Humanoid robots, widely recognized as one of the most promising carriers of artificial intelligence, are moving rapidly from the lab into everyday life and industry.
To accelerate this transition, a large-scale Humanoid Robotics Data Training Center has officially been launched in Beijing, creating an innovative hub that unites core technology R&D, scenario-based application testing, operator training, and ecosystem collaboration.
As a core technology and equipment provider, RealMan Robotics plays a central role in both the deployment and daily operations of the center.
A world-class robotics training facility
Spanning 3,000 square meters, the center is divided into a training zone and an application zone, with 108 robots of diverse forms already deployed. These include embodied dual-arm lifting robots, wheeled humanoids, drone-arms, and quadruped robotic platforms.
To ensure data quality and scenario realism, the center has constructed ten real-world environments – including eldercare and rehabilitation, special operations, new retail, automotive assembly, and smart catering.
Together, these scenarios support large-scale multimodal data generation, producing an estimated over one million high-quality data points annually for training advanced AI models.
Tackling industry bottlenecks
The center addresses three fundamental pain points in robotics:
- Lack of cross-scenario data generalization
- Significant gaps between simulation and real-world conditions
- Absence of standardized data formats and efficient closed-loop iteration
By creating a full-stack data pipeline – from collection and training to validation and deployment – the center aims to accelerate the commercialization of humanoid robotics and embodied AI.
Open day insights: The ‘endgame’ of robotics
At the center’s Open Day, Eric Zheng, director of the Humanoid Robotics Data Training Center, delivered a keynote titled “Exploring the Endgame of Robotics”.
Zheng said: “Robots face three enduring bottlenecks before they can scale into everyday life: operational capability, generalization, and cost efficiency.
“Traditional industrial arms are heavy and expensive, service robots remain too simplistic, and most lack the adaptability of humans in complex environments. Long deployment cycles and poor scenario adaptability – combined with high costs – continue to limit adoption.”
He emphasized that solving these challenges requires both breakthroughs in robot design and large-scale real-world data generation, fueling models that enable flexible and affordable deployment.
RealMan’s new initiative: RealBOT open platform
In response, RealMan unveiled the RealBOT Embodied Intelligence Open Platform, designed for high-quality data acquisition. By deeply integrating with remote teleoperation systems, the platform creates new paradigms of human-robot collaboration.
This marks a key step in robotics evolving from “reliant on humans” to “assisting humans”, and finally to “empowering and liberating humans”.
Toward a global robotics ecosystem
Looking forward, the training center will expand industry-academia collaboration, mobilize ecosystem resources, and foster a culture of technology co-creation, data sharing, and business co-growth. These efforts aim to accelerate the global adoption of humanoid robotics and promote sustainable, high-quality industry development.
