In the movie WALL-E, the last Earthlings travel through the Kuiper Belt on board the starship Axiom. For 700 years, a fully automated crew of robots has cared for them now that Earth has become inhospitable. Running the ship’s operations is AUTO. AUTO is an artificial intelligence (AI) system working to keep humans away from Earth — forever.
Here at home, space agencies like NASA and the European Space Agency are using AI to explore our solar system. This includes guiding rovers on Mars, preventing satellite collisions and training astronauts for spaceflight. But these AI systems are much more limited than their fictional counterparts.
Today’s AI is much more unpredictable and prone to mistakes than what you see in fiction, says Daniele Gammelli. At Stanford University in California, he studies how to integrate AI systems into robots that interact with their environment.
Anyone using ChatGPT has probably seen how it hallucinates, or makes up inaccurate information. AI systems in space robots would need to complete multi-step tasks in all sorts of scenarios without mistakes. After all, Gammelli says, in space, “you have virtually no room for error.”
The little robot that could
The title robot WALL-E is a trash-compacting machine — one that abandons his duties to follow another robot, EVE. WALL-E’s greatest strength is, arguably, his ability to handle change. To escape a self-destructing pod, WALL-E uses a fire extinguisher to flee. When his wheel or eye malfunctions, WALL-E can replace the damaged part. All this is learned from experience and done without additional programming.
Such versatility is an example of artificial general intelligence (AGI). This type of AI doesn’t yet exist. It would think and learn like a human across different situations. AGI could also take on tasks for which it had not been programmed.
Adapting to unforeseen situations is a big goal for future space robots, says Gammelli. Between radiation, extreme temperatures and space debris, space is a dangerous, ever-changing environment. Any robot navigating space would need to handle evolving conditions — many of which don’t exist on Earth.
“The kind of scenarios you are kind of forcing on your robot are, by definition, things that nobody has ever seen,” he says.
Today’s AI excels at single tasks or several closely related ones. Known as narrow AI, it handles repetitive and predictable work well. “I’d say the top skill that it excels in is processing a huge amount of data very efficiently,” says Sanjoy Paul in Houston, Texas. There, at Rice University, he studies how AI can assist in space missions.
Martian rovers use narrow AI. To select rock samples, Perseverance employs AI algorithms to scan minerals and assess if they’re worth collecting. Another rover, Curiosity, uses AI to zap rocks with lasers based on their shape and color. All of this is done without human input.
Any human sorting through that kind of data could get overwhelmed, says Paul. When faced with huge amounts of data, people can struggle to make decisions. Why? Picking out important details becomes much harder. “AI can actually cut through all the details … and highlight those things for humans to take a look at,” he says.
To handle multi-step tasks, nearly all space robots rely on so-called autonomy stacks, explains Gammelli. These are separate, but linked, modules that tackle different actions. For instance, one AI model might use cameras or sensors to detect rocks or obstacles. This info would be passed to another module. It would interpret those results and determine the appropriate next action. Other modules would then carry out the physical maneuvers to get that job done.
Still, today’s robots fall short of what people can physically do, says Paul. Many of the basic actions we perform require lots of coordination. Researchers are still studying how to design AI models to carry out actions as efficiently as possible, says Paul.
Would you trust AI with your life?
Aboard the fictional Axiom, robots manage everything. Custodial robots scrub and polish. Utility bots handle repairs and maintenance. Hover chairs cart the ship’s residents to their destinations. This lets Axiom’s passengers live sedentary lives, spending their days watching videos and drinking food shakes.
People would probably need to play a bigger role in space travel than what was depicted in WALL-E, says Paul. While AI continues to improve by leaps and bounds, it remains unpredictable. With lives at risk, one small mistake could prove disastrous. “If your life depends on it, would you really bank on AI? Probably not,” he says. “You still need humans in the loop.”
Most likely, he suspects, space travelers would rely on AI as an assistant. That might look more like another fictional AI system: J.A.R.V.I.S. from the Iron Man series. Tasked with monitoring Tony Stark’s buildings and power suits, J.A.R.V.I.S. acts more like a team member than a captain. It synthesizes data and offers suggestions to Stark, who remains in control. With large language models like ChatGPT and Claude, that option seems much more feasible, says Paul.
Still, people wouldn’t want to micromanage all spacecraft, says Gammelli. Machines like rovers should eventually be able to make their own mini-goals, he says. These would all align with the engineer’s overall mission.
Such mini-goals would allow bots to handle unforeseen situations better. It would also free up people to take care of more critical tasks and decisions. “We want these robots to be as independent as possible,” he says. Though maybe not as independent as mission-quitting WALL-E.
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