Venture funding to robotics startups has soared in 2026, with the bulk of investment going to companies based in China and the U.S., Crunchbase data shows. All told, global venture funding to robotics startups totaled $9.9 billion in Q3, more than double the $4.3 billion invested in Q3 2025, per Crunchbase data 1.
It was the latest in a run of quarters with nearly $10 billion or more in funding. Funding to the robotics sector in Q1 through Q3 2026 is up around 185% year over year.
China and the US lead
The bulk of robotics funding this year has been in China, with $13.2 billion invested, and the U.S., with $12.1 billion. Germany, the third-largest recipient of robotics startup funding, trails with $1.7 billion invested.
The largest rounds in China went to Guangzhou-based Xpeng Robotics, a builder of AI models and physical robots that raised $900 million, and Shenzhen’s AI² Robotics, which is working to build intelligent robots for manufacturing, healthcare and services and raised a $736 million Series C round.
In the U.S., billion-dollar rounds have also been raised this year by companies including Travis Kalanick’s Los Angeles-based Atoms — which includes its ghost kitchen business, and divisions for robotics in mining and transport — and Pittsburgh-based Skild AI, which raised $1.4 billion for its robotics foundation model Skild Brain.
Another notable round this year went to Germany-based Neura Robotics, which raised $1.4 billion for its cognitive robots, with AI and data infrastructure to build intelligence.
Building out the data and model layer
“We’re just seeing physical AI take off,” Ulrik Stig Hansen, co-CEO of San Francisco-based Encord, a provider of the data layer for physical AI, told Crunchbase News at its inaugural Long Horizon Physical AI Summit in San Francisco earlier this month.
The compute and storage capabilities are being developed to support these systems, he noted, but building for the physical world takes time, especially compared to large language models trained on the vast troves of text on the internet. “Physical AI is very different because there is no internet of physical AI data, and so the data first has to be collected, and you have to convert it from sensor tokens to action tokens,” he said.
Data sets are orders of magnitude larger for physical AI, requiring multimodal data combining vision, tactile, force and torque. “Storing all that data, curating all that data, enriching all that data, and validating that all the data works for these systems is a very expensive operation,” said Hansen.
We are still in the pre-training phase of physical AI, but will soon be entering the post-training phase, he noted.
More winners
Around 75 robotics companies on the unicorn board have raised funding in the past three years. Of these, more than half — 45 — joined the board just this year. Among the most highly valued robotics startups, many competing companies are building data and models, as well as varied vertical use cases in heavy industry, manufacturing, logistics and household and use cases among others.
Robotics funding is surging and new unicorns are emerging, but the sector’s direction remains uncertain as companies race toward further breakthroughs over the next year.
“There are a lot of companies that are raising capital, and I think a lot of them are going to win, just because there’s so many different types of applications to the physical world,” said Hansen.
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Illustration: Dom Guzman
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