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Humanoid Robotics, 2025 - Market Trends, Critical Components & Strategic Shifts
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DIGITIMES believes that due to the high cost of hardware components, humanoid robots can hardly see rapid adoption across various industries within the next 3-5 years and will primarily focus on specific application scenarios. It will not be until after 2029, with advancements in technology and economies of scale, that humanoid robots with bipedal mobility and dual-arm high-degree-of-freedom hand structures may experience more significant growth in scale.

Global demand for robots has been driven by multiple factors, including labor shortages and rising costs, the advancement of Industry 4.0, and the integration of AI technologies. In particular, humanoid robot development has historically been constrained by high costs due to technological limitations. Despite continued R&D investment by some companies, humanoid robots have struggled to achieve large-scale commercialization. However, with significant advancements in AI applications in recent years, substantial capital and talent have poured into the commercial humanoid robot sector. DIGITIMES estimates that humanoid robots will account for only 0.2%of the projected US$8.8 billion robot market in 2025, but their share is expected to surge to 0.8% by 2026.

DIGITIMES defines humanoid robots in two types and two development stages. From 2025 to 2028, the global robotics industry will evolve beyond mature industrial and service robots towards robots with wheeled mobility equipped with single or dual arms featuring grippers or suction nozzles for object handling. This can be considered as "Humanoid Version 0.5," primarily aimed at performing simple tasks in specific environments. However, since the cost of humanoid robots currently far exceeds that of industrial robots with comparable capabilities, manufacturers find it difficult to afford large-scale adoption of humanoid robots. Consequently, the number of humanoid robots deployed during this period remains limited, making the reduction of component costs a key challenge for the development of humanoid robots at this stage.

DIGITIMES estimates that after 2029, advancements in technology and economies of scale will significantly reduce the cost of modules for bipedal mobility and dual-arm high-degree-of-freedom hand structures, making humanoid robots enter a stage suitable for mass production. Robots in this "Humanoid Version 1.0" phase will feature complete configurations including bipedal mobility and dual arms equipped with dexterous hands, enabling them to perform more complex tasks. This development is expected to accelerate the adoption of humanoid robots, expanding their applications from industrial settings to service-oriented environments and other scenarios. As scenarios involving collaboration and interaction with humans increase, the development of humanoid robots will need to focus not only on hardware and software factors but also on safety regulations as a key consideration.

This research report will explore the development trends of humanoid robots, analyzing developer strategies and application scenarios to uncover the context of industry trends and key challenges. It will delve into issues and challenges in areas such as software (AI), hardware (components), and safety regulations, along with potential solutions. Based on these findings, it will outline short-, mid-, and long-term development trends for the humanoid robot market.

Looking ahead, driven by AI, humanoid robots as part of Physical AI will also significantly impact and transform industries. The core key lies in when it happens, where it originates, and how it unfolds, which leads to clear market goals but a journey filled with uncertainties. These are precisely the central issues explored in this research report.

Table of Contents

Executive summary

Contents

Figure

Chapter 1: Current status of the global robotics market

Chapter 2: Global humanoid robot application directions

Chapter 3: Key software and hardware technology development trends for humanoid robots

Chapter 4: Conclusion

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