Robotics @ XIAOMI

Xiaomi-Robotics-1 is a ready-to-use robot foundation model trained on over 100K hours of real-world manipulation trajectories.

ReportCodeHuggingfaceModelscopeBreaking the data barrier. Scaling robot policy models with embodiment-free pre-training.

Following the training paradigm of LLMs, the training of Xiaomi-Robotics-1 consists of two stages: pre-training and post-training. The first stage learns general representations for action generation from large-scale UMI data, while the post-training stage aligns the model with real robot embodiments and instruction-following capabilities.

An encouraging finding is that pre-training shows a clean scaling behavior: as data and model size grow, validation action error steadily decreases.

After post-training, Xiaomi-Robotics-1 can be used out-of-the-box to perform a wide range of mobile manipulation tasks in the real world. We evaluate the post-trained model in unseen environments with unseen object instances to understand whether the scaling behaviors from pre-training can transfer to real-robot performance after post-training.