Gasgoo Munich- According to Gasgoo Embodied AI, Yanfeng International and the National and Local Co-built Humanoid Robotics Innovation Center officially entered a strategic partnership on October 28. The alliance centers on co-building an embodied AI scenario data center and a training demonstration site for the automotive industry, with deep collaboration spanning data platform setup, training site construction, vertical-scenario solution development, and joint industry standards.
On one side sits a global auto-parts giant; on the other, China's first national-level humanoid robot innovation platform. Their shared aim: pulling embodied AI off the demo stage and putting it to work on real automotive production lines.
Image Source: National and Local Co-built Humanoid Robotics Innovation Center
At the signing ceremony, the two parties exchanged plaques in a mutual accreditation. The National and Local Co-built Humanoid Robotics Innovation Center granted Yanfeng International the plaque for the "National-Local Co-built Humanoid Robot Innovation Center Auto Parts Industry Embodied AI Scenario Data Center and Training Demonstration Site." In return, Yanfeng International awarded the Center the plaque for the "Yanfeng International Automotive Technology Co., Ltd. Embodied AI Auto Parts Industry Application Demonstration Center."
The dual accreditation formalizes a clear division of labor. The National and Local Co-built Humanoid Robotics Innovation Center can fast-track its technological breakthroughs into Yanfeng's manufacturing scenarios for validation and iteration. Yanfeng, meanwhile, feeds its scenario demands and data back into the Center's R&D system—closing the loop from scenario to data, technology, and product.
For a robotics innovation platform, the bottleneck is rarely algorithms—it is access to real, stable industrial settings where systems can be tested repeatedly. For an auto-parts supplier, the gap lies in proprietary robotics and embodied AI tech. This partnership bridges both deficits.
Zang Chungao, general manager of Yanfeng International, argues that automotive and parts manufacturing offers high process standardization, steady production cadences, and clear return-on-investment paths—making it one of the most primed industrial settings for embodied AI to scale.
Yanfeng is already moving to seize the embodied AI opportunity, accelerating its push along a path from data asset accumulation to closed-loop validation in vertical scenarios, and finally to industry solution rollout. Next up: the supplier will fully open its manufacturing scenarios and production-line data resources, working closely with the National and Local Co-built Humanoid Robotics Innovation Center to put the partnership into action.
The National and Local Co-built Humanoid Robotics Innovation Center—jointly licensed by China's Ministry of Industry and Information Technology and the Shanghai municipal government—is the country's first national-level humanoid robot innovation platform. It leads multiple major national and provincial research initiatives, aiming to bridge the innovation, industry, capital, and talent chains to build a unified government-industry-university-research-application ecosystem.
To date, the Center has built the world's first heterogeneous humanoid robot training ground, dubbed "Qilin," using a "1+N" model to link sub-training sites nationwide. It has spearheaded the drafting of over 80 industry and group standards, launched the OpenLoong open-source community for humanoid robots, and established Shanghai's humanoid robot pilot-scale testing platform. That platform offers the entire industry open access to real-machine testing and evaluation, lowering the barrier to R&D.
One side commands the scenarios and industrial muscle; the other holds the full-stack technology and data infrastructure. That complementarity is the bedrock of the alliance.
Over the past two years, the robotics industry has proven what machines can do. It has yet to prove they can do it reliably and cheaply on a live production line.
Automotive manufacturing demands far higher reliability, pacing, and yield than typical settings. Crack the code here, and the gains could spill over into the rest of high-end manufacturing.
