How AI could enable autonomous robot workers in workplaces—and maybe homes - Ars Technica

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In a world where self-driving robotaxis glide through major city streets without drivers behind the wheel and delivery drones autonomously fly through the skies to drop off orders at customers’ homes, the idea of general-purpose robots helping humans with various tasks in workplaces or even homes may not seem far-fetched.

But that future hinges on developing increasingly autonomous robots powered by modern artificial intelligence—an ambitious vision that has motivated many researchers to become startup founders while also attracting billions of dollars in investment.

“When I started maybe about 15 years ago, I led a project team that was focused on autonomy, but in that era, the goal of that team was to just get a robot to navigate from point A to point B,” said Matt Malchano, vice president of software at the robotics company Boston Dynamics based in Waltham, Massachusetts. “And now, when we think of autonomy, we think of this huge space of tasks and things that we can imagine a robot doing on its own.”

It was previously difficult to imagine a practical path for creating general-purpose, autonomous robots like housekeeper Rosie from The Jetsons or the various droids like C-3PO from Star Wars, especially when robotics labs and companies were still struggling to solve autonomous navigation and even self-balancing, in the case of walking robots. In 1979, the experimental autonomous vehicle known as the Stanford Cart required five hours to successfully move 20 meters through an obstacle-filled room. The first bipedal robot capable of walking on its own without losing its balance was developed in 1996.

But robot autonomy has always been a “moving target,” with the goal of reaching a point where robots can do an increasingly larger subset of things that humans can already do, ideally without direct human supervision, Malchano told Ars. The International Standards Organization defines autonomy in robotics as the “ability to perform intended tasks based on current state and sensing, without human intervention.”

More recent advances in AI—such as reinforcement learning in the 2010s and large foundation models trained on huge amounts of data in the 2020s—have “unlocked” the ability to “imagine a world where the robot can do sequences of activities and really understand the tasks, and that’s very exciting,” Malchano said. Now, multiple research labs and companies are racing to develop general-purpose robots capable of handling a wide variety of tasks independently in more complex, unpredictable environments.

Such robots will not necessarily be humanoid in appearance and function despite the substantial amounts of investor money going into humanoid robots. But whatever their form, they could represent a significant step beyond the millions of industrial robots and service robots that already perform specific tasks within the relatively controlled environments of factories and warehouses.

“There’s an assembly line, the robot is supposed to do a particular motion, and if you do that motion reliably and repeatedly, that’s a basic factory level of autonomy,” said Sergey Levine, a computer scientist at the University of California Berkeley and cofounder of the AI and robotics company Physical Intelligence. “The next level, though, the one that is currently at the edge of what’s possible—like a research topic that’s making its way into the real world—is that the robot can do a thing in an unstructured environment reliably.”

Ars interviewed robotic researchers and founders about how AI has supercharged interest in robotics, the challenges of making general-purpose robots, how safety is a make-or-break issue for robot workers, why surgical robots still have limited autonomy, and when to expect robot helpers in people’s homes.

The modern AI impact on robotics

Levine’s startup, called Physical Intelligence, is working toward achieving practical robotic intelligence that can empower many different types of robots operating autonomously in open-world environments. “I don’t think it will be the one ultimate robot, like a super advanced humanoid that can do everything,” Levine told Ars. “I think it will be a general AI model that can power lots of different robots that are well-suited for their job.”

For example, a small robotic arm hanging from the ceiling might prove more suitable for a tiny New York City apartment, whereas a “hulking giant robot” that moves heavy objects could be more handy...