Editor's note: The APEC Economic Leaders' Meeting is set to convene in Shenzhen from November 18–19, 2026. Against growing global interest in embodied AI and cross‑border robotics collaboration, CGTN invited Zhou Changjiu, president of RoboCup Asia‑Pacific (RCAP) Confederation and vice‑president of the RoboCup Federation, to share his insights. As co‑founder of the RoboCup Humanoid Soccer League, he draws on decades‑long competition‑driven research experience to analyze opportunities, practical bottlenecks and viable pathways for inclusive cross‑border AI cooperation across the Asia‑Pacific, ahead of the upcoming RCAP Changsha Invitational Tournament in December.

The Asia-Pacific Economic Cooperation (APEC) Economic Leaders' Meeting will take place in Shenzhen, China, on November 18–19, 2026.

As artificial intelligence (AI) reshapes technology and industry worldwide, a key question is how economies can combine their technological capabilities and industrial strengths so that more people can participate in this innovation and benefit from it.

AI is moving beyond the digital realm into the physical world. Embodied AI, particularly humanoid robotics, is advancing from laboratories and competition arenas toward factories and everyday settings. 

But turning technological breakthroughs into practical applications, and individual innovations into international industrial collaboration, remains challenging.

Since its first competition in 1997, RoboCup has spent nearly three decades advancing AI and robotics research through international competition. 

As one of the co-founders of RoboCup's Humanoid Soccer League, I have been deeply involved in developing its international competition framework and fostering cooperation between the global robotics research community and China’s robotics industry.

This experience has convinced me that AI's value depends on both technical progress and the cooperation that puts it to use. Combining different countries' technological strengths and industrial resources can enable more developers to innovate and more sectors to benefit.

Opportunities: Collaborative innovation from the robotics arena to global value chains

Humanoid robot football offers a useful window into this cooperation.

During play, fully autonomous robots must perceive their surroundings, control their movements, make decisions and work together without remote control or human guidance. 

Five-a-side and eleven-a-side matches extend the challenge from individual intelligence to multi-robot coordination and collective intelligence.

In August 2026, a total of 24 international RoboCup teams from 16 countries and regions participated in the RCAP Beijing Masters, held as part of the second World Humanoid Robot Games in Beijing. 

Using humanoid robot platforms supplied by Chinese companies, the teams tested their AI algorithms and systems integration capabilities under common competition rules.

The significance went far beyond the matches. Chinese companies provided robotic hardware and engineering support, while international research teams contributed AI algorithms, software and systems integration expertise. 

Training, testing and competition helped both sides identify technical bottlenecks, improve hardware-software integration and accelerate development.

RCAP is now extending this model from the competition field to industrial applications. The RoboCup Asia-Pacific (RCAP) Changsha Invitational Tournament 2026, scheduled for December 18–20 in Changsha, Hunan Province, will bring together teams from China, Portugal, Brazil, Thailand, Malaysia and Singapore.

The tournament will feature humanoid robots developed by a major Chinese heavy-equipment manufacturer based in the host city, a company whose core businesses include construction and agricultural machinery. 

The company's expansion into humanoid robotics illustrates how established manufacturers can draw on engineering expertise, manufacturing capacity and real-world industrial environments to advance embodied AI. 

Participants will use these robots for training, joint research and international competition, while exploring potential applications in industrial production and household services.

The event aims to connect China's robot platforms and application environments with the global RoboCup developer community and leading industrial enterprises. 

By bringing competition, collaborative research and real-world testing together, it seeks to create a clearer pathway from technical experimentation to practical application.

Industrial testing can also generate valuable operational data. Repeated trials can reveal how variations in lighting, object placement or workflow affect robot performance, helping researchers identify weaknesses and refine their systems. 

For these benefits to extend across borders, partners need clear agreements on data access and reuse, supported by safeguards for security, privacy and intellectual property. 

These arrangements can help turn access to industrial environments into shared opportunities for research and innovation.

China's extensive robotics manufacturing ecosystem, efficient supply chains, rapid engineering iteration and varied applications in smart manufacturing and services offer international researchers valuable opportunities for development and validation. 

In return, Chinese manufacturers can use the diverse AI algorithms, software solutions and technical feedback of global developers to improve their products and software ecosystems.

This two-way exchange demonstrates how hardware, software, AI algorithms and application scenarios can complement one another across global robotics value chains, creating more opportunities for shared innovation.

Barriers: Technical capability alone does not guarantee real-world use

Despite rapid advances in AI and robotics, moving a technology from the laboratory into everyday use remains difficult. 

The obstacles often lie not in the intelligence of the robot itself, but in infrastructure, device interfaces, technical standards and system compatibility.

Consider a simple task: how does a service robot take an elevator? 

Many robots can already navigate autonomously, recognize their surroundings and avoid obstacles. Yet in some commercial buildings in Singapore and elsewhere, elevator control systems offer no usable communication interface for third-party robots. 

A robot may be unable to call an elevator or select a floor digitally, and may instead require an add-on mechanical arm to physically press the buttons.

The contrast is striking: a robot capable of sophisticated autonomous decisions can still be held back by something as basic as an elevator interface.

Of course, elevators are safety-critical systems. Access to their controls must meet requirements for physical safety, cybersecurity and building management. 

Safe integration requires standardized interfaces, appropriate certification and clear access rules. 

Singapore's national standard for data exchange between robots, elevators and automated doors is a step in this direction, though upgrading existing buildings takes time.

Similar problems arise in industrial automation. Robots from different manufacturers often use different communication protocols, software architectures and control systems. 

An AI algorithm that performs well on one platform may need substantial software adaptation, parameter tuning and testing before it can run on another. 

Differences in development tools, operating environments, data-use requirements and intellectual property arrangements can further complicate international joint research and the reuse of research results.

Technical compatibility is only part of the challenge. A robot that performs well in a trial may still require further assessment or approval before deployment in another economy.

Differences in certification requirements, procurement procedures and market access can add time and cost to joint projects. Cooperation therefore needs more than compatible hardware and software. 

It also depends on transparent requirements and coordination among technology providers, regulators and users.

These examples point to a broader lesson: technological sophistication does not automatically translate into practical usability, let alone into benefits that are widely shared. 

A breakthrough in one component does not establish the maturity of an entire system, and success in a laboratory does not guarantee reliable performance in the real world.

Wider adoption therefore depends not only on stronger AI algorithms, but also on interoperability, standardized interfaces, system safety and dependable performance in real operating environments.

Pathways: Making the fruits of AI innovation more accessible worldwide through open cooperation

How can international collaboration lower development barriers and help more countries, companies and researchers participate in AI innovation? RoboCup's nearly three decades of experience offer practical lessons.

Even when teams from different countries work on the same task and use identical hardware, they often choose very different technical approaches. 

Some specialize in motion control, others in computer vision and autonomous decision-making, and still others in software architecture or multi-robot coordination. 

Common rules, shared testing environments and technical exchanges let teams compare, validate and improve these approaches.

At international competitions, I have often witnessed teams compete fiercely on the field and then, after the final whistle, exchange AI algorithms, share experience and sometimes begin long-term research partnerships.

Shared technical goals leave room for different development paths. This approach is consistent with APEC's principles of voluntary cooperation and consensus. 

Economies should be able to exchange experience and choose technologies suited to their own needs, resources and stages of development, rather than follow a single prescribed model. 

Joint research and talent exchanges can support those choices, building capabilities through sustained testing and adaptation.

Three practical priorities follow.

First, build open and interoperable development platforms. Accessible software development kits, simulation tools, standardized interfaces and technical documentation can reduce integration costs and encourage the reuse of algorithms and software modules. 

This allows developers to spend less time on repetitive integration work and more on core technical problems.

Second, make real-world applications the focus of joint R&D. Universities, research institutes and companies from different countries can work on common platforms to develop and validate solutions for smart manufacturing, logistics, public services and home assistance. 

China's robotics supply chains and application scenarios can complement the AI algorithms and software expertise of developers worldwide, accelerating the transition from research to deployment.

Third, strengthen research partnerships and talent exchanges across the Asia-Pacific. Joint laboratories could pair university teams with industrial partners to test robots on shared tasks, while researcher exchanges could provide practical training in deployment and maintenance. 

Participants could take tested methods and engineering experience back to their institutions and adapt them to local needs. International competitions can help initiate these relationships and keep partners working toward shared technical goals.

Wider access to advanced products matters. So does the capacity to develop and adapt the technology behind them. 

Lowering barriers to innovation enables research teams in different countries to contribute according to their strengths and build lasting research and application capabilities. 

Such capacity-building is a gradual, long-term process, not a one-off transfer.

Innovation to deployment: Leveraging China's strengths for shared global innovation

China's growing strengths in robotics manufacturing, supply-chain efficiency and real-world applications are creating new opportunities for AI developers around the world. 

At the same time, the AI algorithms, software and application expertise of international teams are helping Chinese robotics companies improve their technologies.

Moving from innovation to large-scale deployment still requires sustained engineering work, open collaboration and talent development. 

RoboCup's experience shows that competition and cooperation can reinforce each other: shared challenges encourage diverse solutions, while open exchange helps knowledge and technology advance faster.

Connecting China's robotics industry and real-world application environments with the creativity of developers worldwide can lower barriers to innovation, enabling more people to contribute to and benefit from advances in robotics and AI.

The long-term promise of international AI cooperation lies in translating innovation in the competition arena into practical solutions for factories, services and everyday life, delivering tangible benefits across industries and societies.