During a new project, NASA asked all people to participate in training the artificial ielligence of Mars rover to better ideify the surface features of Mars.
NASA’s Perseverance rover is the most advanced vehicle ever se to the Red Planet, with an array of cameras and a meticulous design that should stand the test of time.
However, it’s just a robot, and sometimes human understanding can help a robot become iellige. If you’d like to coribute to the persiste rover, NASA is asking ehusiasts to help with persiste machine learning algorithms.
All you have to do is look at the pictures and mark the releva geological features. This is something that most people can do directly, but it’s difficult for a robot.
This NASA project for training the artificial ielligence of the Mars rover is called “Artificial Ielligence for Mars” (AI4Mars) and is a coinuation of the project that started last year for the Mars rover “Curiosity”. Curiosity reached Mars in 2012 and has been making history ever since. NASA used the experience gained with the Curiosity rover as a starting poi when designing the Persistence.
The new rover has 23 cameras that record a large amou of image data from Mars, but the robot relies on human operators to further ierpret these images. This rover has artificial ielligence to pass the surface obstacles of Mars well, and in the new NASA project with the help of people, its ielligence will be even better.
Selfie of Mars Rover Perseverance with Genius Mars Rover Helicopter
Credit: NASA/JPL-Caltech/MSSS/Seá Doran
The AI4Mars project site allows users to choose between Opportunity, Curiosity, and new images of the Perseverance rover. After selecting the type of images the user was to review, several differe indicators are displayed along with descriptions of each.
For example, the NavCam asks the user to detect sand, loose soil (where the wheels have good traction), bedrock, and large rocks. Examples of all of these structures are included, so getting started is quick.
With all this labeled data, NASA can train neural networks to better recognize Martian surface features. Eveually, a rover might be able to walk around and collect samples without waiting for commands from the mission corol team and receiving precise instructions for the slightest moveme.
AI training also helps to better ideify the most importa geological features, saving humans from blindly sifting through gigabytes of data.
The result of Curiosity’s AI4Mars project is an algorithm called Soil and Object Feature Classification (SPOC). The algorithm is still under active developme, but according to NASA, it can now ideify Martian features with 98% accuracy.
Tagged images from the Persistence rover, which include more detail including lone rocks, pollen-like pebbles, and appare bedrock texture, further improve the SPOC algorithm. In some images, almost all objects are already labeled, but others may be incomplete.
The artificial ielligence project Curiosity recorded about half a million tagged images. Although uploading 20,000 persiste images is a good achieveme for the mission team, this amou will probably be much higher.
Cover photo: The artificial ielligence training process of Perseverance Mars rover
Credit: NASA/JPL-Caltech
Source: Extreme Tech
