Article intro - Hierarchical Framework for AutonomousSurgery
Dr. Krieger et al. at Johns Hopkins' LCSR keep advancing on the track of surgical subtask automation - documented in their most recent Science Robotics (vol. 10. issue 104) article as well. In their publication: "SRT-H: A hierarchical framework for autonomous surgery via language-conditioned imitation learning", Ji Woong (Brian) Kim, Juo-Tung Chen, Pascal Hansen, Lucy Xiaoyang Shi, Antony Goldenberg , Samuel Schmidgall, Paul Maria Scheikl, Anton Deguet, Brandon M. White, De Ru Tsai, Richard Jaepyeong Cha, Jeffrey Jopling, Chelsea Finn, and Axel Krieger documented their latest ex-vivo
Abstract
Research
on autonomous surgery has largely focused on simple task automation in
controlled environments. However, real-world surgical applications
demand dexterous manipulation over extended durations and robust
generalization to the inherent variability of human tissue. These
challenges remain difficult to address using existing logic-based or
conventional end-to-end learning strategies. To address this gap, we
propose a hierarchical framework for performing dexterous, long-horizon
surgical steps. Our approach uses a high-level policy for task planning
and a low-level policy for generating low-level trajectories. The
high-level planner plans in language space, generating task-level or
corrective instructions that guide the robot through the long-horizon
steps and help recover from errors made by the low-level policy. We
validated our framework through ex vivo experiments on cholecystectomy, a
commonly practiced minimally invasive procedure, and conducted ablation
studies to evaluate key components of the system. Our method achieves a
100% success rate across eight different ex vivo gallbladders,
operating fully autonomously without human intervention. The
hierarchical approach improved the policy’s ability to recover from
suboptimal states that are inevitable in the highly dynamic environment
of realistic surgical applications. This work demonstrates step-level
autonomy in a surgical procedure, marking a milestone toward clinical
deployment of autonomous surgical systems.
Source: Science Robotics, EurekAlert
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