# Open X-Embodiment and RT-X: A Practical Guide to Cross-Embodiment Transfer for Large-Model Robot Policies

- Source: 古月居 · 微信公众号
- Published: 2026-10-30T09:20:00.000Z
- RoboHot: https://robohot.news/en/items/nl3zwf28tgnml1zvkzjybxj5g
- Original: https://mp.weixin.qq.com/s?__biz=MzU1NjEwMTY0Mw==&mid=2247622373&idx=1&sn=6f1213b0258734753f6b522c865ec400&chksm=fa147e9e056ee67d03b4489a3d8d7078d027b9a11fc32d5cceb1142d956475a6d5a0ee20d522&scene=126&sessionid=1793358027#rd

## Summary

This article provides a systematic walkthrough of cross-embodiment transfer practice with Open X-Embodiment and RT-X, covering RLDS data-format unification, the RT-X model architecture, pretraining, fine-tuning, and deployment on new robots. It presents RLDS conversion scripts, a PyTorch implementation of an RT-1-based model, and training techniques such as temperature sampling and embodiment-weighted loss, and it documents six categories of pitfalls, including slow data loading, poor cross-embodiment performance, and action-space mismatch, along with corresponding solutions.