# SurgicAI: A Hierarchical Platform for Fine-Grained Surgical Policy Learning and Benchmarking

arXiv: https://arxiv.org/abs/2406.13865 · HTML: https://mlsanity.com/paper/2406.13865/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jun 2024.

## Built on by (most cited first, 4 of 4)

- [Towards Cross-View Point Correspondence in Vision-Language Models](https://mlsanity.com/paper/2512.04686/) (2025)
- [SutureBot: A Precision Framework & Benchmark For Autonomous End-to-End Suturing](https://mlsanity.com/paper/2510.20965/) (2025)
- [Safe Uncertainty-Aware Learning of Robotic Suturing](https://mlsanity.com/paper/2505.16596/) (2025)
- [Imitation Learning for Robot Assistance in Open Surgery: A Multi-Policy Evaluation on Suture Following](https://mlsanity.com/paper/2605.28736/) (2026)

## Abstract (arXiv)

Despite advancements in robotic-assisted surgery, automating complex tasks like suturing remain challenging due to the need for adaptability and precision. Learning-based approaches, particularly reinforcement learning (RL) and imitation learning (IL), require realistic simulation environments for efficient data collection. However, current platforms often include only relatively simple, non-dexterous manipulations and lack the flexibility required for effective learning and generalization. We introduce SurgicAI, a novel platform for development and benchmarking addressing these challenges by providing the flexibility to accommodate both modular subtasks and more importantly task decomposition in RL-based surgical robotics. Compatible with the da Vinci Surgical System, SurgicAI offers a standardized pipeline for collecting and utilizing expert demonstrations. It supports deployment of multiple RL and IL approaches, and the training of both singular and compositional subtasks in suturing scenarios, featuring high dexterity and modularization. Meanwhile, SurgicAI sets clear metrics and benchmarks for the assessment of learned policies. We implemented and evaluated multiple RL and IL algorithms on SurgicAI. Our detailed benchmark analysis underscores SurgicAI's potential to advance policy learning in surgical robotics. Details: https://github.com/surgical-robotics-ai/SurgicAI