Teaching Robots to Work: China's Embodied Intelligence Data Collection and Training Ecosystem
Overview
RoboMIND开源打破数据壁垒，推动具身智能发展。高质量数据成为核心燃料，解决数据稀缺、格式不统一等问题。数据生态逐步标准化，助力机器人迭代升级。","latest":"RoboMIND开源后全球下载量突破2000万次，推动数据生态标准化，加速具身智能发展。"}
Generated from attributed reports · Updated 49 minutes ago
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
Environment: controlled real
“在这个占地近6000平方米的基地里，家居、商超、工业装配、化学实验室、康养护理等模拟实景分区排布，构成一座面向人形机器人的“实景实训工厂”，源源不断产出高质量数据。”
Exact source · revision 2Source owner not reported
Reported quantity · data_hours: 30000 hours · Basis not reported
“目前，基地已对外交付近3万小时高质量数据，并打通了从数据采集、清洗、质检、标注到模型训练、真机评测、模型部署、数据回流的完整闭环链路。”
Exact source · revision 2Source owner not reported
“目前，基地已对外交付近3万小时高质量数据，并打通了从数据采集、清洗、质检、标注到模型训练、真机评测、模型部署、数据回流的完整闭环链路。”
Exact source · revision 5Source owner not reported
Reported quantity · data_downloads: 20000000 other · Basis not reported
“2025年12月，北京人形面向全球开发者开源开放具身智能数据集RoboMIND，在一个月内全球下载量实现翻倍增长，目前全球下载量已突破2000万次。”
Exact source · revision 2Source owner not reported
Reported quantity · training_fields_area: 200 other · Basis not reported
“基地不仅搭建了模拟实景，还建设了约200平方米的专业光学动作捕捉场地，为机器人的拟人化动作提供了高精度的采集环境。”
Exact source · revision 2Source owner not reported
Reported quantity · data_hours_produced: 30000 hours · Basis not reported
“目前，基地已对外交付近3万小时高质量数据，并打通了从数据采集、清洗、质检、标注到模型训练、真机评测、模型部署、数据回流的完整闭环链路。”
Exact source · revision 2Source owner not reported
Reported quantity · data_hours_global: 30000 hours · Basis not reported
“目前，基地已对外交付近3万小时高质量数据，并打通了从数据采集、清洗、质检、标注到模型训练、真机评测、模型部署、数据回流的完整闭环链路。”
Exact source · revision 2Source owner not reported
Reported quantity · training_centers: 70 other · Basis not reported
“截至今年6月底，全国共建成启用超过70家具身智能训练场，在建或规划中的训练场有40多家。”
Exact source · revision 2Source owner not reported
Reported quantity · training_hours: 30000 hours · Basis not reported
“目前，基地已对外交付近3万小时高质量数据，并打通了从数据采集、清洗、质检、标注到模型训练、真机评测、模型部署、数据回流的完整闭环链路。”
Exact source · revision 5Source owner not reported
Reported quantity · data_download: 20000000 other · Basis not reported
“2025年12月，北京人形面向全球开发者开源开放具身智能数据集RoboMIND，在一个月内全球下载量实现翻倍增长，目前全球下载量已突破2000万次。”
Exact source · revision 5Source owner not reported
Reported quantity · Reported duration: 1000 hours · Basis not reported
“在该公司与乐聚智能合作部署的车间内，15台“夸父”人形机器人已投入常态化上料作业，经过一年磨合，累计运行超过约1000小时，完成超6万件零件生产，作业成功率稳定在98%以上。”
Exact source · revision 2Source owner not reported
Reported quantity · pieces: 60000 other · Basis not reported · Differing source assertions
“在该公司与乐聚智能合作部署的车间内，15台“夸父”人形机器人已投入常态化上料作业，经过一年磨合，累计运行超过约1000小时，完成超6万件零件生产，作业成功率稳定在98%以上。”
Exact source · revision 2Source owner not reported
Reported quantity · Reported success rate: 98 percent · Basis not reported
“在该公司与乐聚智能合作部署的车间内，15台“夸父”人形机器人已投入常态化上料作业，经过一年磨合，累计运行超过约1000小时，完成超6万件零件生产，作业成功率稳定在98%以上。”
Exact source · revision 2Source owner not reported
Reported quantity · seconds: 35 other · Basis not reported · Differing source assertions
“不过，财联社记者在车间看到，夸父机器人单次上料耗时35至40秒，而产线熟练工人上料仅需约15秒；与此同时，此次上岗的15台机器人全部采用“轮式底盘+人形双臂”构型。”
Exact source · revision 2Source owner not reported
Reported quantity · seconds: 15 other · Basis not reported · Differing source assertions
“不过，财联社记者在车间看到，夸父机器人单次上料耗时35至40秒，而产线熟练工人上料仅需约15秒；与此同时，此次上岗的15台机器人全部采用“轮式底盘+人形双臂”构型。”
Exact source · revision 2Source owner not reported
Reported quantity · pieces: 250 other · Basis not reported · Differing source assertions
“以兆丰股份为例，该公司总经理孔辰寰对财联社记者表示，固定产线适用于大批量、单一品种生产，而公司部分海外售后订单属小批量、多品种，最小起订量仅250至300套，对高频换产诉求极高，人形机器人能弥补传统刚性连线的不足。”
Exact source · revision 2Source owner not reported
Reported quantity · seconds: 15 other · Basis not reported · Differing source assertions
“乐聚智能CEO常琳对财联社记者表示，目前机器人的准确度和 平均无故障工作时间（MTBF） 均已达标，下一步是将单件上料时间压缩至与生产节拍相匹配的15秒。”
Exact source · revision 2Source owner not reported
Developments
- 2026-10-08 23:31 UTC · 2 reportsA Tutorial on Data-Driven Embodied Intelligence: Training Robots with Real-World DataRobotics — Chinese web discovery：A Tutorial on Data-Driven Embodied Intelligence: Training Robots with Real-World Data
- 2026-10-06 01:43 UTC · 1 reportsEvent updateChinese robotics — Dataset and collection discovery：Teaching Robots to Work: China's Embodied Intelligence Data Collection and Training Ecosystem
Report timeline
Follow attributed reports and material updates.
- Chinese robotics — Hardware and sensingSignalHumanoid Robots in Production Lines: Real-World Data Drives Model Evolution
The article reports on the deployment of 15 'KuaFu' humanoid robots in a factory for material handling tasks, achieving over 98% success rate after one year of operation. It explores the challenges of integrating humanoid robots into industrial settings, the role of real-world data in improving embodied models, and the strategic importance of data sharing and open-source initiatives in advancing the field.
- Chinese robotics — Dataset and collection discoverySignalA Practical Guide to Data Collection and Utilization in Embodied Intelligence
The article outlines the operations of a humanoid robot training center that generates high-quality data for embodied intelligence applications. It details the data collection process, the role of open-source datasets like RoboMIND, and the importance of standardized, high-value data in driving the development of autonomous robotic systems.
- Robotics — Chinese web discoverySignalA Tutorial on Data-Driven Embodied Intelligence: Training Robots with Real-World Data
The article describes the process of collecting and processing high-quality data for training humanoid robots, including simulation environments, optical motion capture, and data standardization. It highlights the importance of real-world data in enabling robots to learn and adapt, and discusses the role of open-source data sets like RoboMIND in accelerating the development of embodied intelligence.
- Robotics — Chinese web discoverySignalThe 'Meituan' of Embodied Intelligence: Can It Work?
The article discusses MeFeng Technology's launch of MeFeng Pai, a crowdsourcing platform for physical AI data collection. It examines the challenges of scaling data collection for complex tasks, the economic viability of such platforms, and the broader industry context of data collection in robotics. The article compares MeFeng's approach with Figure AI's Index platform and Comma.ai's past attempts, highlighting the ongoing uncertainty and challenges in this space.
- Chinese robotics — Dataset and collection discoverySignalTeaching Robots to Work: China's Embodied Intelligence Data Collection and Training Ecosystem
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.
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