202617 min read