Skip to main content

You can help teach NASA rovers to explore Mars with the AI4Mars project

Artificial intelligence could be a huge help to Mars rovers like NASA’s Curiosity or Perseverance, but first these A.I. systems need to be trained on what to look for. A NASA project invites members of the public to help identify features of the Martian landscape, in order to train an algorithm that future rovers could use to navigate around the red planet.

The robotic arm of NASA’s Perseverance rover is visible in this image used by the AI4Mars project.
The robotic arm of NASA’s Perseverance rover is visible in this image used by the AI4Mars project. Users outline and identify different rock and landscape features to help train an artificial intelligence algorithm that will help improve the capabilities of Mars rovers. NASA/JPL-Caltech

The AI4Mars project was launched last year, and users have already labeled nearly half a million images to help develop the Soil Property and Object Classification (SPOC) algorithm. This algorithm identifies features of the landscape like sand and rock, and does so correctly nearly 98% of the time. In the future, this algorithm could be incorporated into Mars rovers’ autonomous driving capabilities like the AutoNav technology used by Perseverance.

Now, the researchers want to expand SPOC to get more detailed information about rock formations such as the presence of float rocks or nodules. By automatically classifying the types of rock imaged by rovers, the researchers can send driving instructions back to the rovers more quickly.

“It’s not possible for any one scientist to look at all the downlinked images with scrutiny in such a short amount of time, every single day,” explained Vivian Sun, a JPL scientist who helps coordinate Perseverance’s daily operations and consulted on the AI4Mars project. “It would save us time if there was an algorithm that could say, ‘I think I saw rock veins or nodules over here,’ and then the science team can look at those areas with more detail.”

To help develop this algorithm, NASA is inviting members of the public to go to the AI4Mars page on Zooniverse and look at images of the Martian surface captured by the Curiosity rover. They are asked to draw polygons around particular features like sand, soil, bedrock, and large rocks. The results of thousands of classifications made by the public are then collated and checked by scientists to make sure that the labeling is accurate.

Over time, as more individual pieces of data are labeled, the algorithm can learn to distinguish features for itself.

“Machine learning is very different from normal software,” said lead researcher for the AI4Mars project, Hiro Ono. “This isn’t like making something from scratch. Think of it as starting with a new brain. More of the effort here is getting a good dataset to teach that brain and massaging the data so it will be better learned.”

Editors' Recommendations

Georgina Torbet
Georgina is the Digital Trends space writer, covering human space exploration, planetary science, and cosmology. She…
How Europe’s ExoMars rover plans to get to Mars without Russia
ESA’s Rosalind Franklin twin rover is back on its wheels and drilled down 1.7 metres into a martian-like ground in Italy – about 25 times deeper than any other rover has ever attempted on Mars. The test rover, known as Amalia, also collected samples for analysis under the watchful eye of European science teams.

Space missions get scuppered for all kinds of reasons, from engineering problems to budget issues. But the ExoMars mission, Europe and Russia's joint plan to send a rover to Mars, faced a complicated political and ethical issue when Russia invaded Ukraine last year. The European Space Agency (ESA) had been working with the Russian space agency Roscomos on the mission but this partnership was soon suspended over what ESA called the "human casualties and tragic consequences of the aggression towards Ukraine."

Without Roscosmos, the Rosalind Franklin rover was left without a launcher and it was not clear whether the rover would be able to launch at all. But loath to give up on the project, ESA decided it would build its own lander and get the rover to Mars hopefully by 2030. This week, ESA shared more information about the plans for the mission and how it is continuing with testing for the rover.

Read more
Rovers could explore lava tubes on Mars or the moon using breadcrumbs
In this artist's impression of the breadcrumb scenario, autonomous rovers can be seen exploring a lava tube after being deployed by a mother rover that remains at the entrance to maintain contact with an orbiter or a blimp.

When looking for safe places for astronauts to stay when they venture away from Earth to new moons and planets, one strong contender is that they should stay underground. Being underground means more protection from harmful space radiation and less exposure to weather events, and nature already creates environments that could be ideal bases in the form of lava tubes. Created when molten lava flows under the surface, lava tubes are thought to exist on both Mars and the moon, providing potential shelter for human explorers.

Now, new research from engineers at the University of Arizona proposes a method for using robots to scout out lava tubes for use as habitats ahead of the arrival of human astronauts. "Lava tubes and caves would make perfect habitats for astronauts because you don't have to build a structure; you are shielded from harmful cosmic radiation, so all you need to do is make it pretty and cozy," said lead author of the research, Wolfgang Fink, in a statement.

Read more
Perseverance Mars rover shares detailed panorama of sample depot
The site of Perseverance's sample depot.

NASA’s Perseverance Mars rover has been busy creating what the space agency recently said was “humanity’s first sample depot on another planet.”

The depot, which is essentially a flat patch of land, contains 10 titanium tubes holding samples of martian rock and dust collected by NASA’s rover in the two years since it landed on the red planet.

Read more