Watch eerie video of humanoid robot 'army' marching naturally, thanks to a major AI upgrade
Figure 02's human-like gait is the product of the company's simulated reinforcement learning system, and is just the beginning of its plans to make its robots perform physical tasks more naturally.

A U.S. robotics company has used artificial intelligence (AI) to give its humanoid robots a more natural-looking stride, and they say it's just the beginning.
In the promotional video, the robot, called Figure 02 and manufactured by the company Figure, marches with a "human-like" gait. This is an ability it claims will help its robot to navigate the physical world more easily.
"These initial results are exciting, but we believe they only hint at the full potential of our technology," company representatives wrote in a blog post accompanying its announcement. "We're committed to extending our learned policy to handle every human-like scenario the robot might face in the real world."
Robots have been running, cartwheeling, doing backflips, breakdancing, and beating us at chess for years now. But performing tasks that appear simple to humans, such as walking in a straight line, gripping objects, tying shoelaces, and navigating social situations, have proven tough for robots to master.
Related: Chinese humanoid robot is the 'fastest in the world' thanks to its trusty pair of sneakers
The problem, known as Moravec's Paradox, emerges because computers excel at problems that require complex calculations and large datasets, but lack our real-world experience honed by millions of years of evolution. This makes robots' shuffling gaits, well, robotic at best. At worst, it gives them the appearance that they may have soiled themselves.
To tackle the robot's unnatural gait, Figure's engineers used a learning technique called reinforcement learning — placing thousands of virtual robots inside a physics simulator that recreates various terrains, thereby improving their walking through trial and error.
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By rewarding the virtual robot army for natural motions, they refined their gaits to appear more human-like. With this task accomplished, they uploaded the refined "Learned Natural Walking" model to a real-world Figure 02 robot. The result is an android that can move somewhat naturally, with heel strikes, toe-offs and synchronized arm swings.
Figure's reinforcement learning technique is key to the California company's plans to roll out its robots on factory floors. It has already tested its humanoid robots in a BMW factory in 2024 and plans to introduce more this year. Meanwhile, Apptronik, a Texas-based competitor, is also commercializing its humanoid robot, Apollo, for use in Mercedes-Benz factories by the end of 2025. Agility Robotics' Digit will also be introduced into warehouses this year.
Ben Turner is a U.K. based staff writer at Live Science. He covers physics and astronomy, among other topics like tech and climate change. He graduated from University College London with a degree in particle physics before training as a journalist. When he's not writing, Ben enjoys reading literature, playing the guitar and embarrassing himself with chess.
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