# From Grasping to Dexterous Manipulation: Large-Scale Grasp Pretraining for Dexterous Manipulation

- Source: arXiv cs.RO
- Published: 2026-10-28T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/pa06pajs67dxs7p9dlcdzytzw
- Original: https://arxiv.org/abs/2606.30749

## Summary

The research team proposes pretraining the low-level controller of a hierarchical imitation learning framework with large-scale dexterous grasp data, then fine-tuning it on downstream task demonstrations to support functional dexterity in articulated tool use. They built a 355k-trajectory grasp-pretraining dataset from large-scale dexterous grasp annotations and introduced DexCraft, a simulation benchmark with six articulated tool-use tasks. In simulation and real-world experiments, the method outperforms end-to-end diffusion policy baselines and hierarchical policies trained from scratch, improving real-world full-task success by 33.3 percentage points over DP3.