Xiaomi-Robotics-1: Scaling Vision-Language-Action Models with over 100K Hours of Real-World Trajectories
Year: 2026
Type: preprint
Abstract: We present Xiaomi-Robotics-1, a foundational vision-language-action (VLA) model capable of (1) following diverse language instructions to perform a wide range of mobile manipulation tasks in unseen environments out-of-the-box, and (2) efficiently adapting to novel downstream tasks with minimal fine-tuning data. We propose a two-stage training recipe consisting of pre-training and post-training. During pre-training, we imbue the model with broad and generalizable action-generation capabilities by training on over 100k hours of real-world manipulation trajectories collected via UMI devices. Crucially, we develop a scalable auto-labeling pipeline that annotates trajectory clips with natural languages describing scene state transitions, providing rich and precise conditioning for action learning. During post-training, we aim to align these capabilities with robot embodiments and imperative instructions that humans naturally use to prompt robots. Extensive experiments demonstrate strong scaling behavior. Xiaomi-Robotics-1 consistently improves with increased data scales and model sizes during pre-training. This scaling behavior directly transfers to post-training, where a stronger pre-training model yields better out-of-the-box real-robot performance in unseen environments. Furthermore, Xiaomi-Robotics-1 serves as a strong robot foundation policy that can be efficiently fine-tuned on complex, dexterous tasks with high data efficiency. Across multiple simulation benchmarks, Xiaomi-Robotics-1 outperforms state-of-the-art methods. Notably, it establishes a new state-of-the-art with a 57.4% success rate on RoboCasa365, surpassing the previous best of 46.6%. Furthermore, it achieves an average score of 20.07 on RoboDojo, significantly outperforming the prior state-of-the-art (13.07). Code and model checkpoints will be released. Project page: https://robotics.xiaomi.com/xiaomi-robotics-1.html
Source: arXiv (Cornell University)
Authors: Xiaomi Robotics Team, Guo, Jun, Jin, Piaopiao, Li, Jason, Li, Peiyan, Li, Yingyan, Liu, Futeng, Peng, Wanli, Qin, Optimus, Su, Yifei, Sun, Nan, Sun, Qiao, Suo, Runze, Wang, Heyun, Wang, Yunhong, Wu, Rujie, Xia, Caoyu, Zhang, Lina, Zhao, Jack, Chen, Guoliang, Chen, Wenlong, He, Xinze, Li, Bin, Li, Qing, Li, Zhuorong, Qu, Heng, Song, Wenxuan, Xiang, Diyun, Xie, Yifan, Xu, Peiran, Ye, Hangjun, Ye, Wen, Zhao, Han, Zhou, Quanyun
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7169765232