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Humanoid robots face two linked hurdles: they must work reliably beyond carefully controlled demonstrations, and the companies building them need affordable, dependable supplies of the parts that make this possible. China has scale and dense manufacturing networks in several relevant industries; US and allied suppliers remain important in areas such as AI chips, simulation and some high-precision components. Trade tensions can make those cross-border dependencies costlier and less predictable, but they do not establish a single winner—or prove that either ecosystem can yet deliver broadly capable humanoids at scale.
What is holding humanoid robots back?
The central technical challenge is not simply making a robot walk. A useful humanoid must perceive a changing environment, manipulate objects, recover from unexpected situations and complete tasks safely at a pace and cost that make sense in a real workplace. It must also fit into existing operations rather than require a workflow built around a fragile pilot.
Autonomy, dexterity and adaptation
In its January 2026 assessment, Gartner identifies dexterity, intelligence and adaptability in unstructured settings, compatibility with established workflows, upfront and maintenance costs, and battery life as major adoption barriers. Gartner analyst Abdil Tunca described the technology as immature and not yet meeting expectations for versatility and cost-effectiveness. That is Gartner’s assessment, not a measured verdict on every product or task.
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The hand is a compact system-level problem
Human-like hands combine many degrees of freedom with sensitive tactile feedback. McKinsey’s 2026 analysis describes a human hand as having more than 20 degrees of freedom. It gives Tesla Optimus as an example in which the hands contain more than 50 actuators, compared with roughly 25–30 across the rest of the body. Those figures illustrate the engineering burden in that example; they are not a specification for every humanoid.
Fitting many actuators and sensors into a small space creates competing demands for power, sensing resolution, heat management and low-latency control. A hand that can move is not necessarily a hand that can reliably identify, grip and manipulate varied objects in a production environment.
Battery life, cost and workflow integration
Battery capacity constrains operating time, while charging, battery changes or downtime affect useful uptime. A robot’s economics also depend on more than its purchase price: maintenance, supervision, integration, throughput and safety all matter. A controlled pilot may show that a task can be performed, but it does not by itself establish reliable high-throughput operation in a warehouse or factory.
Gartner forecast in January 2026 that fewer than 20 companies would reach production for humanoid manufacturing or supply-chain use cases by 2028, mostly in controlled environments. This is a dated analyst forecast, not a confirmed count or a guarantee about what will happen.
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Why actuators and other components matter to cost
McKinsey’s 2026 estimates put actuators at 40–60% of a humanoid robot’s bill of materials, making them a particularly important cost and performance lever. Its estimates for five major hardware areas are shown below. These are McKinsey estimates, not audited industry-wide cost accounting; component shares will depend on the robot’s design and configuration.
| Hardware area | Estimated share | Source and qualification |
|---|---|---|
| Actuators | 40–60% of bill of materials | McKinsey, 2026 estimate |
| Sensing and perception | 10–20% | McKinsey, 2026 estimate |
| Compute and control | 10–15% | McKinsey, 2026 estimate |
| Structural components | 5–10% | McKinsey, 2026 estimate |
| Battery modules | 5–10% | McKinsey, 2026 estimate |
McKinsey estimates these five areas together account for 85–90% of unit cost. That concentration helps explain why actuator performance, supplier capacity and component access can influence both the robot’s capabilities and the cost of making it. It also means a low quoted price for a prototype does not establish the cost of a dependable system at production volume.
Where US-China tensions intersect with the supply chain
Humanoid manufacturing draws on industries that are already international. A robot may rely on motors, precision bearings, magnets, batteries, sensors, power electronics, AI chips and software from different suppliers and countries. That creates interdependence: manufacturing scale in one area does not guarantee access to every other critical component.
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China’s manufacturing and supplier strengths
McKinsey’s 2026 analysis attributes China’s position to proximity to electric-vehicle and electromechanical manufacturing, supplier reuse, process transfer, competition among suppliers and industrial clusters. It reports that China accounts for 90% of global permanent-magnet processing, 40% of precision bearings, 35% of motors and 30% of power electronics. These are McKinsey’s figures for the component categories it names, not a complete scorecard of humanoid production capacity.
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Industrial robot figures also illustrate the scale of China’s broader automation sector, but they must not be mistaken for humanoid shipments. Citing the International Federation of Robotics’ World Robotics 2025 release, McKinsey reports that China installed 295,000 new industrial robots in 2024 and had an operational stock of about 2.03 million, representing roughly 54% of global industrial-robot deployments that year.
US and allied positions—and dependencies
DSET’s August 2026 summary says China still depends on the United States, Taiwan and other partners for AI chips, simulation software and some high-precision components. It reports that Western producers make over 90% of high-end planetary screws and 70% of high-end coreless motors. DSET also says Chinese firms are moving up the value chain and designing around the need for the highest-precision parts. These are DSET’s reported findings, not an independently audited census of every supplier.
The same supply chains run in the other direction. DSET identifies allied dependence on China for permanent magnets and for upstream battery materials and processing. Taiwan, in DSET’s account, could contribute contract manufacturing, precision parts, machine tools, control and vision modules, and actuator components to non-China supply chains. Building a resilient alternative would still require manufacturing scale and cooperation; identifying potential capacity does not show that it can be created quickly or at equivalent cost.
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What trade frictions change
Export restrictions, tariffs and policy uncertainty can complicate sourcing and raise cost or delivery risk when a robot depends on components crossing borders. In May 2025, the Associated Press reported concerns over tariffs and China’s rare-earth magnet export restrictions. Agility Robotics CTO Pras Velagapudi told AP the situation had added “some inconveniences” to the company’s supply chain while also opening opportunities. His comment describes one company’s experience; it does not quantify the policy impact across the sector or establish current terms for every supplier.
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- AI Large Model ChatGPT Integration for Enhanced User-Machine Interaction. TonyPi incorporates a multimodal model, with ChatGPT at the core of its interaction system. With AI vision and voice integration, TonyPi excels in perception, reasoning, and action, enabling advanced embodied AI applications and delivering a seamless, intuitive human-machine interaction experience!
- AI Voice Command & Recognition. Equipped with Large Language Models, TonyPi accurately understands voice commands, analyzes visual scenes in its field of view, and carries out appropriate actions—enabling smooth and responsive voice interaction.
- AI Vision Recognition and Tracking. TonyPi's 2DOF head is fitted with an HD camera that provides a wide field of view. It supports a range of AI vision capabilities, including color recognition, target tracking, ball kicking, line following, and MediaPipe-based motion control for interactive AI applications.
- Comprehensive Learning Resources. TonyPi offers abundant educational content, including resources on robotic motion control, OpenCV, deep learning, MediaPipe, AI large models, voice interaction, and sensor applications. We provide extensive learning materials and tutorials to guide you from foundational concepts to advanced practices, helping you develop your AI humanoid robot.
The practical effect is exposure to uncertainty, not proof that production has stopped or that a particular country can replace every affected input. A supplier’s location, component quality, production yield, lead time and available alternatives all matter alongside headline national shares.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to compare the US and Chinese humanoid ecosystems
No single comparable US-China scorecard across autonomy, cost, production quality and verified deployments is established by the sources discussed here. A useful comparison should specify the robot, task, production volume and date rather than use one shipment estimate or component statistic as a proxy for overall leadership.
| Comparison dimension | What to examine |
|---|---|
| Autonomy | Whether the robot completes tasks in unfamiliar, changing conditions and recovers from unexpected situations |
| Manipulation | Hand dexterity, tactile sensing and success across varied objects and tasks |
| Components | Actuator and precision-part quality, cost, yield, capacity and supplier concentration |
| Power and uptime | Operating time, recharge strategy, maintenance and actual availability for work |
| Compute and control | Access to AI chips, simulation tools and control systems, including dependence on cross-border suppliers |
| Economics | Unit cost for a stated configuration and production volume, plus integration and maintenance costs |
| Deployment | Throughput, safety, workflow fit and verified customer use beyond a tightly controlled pilot |
| Resilience | Production scale, alternative suppliers and exposure to trade restrictions or concentrated sources |
China’s industrial-robot installation totals are evidence about its broader automation base, not a count of humanoids. Likewise, a component market share does not establish that a supplier can deliver every humanoid-specific part at the required quality, yield and price. Treat claims about capability and scale as distinct until they are demonstrated together in customer workflows.
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