Teaching Robots to Work: China's Embodied Intelligence Data Collection and Training Ecosystem
教機器人干活，河北這個基地有“數”
The article describes the process of collecting and annotating real-world data for training robots, including first-person and exoskeleton-based data capture methods. It highlights the role of industrial bases and platforms in creating high-quality datasets for robotic training and deployment, as well as the challenges and opportunities in scaling this data-driven approach.
The article provides an overview of how embodied intelligence training data is being collected, annotated, and utilized in China, highlighting the role of industrial bases and platforms in creating high-quality datasets for robotic training and deployment.
Source: Chinese robotics — Dataset and collection discovery · Read original article ↗
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What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
- paper: not_reported
What remains unknown
Dataset licensing and commercial-use rights are not established here.
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
操作員穿上外骨骼設備，或戴上VR頭顯遠程操控機器人，在參照民生服務、居家生活、工業倉儲三大場景搭建的訓練場裡，採集運動軌跡、關節變化、力控信息等數據。
Open source S12
第一視角採回來的數據，要標物體位置、場景信息，還有拿東西、放東西的手部軌跡﹔遙操作採回來的數據，要標關節角度、運動速度，以及抓一個東西該用多大勁兒。
Open source S16
中國信通院發布的《具身智能訓練場研究報告（2026年）》顯示，當前全球可用的高質量真實數據僅為數十萬至百萬小時級，而具身基礎模型要迎來“ChatGPT時刻”至少需要千萬小時級數據。
Open source S8
Implications for data suppliers
RoboSignal interpretation and collection questions, not statements of buyer demand.
- Confirm the required data type and collection setting with the buyer; this source does not establish a complete collection specification.
- Validate demand and acceptance criteria with a buyer before scaling. Publication, popularity and a research result do not establish a purchase commitment.
Source：Chinese robotics — Dataset and collection discovery · he.people.com.cn