From Instrument-Mounted Demonstrations to In-Vivo Execution: Learning Bimanual Laparoscopic Appendectomy Without Robot-Collected Demonstrations

arXiv:2609.25625 · cs.RO · Submitted 2026-09-22 · Read on arXiv

cs.RO

Submitted: 2026-09-22

Updated: 2026-09-22

Comments: Submitted to IEEE ICRA 2027

Code: https://github.com/Rosota-Research/ICRA2027-Invivo-main

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 4× in this paper · explained in 2 episodes
• Aperture — 3× in this paper · explained in 1 episode
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Sim-to-Real Transfer — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Action Chunking — 1× in this paper · explained in 1 episode
• Domain Shift — 1× in this paper · explained in 4 episodes
• Transferability — 1× in this paper · explained in 4 episodes

Sources

• On Bringing Robots Home
• SurgVIL: Scaling Surgical Robot Imitation Learning with Open-source Surgical Videos
• DINOv3
• $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
• Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

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