2025-07-09 ジョンズ・ホプキンス大学 (JHU)
<関連情報>
- https://hub.jhu.edu/2025/07/09/robot-performs-first-realistic-surgery-without-human-help/
- https://www.science.org/doi/10.1126/scirobotics.adt5254
SRT-H:言語条件付き模倣学習による自律手術のための階層的フレームワーク 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, […] , and Axel Krieger
Science Robotics Published:9 Jul 2025
DOI:https://doi.org/10.1126/scirobotics.adt5254
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.
