# STITCH: Augmented Dexterity for Suture Throws Including Thread Coordination and Handoffs

arXiv: https://arxiv.org/abs/2404.05151 · HTML: https://mlsanity.com/paper/2404.05151/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2024.

## Built on by (most cited first, 3 of 3)

- [SutureBot: A Precision Framework & Benchmark For Autonomous End-to-End Suturing](https://mlsanity.com/paper/2510.20965/) (2025)
- [dARt Vinci: Egocentric Data Collection for Surgical Robot Learning at Scale](https://mlsanity.com/paper/2503.05646/) (2025)
- [SurgIRL: Towards Life-Long Learning for Surgical Automation by Incremental Reinforcement Learning](https://mlsanity.com/paper/2409.15651/) (2024)

## Abstract (arXiv)

We present STITCH: an augmented dexterity pipeline that performs Suture Throws Including Thread Coordination and Handoffs. STITCH iteratively performs needle insertion, thread sweeping, needle extraction, suture cinching, needle handover, and needle pose correction with failure recovery policies. We introduce a novel visual 6D needle pose estimation framework using a stereo camera pair and new suturing motion primitives. We compare STITCH to baselines, including a proprioception-only and a policy without visual servoing. In physical experiments across 15 trials, STITCH achieves an average of 2.93 sutures without human intervention and 4.47 sutures with human intervention. See https://sites.google.com/berkeley.edu/stitch for code and supplemental materials.