Key Takeaways
- • Global venture funding to robotics startups totaled $9.9 billion in Q3 2026, more than double the $4.3 billion invested in Q3 2025, according to Crunchbase data.
- • Funding to robotics startups in Q1 through Q3 2026 is up around 185% year over year, with China ($13.2 billion) and the U.S. ($12.1 billion) leading year-to-date investment.
- • Germany ranks third with $1.7 billion invested in robotics startups this year, per Crunchbase.
- • Large rounds include Xpeng Robotics ($900 million) and AI² Robotics ($736 million Series C) in China, and Skild AI ($1.4 billion) and Atoms in the U.S., with Neura Robotics raising $1.4 billion in Germany.
- • Of roughly 75 robotics companies on Crunchbase's unicorn board that raised funding in the past three years, 45 joined this year.
Summary
Venture funding to robotics startups has surged in 2026, with the bulk of capital flowing to companies based in China and the United States, according to Crunchbase data. Global robotics funding totaled $9.9 billion in the third quarter, more than double the $4.3 billion invested in Q3 2025. The Q3 figure was the latest in a run of quarters with nearly $10 billion or more in funding. Year to date through Q3 2026, robotics funding is up around 185% year over year.
China has attracted $13.2 billion in robotics startup investment this year, while the U.S. has received $12.1 billion. Germany, the third-largest recipient, trails with $1.7 billion. The largest Chinese rounds went to Guangzhou-based Xpeng Robotics, which raised $900 million for AI models and physical robots, and Shenzhen-based AI² Robotics, which raised a $736 million Series C to build robots for manufacturing, healthcare and services. In the U.S., billion-dollar rounds this year included Travis Kalanick's Los Angeles-based Atoms, which includes its ghost kitchen business and robotics divisions in mining and transport, and Pittsburgh-based Skild AI, which raised $1.4 billion for its Skild Brain robotics foundation model. Germany-based Neura Robotics raised $1.4 billion for cognitive robots.
At Crunchbase News' inaugural Long Horizon Physical AI Summit in San Francisco, Ulrik Stig Hansen, co-CEO of San Francisco-based Encord, which provides the data layer for physical AI, said the sector is "taking off." He noted that physical AI lacks an internet-scale corpus of data, so data must first be collected and converted from sensor tokens to action tokens. Datasets are orders of magnitude larger than for large language models, requiring combined vision, tactile, force and torque data, which Hansen described as very expensive to store, curate and validate. He said the field is still in its pre-training phase and will soon move to post-training.
Roughly 75 robotics companies on the unicorn board have raised funding in the past three years, and 45 of them joined this year. Many of the most highly valued companies are building data and models or pursuing vertical use cases in heavy industry, manufacturing, logistics and household applications. Crunchbase notes the sector's direction remains uncertain as companies race toward further breakthroughs over the next year.
China has attracted $13.2 billion in robotics startup investment this year, while the U.S. has received $12.1 billion. Germany, the third-largest recipient, trails with $1.7 billion. The largest Chinese rounds went to Guangzhou-based Xpeng Robotics, which raised $900 million for AI models and physical robots, and Shenzhen-based AI² Robotics, which raised a $736 million Series C to build robots for manufacturing, healthcare and services. In the U.S., billion-dollar rounds this year included Travis Kalanick's Los Angeles-based Atoms, which includes its ghost kitchen business and robotics divisions in mining and transport, and Pittsburgh-based Skild AI, which raised $1.4 billion for its Skild Brain robotics foundation model. Germany-based Neura Robotics raised $1.4 billion for cognitive robots.
At Crunchbase News' inaugural Long Horizon Physical AI Summit in San Francisco, Ulrik Stig Hansen, co-CEO of San Francisco-based Encord, which provides the data layer for physical AI, said the sector is "taking off." He noted that physical AI lacks an internet-scale corpus of data, so data must first be collected and converted from sensor tokens to action tokens. Datasets are orders of magnitude larger than for large language models, requiring combined vision, tactile, force and torque data, which Hansen described as very expensive to store, curate and validate. He said the field is still in its pre-training phase and will soon move to post-training.
Roughly 75 robotics companies on the unicorn board have raised funding in the past three years, and 45 of them joined this year. Many of the most highly valued companies are building data and models or pursuing vertical use cases in heavy industry, manufacturing, logistics and household applications. Crunchbase notes the sector's direction remains uncertain as companies race toward further breakthroughs over the next year.
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