Microsoft developed a system based on artificial intelligence (AI) that will help ensure that astronauts’ gloves on board the International Space Station (ISS) are in good condition that is, that they do not have wear or breakage that could affect the safety of the specialists who use them.
The development is of vital importance because astronauts carry out critical scientific missions in an environment in which safety is paramount.
Gloves are used to install instruments or make repairs, among other tasks. Regular use can cause wear and tear such as tears or cuts, which could involve risks to the astronauts when carrying out their activities or manipulating certain artifacts.
Currently, to prevent problems from arising, astronauts working for NASA must take photos of the gloves after each spacewalk and send them back to Earth for inspection. From there, NASA analysts examine the images for any damage. that could pose a danger and then send the results back to the astronauts on the ISS.
To optimize this processa Microsoft team along with NASA scientists and Hewlett Packard Enterprise engineers are working on a system that uses AI and HPE’s Spaceborne Computer-2 to scan and analyze glove images directly on the ISS which could give astronauts autonomy on board with limited support from Earth, highlighted on the official blog of the computer giant.
Astronaut gloves have five layers. The outer layer consists of a rubber coating that provides grip and acts as the first layer of defense. Next comes a layer of a cut-resistant material called Vectran.
The three additional layers maintain the suit’s pressure and protect against extreme temperatures in space, which can range from 180°F to 235°F.
The outer layer is designed to withstand a fair number of situations, but when damage reaches the cut-resistant layer problems can arise. Gloves are most vulnerable between the thumb and forefinger, given the frequency with which those two fingers are used to grab objects, as explained in the posted post.
“Furthermore, some areas of the ISS itself have been exposed to hazards such as micrometeorites for more than two decades. The impacts of these tiny particles have created numerous sharp edges on handrails and other structural components. More dangers will be found on the Moon and Mars, where the lack of natural erosion by wind or water means that rock particles look more like shards of glass than pebbles or grains of sand here on Earth. the notice.
To carry out proper monitoring, NASA began to collect new gloves and contrast them with others that exhibited wear. Once they gathered this material, they photographed it and proceeded to label the types of wear or damage identified.
The latter was done through Azure’s Custom Vision cloud AI system. The engineers opened the images of the gloves in a web browser and clicked on examples of damage.
That data was then used to train a cloud-based AI system and the results were compared to actual damage reports and images from NASA.
The tool then generated a probability score to assess the possibility of damage to a particular location on the glove.
This training served to develop the tool that can be used on the space station as follows:
Astronauts on the space station take photos of the gloves that are sent to HPE’s Spaceborne Computer-2 aboard the ISS, where the Glove Analyzer quickly looks for signs of damage in space.
If any issues are detected, a message is immediately sent back to Earth, identifying areas for further review by NASA engineers.
“What we demonstrate is that we can perform AI and edge processing on the ISS and analyze gloves in real time,” Ryan Campbell, senior software engineer at Microsoft Azure Space, said in the release. “Because we are literally next to the astronaut when we do the processing, we can run our tests faster than images can be sent back to Earth.”
This technology, which is used for gloves today, could be used in the future to verify other critical components, such as docking hatches. In addition, it is possible that Microsoft HoloLens 2 or another similar device could help astronauts quickly perform a visual scan for damage to gloves, or even facilitate assisted repairs on different machinery.
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