Japan Pioneered Humanoid Robots—Can It Now Catch China?

2026-07-04 · Source: IEEE Spectrum · Field: Technology & Digital — Robotics & Autonomous Systems, Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, medium

Summary

At the recent Humanoids Summit in Tokyo, Chinese humanoid robots significantly outnumbered Japanese systems three to one, highlighting Japan's ceded leadership in a field it pioneered. While Japan's Geminoid HI-6, a 20-year-old android equipped with an LLM, demonstrated advanced conversational skills, most full-scale humanoids on display were Chinese, including Booster Robotics' K1 and Unitree Robotics' G1, which sells for US \$16,000. Japanese firms like Omakase Robotics and GMO AI & Robotics are even using modified G1 bots for demonstrations and cargo handling trials at Haneda airport. This contrasts with Japan's historical focus on expensive, uncommercialized technology demonstrations like WABOT-1 and Asimo. Japan's industrial robot density has also fallen to fifth globally in 2024, with China now having 2 million operational units. Experts suggest Japan has a US \$100 billion opportunity in general-purpose robotics, requiring a strategic shift towards AI, software, and collaborative data ecosystems.

Key takeaway

For Directors of AI/ML or Robotics Engineers aiming to establish or regain market leadership, you must prioritize commercialization and scale in AI-driven robotics. Shift your strategy from expensive technology demonstrations to developing practical, cost-effective general-purpose robots. Actively participate in collaborative data ecosystems and invest in software and AI platforms to secure a competitive baseline, avoiding the pitfalls of siloed development that hindered Japan's early lead.

Key insights

Japan, once a humanoid robotics pioneer, has lost its lead to China due to commercialization failures and a lack of focus on AI and data.

Principles

• Commercialization is key for robotics leadership.
• Scale in data, computing, and talent is critical for AI.
• Collaboration fosters competitive ecosystems.

Method

AIRoA collects extensive mobile manipulator data (80,000 hours) to build and verify Vision-Language-Action (VLA) models, advocating for a shared, pre-competitive data infrastructure and foundation model for industry-wide cooperation.

In practice

• Adopt general-purpose robotics strategies.
• Invest in AI, software, and data platforms.
• Form industry-wide data collaboration.

Topics

• Humanoid Robotics
• AI Robotics
• Robotics Commercialization
• Data Ecosystems
• General-Purpose Robots
• Industrial Automation

Best for: Investor, Entrepreneur, Robotics Engineer, Director of AI/ML, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by IEEE Spectrum.