China's Robotics Data Infrastructure Expansion
当地方政府成为机器人的第一大客户
China has established over 70 training fields for embodied AI, with additional projects in planning, driven by government policies and industry investment. These centers aim to generate high-quality data for robot training, but face challenges such as data quality, sustainability, and market dynamics. The article explores both successful initiatives and failed projects, highlighting the evolving landscape of data collection and its role in advancing robotics.
The article highlights the rapid expansion of training fields and data collection centers in China for embodied AI, emphasizing the scale of infrastructure investment and the challenges of data quality and sustainability. It contrasts successful models like OpenLET with failed projects, illustrating the complexities of building a viable data ecosystem.
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.
Reported numbers
training_field_count
>70
View original evidence
关于训练场的地理学 截至 2026 年 6 月底，全国已建成启用 超过 70 家 具身智能训练场，在建或规划中的还有 46 家 ，覆盖全国 18 个省级行政区 。
Open source S17training_field_area
≈5,000
View original evidence
落在18个省级行政区的训练场 上海张江·麒麟训练场 2026年初投用，总建筑面积约 5000 平方米，搭建高端制造、民生服务、特种作业、家居家政、商业服务、仓储物流等 10 大类真实应用场景，可同时容纳上百台 异构人形机器人 并行实训。
Open source S18data_set_duration
60,000 minutes
View original evidence
同期发布的"白虎"数据集总时长超 60,000 分钟，约 9,072 万对真实物体接触样本，覆盖 380 余项典型任务、500 多种日常物体。
Open source S19data_download
40,000
- dataset: 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.
一座五千平方米的训练场，一百多台机器人来自十几个不同的品牌，高矮胖瘦各不相同。
Open source S3
大家每天的工作，是把一个动作重复五百次以上。
Open source S6
每一个场景都需要上百万条准确的数据，单个采集师要这样干满约两百天，一个动作要重复一万次以上。
Open source S7
这些年轻人生产的是数据。
Open source S8
关于训练场的地理学 截至 2026 年 6 月底，全国已建成启用 超过 70 家 具身智能训练场，在建或规划中的还有 46 家 ，覆盖全国 18 个省级行政区 。
Open source S17
落在18个省级行政区的训练场 上海张江·麒麟训练场 2026年初投用，总建筑面积约 5000 平方米，搭建高端制造、民生服务、特种作业、家居家政、商业服务、仓储物流等 10 大类真实应用场景，可同时容纳上百台 异构人形机器人 并行实训。
Open source S18
同期发布的"白虎"数据集总时长超 60,000 分钟，约 9,072 万对真实物体接触样本，覆盖 380 余项典型任务、500 多种日常物体。
Open source S19
首批 6000 分钟核心数据上线 OpenLoong 开源社区后，单平台单日下载量突破 4 万次。
Open source S20
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.
- Compare the reported units and scope before using these quantities in a budget. Recording hours, sensor-hours and trajectories are different measures.
- 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 · news.qq.com