Why China’s humanoid robot sector is dominating the initial market

Why China’s humanoid robot sector is dominating the initial market

China’s humanoid robots captured worldwide interest with kung fu stunts during the nation’s aired Spring Festival Gala, while Chinese smartphone manufacturer Honor is poised to introduce its inaugural humanoid robot at MWC in Spain. 

Robotics has been identified as a key focus in the country’s “Made in China 2025” initiative, originally aimed at factory automation but now shifting towards humanoid robots. Significant advancements in multimodal AI are boosting what is referred to as embodied AI — autonomous machines functioning in real-world settings — a move that officials claim could alleviate labor shortages and enhance productivity. 

At this nascent phase of humanoid robot evolution, Chinese firms are surpassing their U.S. competitors in both speed and production volume, stated Selina Xu, an AI policy lead in Eric Schmidt’s office.

“China boasts a more established hardware supply chain — largely developed through the electric vehicle industry, including sensors and batteries — and the world’s most powerful manufacturing infrastructure, enabling companies to innovate significantly faster than Western counterparts,” Xu informed TechCrunch. 

Consequently, Chinese robots are not only more cost-effective but companies can also launch new models at a quicker pace, Xu observed, noting that top Chinese company Unitree delivered approximately 36 times more units last year than American competitors Figure and Tesla.  

In the previous year, global humanoid robot shipments reached merely 13,317 units, as per a Forbes report released last month. This is a minuscule figure for an industry projected to nearly double every year, reaching 2.6 million units by 2035. (However, caution is necessary when interpreting these figures. The report indicates uncertainty regarding how many units represent actual commercial sales compared to demo units or pilot trials, highlighting the industry’s early-stage status.) 

The leading humanoid robot manufacturers by 2025 shipment volumes were China’s Agibot and Unitree, succeeded by UBTech, Leju Robotics, Engine AI, and Fourier Intelligence, highlighting Beijing’s preliminary supremacy in the field.  

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Recently, the most significant shift has transitioned from “demo-driven enthusiasm” to “operations-driven implementation,” Yuli Zhao, chief strategy officer at Galbot, shared with TechCrunch. Galbot’s humanoid robot, the G1, was showcased at this year’s Spring Festival Gala, China’s yearly state-sponsored lunar New Year’s Eve broadcast, alongside robots from Unitree Robotics, Noetix, and MagicLab. 

“An increasing number of customers are inquiring: Can the robot operate consistently in real-life scenarios and genuinely assist people? This practical demand is reinforced in China, where policy and industrial strategies promote automation upgrades, and the manufacturing environment enables rapid iteration,” Zhao remarked.

While boosted financing for humanoid startups “has certainly accelerated” progress, “the most sustainable adoption occurs when you can demonstrate consistent and reproducible value in production or service settings, rather than just a one-time exhibition,” Zhao added.

Nevertheless, investments are crucial, and Chinese robotics manufacturers are securing them. Last year, Unitree was valued at approximately $3 billion after concluding its Series C, with aspirations of reaching as high as $7 billion in a potential IPO. Concurrently, Galbot has attracted over $300 million in new investments, reportedly elevating its valuation to $3 billion, marking one of the largest funding rounds in China’s humanoid robotics sector to date. 

U.S. firms are also advancing beyond impressive demonstrations to emphasize real-world implementations. Furthermore, they are pursuing their ambitious targets. U.S. startup Foundation intends to develop 50,000 humanoid robots by the end of 2027. 

However, China is already aiming for a combination of budget-friendly mass-market models and premium applications, quickly proliferating humanoids across industrial, consumer, and rehabilitation domains, as highlighted in a December TrendForce report.

Obstacles to China’s dominance

Regarding AI systems and integrated software, the true standing of Chinese humanoid companies remains ambiguous. The industry is fundamentally relying on vision-language-action frameworks and “world models,” yet both technologies are still in their infancy. Nvidia currently dominates this area with its comprehensive humanoid software suite, according to Xu, leading most humanoid startups in China to depend on Nvidia’s Orin chips. Nonetheless, local chip manufacturers are working on developing native alternatives, she noted. 

Yet, humanoid robotics developers are still tackling fundamental issues. The challenge lies in enabling robot foundational models to anticipate the “next physical state” they will encounter in unpredictable settings, similar to how large language models project the next word. Unlike LLMs, however, humanoid robotics firms cannot merely harvest internet data for training, Xu explained. Thus, most are relying on simulated environments to create synthetic data, although gathering real-world data is crucial.

“Due to the data scarcity issue, humanoids are still quite a distance from true autonomy. The hardware is presently ahead of the software — the robot bodies can now manage substantially more dexterity than in the past (although they face reliability issues, as seen when some robots malfunctioned during humanoid marathons), but the cognitive functions remain in the early stages,” the analyst stated. 

Safety is also a major obstacle for humanoid robots. A single high-profile incident could lead to public backlash, and China is likely considering how to swiftly deploy the technology without proceeding too hastily. As the sector matures, stronger regulations are anticipated.

Given the data limitations, Zhao posits that the initial demand for humanoids will likely grow first in relatively controlled work environments.

“Early momentum is expected in industrial manufacturing, warehouse logistics, and retail, where tasks are repetitive, hours are lengthy, and processes are well-defined — generating genuine demand and optimal conditions for humanoid robots to deliver large-scale value,” he stated. 

Additional APAC competitors 

Humanoid robot advancement is not confined to a two-nation competition. Japan’s robotics sector — encompassing startups to semiconductor powerhouses — aims for humanoid mass production by 2027. Long a trailblazer with initiatives like Honda’s Asimo, Murata Manufacturing’s Murata Boy, and SoftBank Robotics’ Pepper, Japan relies on precision and advanced control. A unique area for this country: Humanoid robots are increasingly utilized in eldercare.  

Coral Capital CEO James Riney, who invests in technology firms in Japan, is confident that Tokyo will continue to prosper in the humanoid robotics field. “Three factors are likely to propel the adoption of robotics in Japan. One is the labor shortage and the intent to rely less on mass immigration. The second is the prevalent cultural perception of robots as allies — more Doraemon than Terminator. The third is that Japan already excels in many aspects of the robotics supply chain.”

Hyundai Motor’s Boston Dynamics division unveiled a new Atlas humanoid scheduled for factory use by 2028, aiming to manufacture up to 30,000 units yearly in the U.S. as part of its AI-driven robotics strategy.  

For China, however, government initiatives, industrial strategies, labor deficiencies, and private investments are converging to accelerate the country’s humanoid robotics initiative. 

 “China’s leadership can be best understood as a speed-to-scale advantage,” Zhao remarked. “The ecosystem here compresses the entire cycle — research and development, supply chain, manufacturing, integration, and customer deployment — into a very tight loop. This allows humanoid firms to transition from prototype to real-world deployment more swiftly, learn from actual operations, and iterate at a pace that is challenging to replicate elsewhere.” 

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