# OneDemo: Learning policies and generating data from a single demonstration

- Source: arXiv cs.RO
- Published: 2026-10-27T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/pkwrlir3xytvnvl23g57g7448
- Original: https://arxiv.org/abs/2610.18188

## Summary

OneDemo proposes a reinforcement learning framework that edits a single successful demonstration into trajectories suited to new task configurations; the learned editor serves both as a task policy and as a reusable demonstration generator. On 15 Meta-World tasks, it reaches a 92.7% success rate using an average of 53.7k environment interactions; on 9 DexMimicGen tasks, it generates demonstrations with an average success rate of 98.4%, and BC-RNN policies trained on the generated data reach an average success rate of 99.6% at the same data scale.