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---
license: cc-by-4.0
language:
- en
tags:
- medical
---
# SutureBot: A Precision Framework and Benchmark for Autonomous End-to-End Suturing
This dataset is part of the **SutureBot** project, a benchmark for developing and evaluating autonomous surgical robotic policies for end-to-end suturing. It contains high-resolution, multi-camera video and robot kinematics from real robot demonstrations on tissue phantoms, supporting research in imitation learning, vision-language-action modeling, and surgical autonomy.
[project website](https://suturebot.github.io/) | [code repository](https://github.com/SutureBot/SutureBot/tree/ACT).
## Dataset Summary
The dataset includes:
- **Stereo endoscope images** (`left_img_dir`, `right_img_dir`)
- **Wrist camera views** (`endo_psm1`, `endo_psm2`)
- **Low-level kinematics** (end-effector pose, joint angles, jaw state, etc.) in `ee_csv.csv`
- **Multiple tissues** and **multiple task types** (e.g., needle pick-up, suturing)
- All data is organized by:
tissue_[id]/[task_name]/[episode_timestamp]/
The following is a visualization of the dataset folder structure:
```
$PATH_TO_DATASET
βββ [DATASET_NAME] # the dataset base dir
| βββ tissue_1 # data subset
| | βββ 1_[task_name] # task name
| | | βββ [episode] # should be timestamp when the data was recorded
| | | | βββ left_img_dir # left endoscope cam images (frame000000_left.jpg)
| | | | βββ right_img_dir # right endoscope cam images (frame000000_right.jpg)
| | | | βββ endo_psm1 # right wrist cam images (frame000000_psm1.jpg)
| | | | βββ endo_psm2 # left wrist cam images (frame000000_psm2.jpg)
| | | | βββ ee_csv.csv # kinematics
| βββ tissue_2 # data subset
| | βββ 1_[task_name] # task name
| | | βββ [episode] # should be timestamp when the data was recorded
| | | | βββ left_img_dir # left endoscope cam images (frame000000_left.jpg)
| | | | βββ right_img_dir # right endoscope cam images (frame000000_right.jpg)
| | | | βββ endo_psm1 # right wrist cam images (frame000000_psm1.jpg)
| | | | βββ endo_psm2 # left wrist cam images (frame000000_psm2.jpg)
| | | | βββ ee_csv.csv # kinematics
...
```
Each episode is a complete trajectory from a real robotic execution using a da Vinci Research Kit (dVRK) platform.
---
## Usage
This dataset is designed for training and evaluating autonomous policies that take as input multi-view RGB images (optionally language-conditioned), and output continuous control actions.
It supports a wide range of applications including:
- Behavioral cloning and offline RL
- Multi-modal policy learning (images + kinematics + language)
- Visual servoing and tool tracking
- Surgical robot benchmarking
---
## File Structure
Each episode contains:
- `left_img_dir/`: Left endoscope camera images
- `right_img_dir/`: Right endoscope camera images
- `endo_psm1/`: Right wrist (PSM1) camera images
- `endo_psm2/`: Left wrist (PSM2) camera images
- `ee_csv.csv`: Kinematic data including joint states, poses, and jaw angles
---
## Format
- Image format: `.jpg`, RGB
- Kinematics: CSV with columns such as:
- `timestamp`
- `psm1_pose.position.{x,y,z}`
- `psm1_pose.orientation.{x,y,z,w}`
- `psm1_js[0-5]`, `psm2_js[0-5]`, etc.
- `ecm_pose.*`, `suj_pose.*`, etc.
A complete list of columns is available in the `dataset.croissant.json` schema.
---
## Citation
If you use this dataset, please cite:
```bibtex
@misc{suturebot2025,
title = {SutureBot: A Precision Framework and Benchmark for Autonomous End-to-End Suturing},
author = {Jesse Haworth, Juo-Tung Chen, Nigel Nelson, Ji Woong Kim, Masoud Moghani, Chelsea Finn, Axel Krieger},
year = {2025},
note = {Under review at NeurIPS 2025 Datasets and Benchmarks Track},
howpublished = {\url{https://huggingface.co/datasets/jchen396/suturebot}}
}
```
## License
This dataset is licensed under CC-BY-4.0. Please credit the authors when using this dataset.
## Contact
For questions or collaboration inquiries, please contact:
Juo-Tung Chen
Johns Hopkins University
π§ jchen396@jh.edu |