A few months ago, NASA unveiled its next-generation space suit that will be worn by astronauts when they return to the moon in 2024 as part of the agency’s plan to establish a permanent human presence on the lunar surface. The Extravehicular Mobility Unit—or xEMU—is NASA’s first major upgrade to its space suit in nearly 40 years and is designed to make life easier for astronauts who will spend a lot of time kicking up moon dust. It will allow them to bend and stretch in ways they couldn’t before, easily don and doff the suit, swap out components for a better fit, and go months without making a repair.
But the biggest improvements weren’t on display at the suit’s unveiling last fall. Instead, they’re hidden away in the xEMU’s portable life-support system, the astro backpack that turns the space suit from a bulky piece of fabric into a personal spacecraft. It handles the space suit’s power, communications, oxygen supply, and temperature regulation so that astronauts can focus on important tasks like building launch pads out of pee concrete. And for the first time ever, some of the components in an astronaut life-support system will be designed by artificial intelligence.
Jesse Craft is a senior design engineer at Jacobs, a major engineering firm based in Dallas that was tapped by NASA to revamp the xEMU life-support system. For Craft and the hundreds of other engineers working on the project, this requires a careful balancing act between competing priorities. The life-support system has to be safe, obviously, but it also has to be light enough to fit the weight limits for the lunar lander and strong enough to withstand the intense g-forces and vibrations it will experience during a rocket launch. “It’s a really big engineering challenge,” says Craft.
Squeezing more stuff into less space with reduced mass is the kind of complex optimization problem that aerospace engineers deal with all the time. But NASA wants boots on the moon by 2024, and meeting that aggressive timeline meant that Craft and his colleagues couldn’t spend weeks debating the ideal shape of each widget. Instead, they’re piloting a new AI-fueled design software that can rapidly come up with new component designs.
“We consider AI to be a technology that can do something faster and better than a trained human can do,” says Jesse Coors-Blankenship, the vice president of technology at PTC, the American company that made the software. “Some of the software technologies are things engineers are already familiar with, like structural simulation and optimization. But with AI, we can do it faster.” This approach to engineering is known as generative design. The basic idea is to feed the software a set of requirements for a component’s maximum size, the weight it has to bear, or the temperatures it will be exposed to and let the algorithms figure out the rest.
PTC’s software combines several different approaches to AI, like generative adversarial networks and genetic algorithms. A generative adversarial network is a game-like approach in which two machine-learning algorithms face off against one another in a competition to design the most optimized component. It’s the same technique used to generate photos of people who don’t exist. Genetic algorithms, by contrast, are analogous to natural selection. They generate multiple designs, combine them, and then take the best designs of the new generation and repeat. In the past, NASA has used genetic algorithms to design optimal—and bizarre—antennas.
“The machine’s iterative process is 100 or 1,000 times more than we could do on our own, and it comes up with a solution that is ideally optimized within our constraints,” says Craft. It’s especially helpful given that the final design of the space suit life-support system is still in flux. Even a small change to the requirements in the future could result in weeks of wasted work by engineers.
Today, engineers are beginning to use AI-driven design software to redesign everything from car chassis to chairs to apartment complexes. The algorithms tend to dream up components that look pretty alien: They’re cellular, flowing, and tendinous, with lots of negative space. “We’re using AI to inspire design,” says Craft. “We have biases for right angles, flat surfaces, and round dimensions—things you’d expect from human design. But AI challenges your biases and allows you to see new solutions you didn’t see before.”
For now, the components that the AI is tasked with making are pretty mundane. “We’re still in the early piloting phase, so we’re not turning over something that could cause a catastrophic failure,” says Sean Miller, a mechanical designer in the crew and thermal systems division at NASA. Instead, the algorithms are building better brackets and support structures for the systems that keep astronauts alive. It might not be the most sexy application for AI, but it works. The AI has been able to reduce the mass on some components by up to 50 percent, and when it comes to space travel, every gram counts.
“When NASA sets the requirements for a human landing system, they allocate a certain amount of mass for every possible thing you can imagine that we have to hit,” says Miller. “So anywhere we can save even a couple of tenths of a pound gets us closer to the weight limit we have to meet for the mission to run.”
When NASA sent humans to the moon for the first time 50 years ago, artificial intelligence was still a distant dream for computer scientists. We may not have moon bases just yet, but with a helping hand from AI, it seems like only a matter of time.
More Great WIRED Stories
- We can protect the economy from pandemics. Why didn’t we?
- Passionflix and the Musk of Romance
- Live wrong and prosper: Covid-19 and the future of families
- How surveillance has always reinforced racism
- Everything you need to know before buying a gaming PC
- ? Is the brain a useful model for AI? Plus: Get the latest AI news
- ? Upgrade your work game with our Gear team’s favorite laptops, keyboards, typing alternatives, and noise-canceling headphones