# A surgical dataset from the da Vinci Research Kit for task automation and recognition

arXiv: https://arxiv.org/abs/2102.03643 · HTML: https://mlsanity.com/paper/2102.03643/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Feb 2021.

## Built on by (most cited first, 6 of 6)

- [General-purpose foundation models for increased autonomy in robot-assisted surgery](https://mlsanity.com/paper/2401.00678/) (2024)
- [Video-based Surgical Skills Assessment using Long term Tool Tracking](https://mlsanity.com/paper/2207.02247/) (2022)
- [SutureBot: A Precision Framework & Benchmark For Autonomous End-to-End Suturing](https://mlsanity.com/paper/2510.20965/) (2025)
- [A benchmark for video-based laparoscopic skill analysis and assessment](https://mlsanity.com/paper/2602.09927/) (2026)
- [Automated Surgical Skill Assessment in Endoscopic Pituitary Surgery using Real-time Instrument Tracking on a High-fidelity Bench-top Phantom](https://mlsanity.com/paper/2409.17025/) (2024)
- [SHANDS: A Multi-View Dataset and Benchmark for Surgical Hand-Gesture and Error Recognition Toward Medical Training](https://mlsanity.com/paper/2603.26400/) (2026)

## Abstract (arXiv)

The use of datasets is getting more relevance in surgical robotics since they can be used to recognise and automate tasks. Also, this allows to use common datasets to compare different algorithms and methods. The objective of this work is to provide a complete dataset of three common training surgical tasks that surgeons perform to improve their skills. For this purpose, 12 subjects teleoperated the da Vinci Research Kit to perform these tasks. The obtained dataset includes all the kinematics and dynamics information provided by the da Vinci robot (both master and slave side) together with the associated video from the camera. All the information has been carefully timestamped and provided in a readable csv format. A MATLAB interface integrated with ROS for using and replicating the data is also provided.