Imitation Learning for Robot Assistance in Open Surgery: A Multi-Policy Evaluation on Suture Following
On the map: Offline RL and imitation learning from data → Safe offline RL
Abstract (arXiv)
This study presents the first evaluation of general-purpose imitation learning for surgeon-robot collaborative assistance in open surgery, targeting suture following: the grab-pull-release motion an assistant performs at every stitch. We collect 160 teleoperated demonstrations (32,374 frames) on an open-source robot arm, benchmark four architecturally diverse imitation learning policies (ACT, Diffusion Policy, SmolVLA, π0) across 28 trained models evaluated in 32 configurations along three clinically motivated dimensions: dataset size, camera viewpoint, and background variation. Our results demonstrate that under ideal conditions, the four policies achieve 50-75% task success, with depth error as the dominant failure mode across all architectures. Among all policies, π0 achieves the strongest results with a pretrained vision-language backbone, demonstrating superior data efficiency, greater robustness to background variation, and smoother trajectories compatible with surgical workflow. When deployed in a surgeon-robot suturing trial, π0 yields a 92% stitch completion rate. These findings establish collaborative robotic assistance in open surgery as a feasible target for imitation learning and highlight depth perception and end-effector design as key priorities for clinical translation.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Safe offline RL, one of 13 directions in Offline RL and imitation learning from data. Builds on 16 of its 33 references that are in the map. First posted on arXiv 27 May 2026.
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16 of 33 references.
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- 2025SRT-H: A Hierarchical Framework for Autonomous Surgery via Language Conditioned Imitation Learning15 May
- 2024Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks17 Jul
Other references · 14
- 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,838
- 2024π0: A Vision-Language-Action Flow Model for General Robot Controlcited by 2,407
- 2023Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardwarecited by 1,568
- 2023LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learningcited by 1,410
- 2019Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learningcited by 1,204
- 2025SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Roboticscited by 530
- 2024Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperationcited by 391
- 2024Behavior Generation with Latent Actionscited by 160
- 2026LeRobot: An Open-Source Library for End-to-End Robot Learningcited by 73
- 2021SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learningcited by 31
- 2024RoboNurse-VLA: Robotic Scrub Nurse System based on Vision-Language-Action Modelcited by 29
- 2024ORBIT-Surgical: An Open-Simulation Framework for Learning Surgical Augmented Dexteritycited by 16
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- 2026SurgVIL: Scaling Surgical Robot Imitation Learning with Open-source Surgical Videos
- 2025SurgiPose: Estimating Surgical Tool Kinematics from Monocular Video for Surgical Robot Learning
- 2025Towards Suturing World Models: Learning Predictive Models for Robotic Surgical Tasks
- 2026Supervised Mixture-of-Experts for Surgical Grasping and Retraction
- 2020Intermittent Visual Servoing: Efficiently Learning Policies Robust to Instrument Changes for High-precision Surgical Manipulation
- 2021Learning needle insertion from sample task executions
- 2025DARIL: When Imitation Learning outperforms Reinforcement Learning in Surgical Action Planning
- 2023Toward a Surgeon-in-the-Loop Ophthalmic Robotic Apprentice using Reinforcement and Imitation Learning