How will AI help space exploration?


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Artificial intelligence is used to solve problems big and small, on Earth and beyond. Rapid developments in AI hold promise for advancing space exploration in leaps and bounds. Whether it’s providing personal assistance to astronauts or helping us better understand the Sun, here’s how AI can help with space exploration.

Virtual assistance to astronauts

We’re a long way from an actual R2D2, but AI-based virtual assistants that can help astronauts are currently in development. A newly developed AI assistant is able to detect risks and dangers in long space missions, detecting things such as increased carbon dioxide in the atmosphere of the spacecraft. These assistants can alert the crew to sensor malfunctions and other issues requiring inspection.

Likewise, in 2019, a similar AI assistant known as Cimon visited the International Space Station, where he will “live” for three years. Cimon will be tested to reduce stress on astronauts by performing the tasks requested of him. He’s an interstellar butler, if you will. Additionally, NASA is developing Robonaut, an AI bot that will work with astronauts in the harsh conditions of space – and even fulfill responsibilities that may be too dangerous for humans.

Study the sun

Understanding the Sun is a particularly difficult activity. Solar telescopes degrade rapidly due to intense sunlight and an “endless stream of solar particles,” according to NASA. AI is used by some researchers to improve solar research. AI can help ensure that the data used by scientists to understand the Sun is always accurate and allow scientists to periodically recalibrate their telescopes to maintain data quality.

The result: since 2010, NASA’s Solar Dynamics Observatory has been able to continuously monitor the Sun, taking images at 10 wavelengths every 12 seconds. With machine learning and AI, they can determine the extent of degradation affecting current telescope images and the amount of calibration needed for each. This leads to a much better understanding of the most important star in our universe.

Mission planning made easy

Exploring the great hereafter requires planning for a plethora of unknowns. Since astronauts go where little, if any, has traveled before, they must rely on limited information obtained from previous studies or space missions. This information can be both scarce and inaccessible.

Mission planning teams are now using AI to help gather information from past explorations. “Someday there may be a smarter system – similar to Wikipedia, but with artificial intelligence capable of responding to complex queries with reliable and relevant information – to help early design and planning of news. space missions, “wrote the World Economic Forum.

An AI assistant is already deployed to condense the time required to create a preliminary mission design. Additionally, Daphne is an intelligent assistant used to design Earth observation satellite systems. AI clearly has the potential to reduce the number of man-hours required to create a mission plan, by gathering feedback and information quickly.

Avoid space debris

It turns out that space is actually running out of space. There are nearly 34,000 objects larger than 10 cm that could endanger existing space infrastructure, cause collisions or damage space missions.

Machine learning helps to avoid possible collisions with space debris using “collision avoidance maneuver design”. The AI ​​performs complex calculations to map the best possible path for a satellite or spacecraft to avoid oncoming debris. These models can help improve safety and keep satellites in circulation longer.

Understanding satellite data

Satellites produce a huge amount of data, so much so that scientists and researchers cannot process it in real time. AI is able to help, by producing reports that have a real impact on life on Earth. For example, AI can use satellite data to estimate heat storage in cities or weather data to better estimate wind speed. AI can also help scientists understand when satellites need to be called up for maintenance, detect problems or malfunctions, and predict performance over time.

Image Credit: iurii / Shutterstock.com

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