Artificial intelligence has made headlines in recent years, allowing us to solve issues faster than traditional computing ever could. Google's artificial intelligence unit DeepMind, for example, recently produced AlphaFold2, a programme that solved the protein-folding challenge. For the past 50 years, scientists have been perplexed by this issue.

AI advancements have enabled us to make progress in a wide range of areas, and these are not confined to applications on Earth. Here are a few ways artificial intelligence can help us go further in space, from mission planning to cleaning debris from Earth's orbit.

Virtual assistant

A recently developed virtual assistant may be able to detect any threats in long-duration space missions, such as changes in the spacecraft atmosphere, such as increasing carbon dioxide, or a sensor malfunction that could be dangerous. It would then notify the staff and make inspection suggestions.

Cimon

Cimon, an AI helper, was sent to the International Space Station (ISS) in December 2019 and will be tested for three years. Cimon will eventually be utilized to alleviate astronaut stress by doing duties assigned to it. NASA is also creating Robonaut, a companion for astronauts aboard the ISS that will work alongside them or take on activities that are too dangerous for them.

Mission planning 

Planning a Mars expedition is a difficult task, but artificial intelligence can help. Previous research has traditionally been used to inform new space missions. However, this information is frequently limited or inaccessible.

Mission Design

This means that the flow of technical knowledge is limited by who has access to and shares it with other mission design engineers. But what if anyone with authorization could access virtually all prior space missions with just a few mouse clicks? One day, a smarter system - similar to Wikipedia, but with artificial intelligence that can answer complicated inquiries with credible and relevant material - may be available to aid in the early design and planning of new space missions.

Initial mission design

Researchers are developing the concept of a design engineering assistant to shorten the time required for initial mission design, which would otherwise take many human labor hours. Another example of an intelligent helper for constructing Earth observation satellite systems is 'Daphne.' Systems engineers in satellite design teams utilize Daphne. It simplifies their job by giving them access to relevant information, such as comments and answers to particular questions.

Data processing through satellite

Earth observation satellites produce massive amounts of data. This is received in bits by ground stations over a long period of time and must be stitched together before it can be analyzed. While some crowdsourcing efforts have been done to undertake basic satellite imagery analysis on a very limited scale, artificial intelligence can come to our rescue for extensive satellite data analysis.

Data Volume

For the sheer volume of data received, AI has shown to be quite successful in processing it intelligently. It's been used to estimate heat storage in cities and to integrate meteorological data with satellite pictures to estimate wind speed. AI has also aided in the calculation of solar radiation using geostationary satellite data, among many other applications.

Debris in space

One of the most pressing space concerns of the twenty-first century is how to deal with space trash. According to the European Space Agency, over 34,000 objects larger than 10cm pose major hazards to existing space infrastructure. There are some novel techniques to dealing with the threat, such as constructing satellites to re-enter Earth's atmosphere if put in low Earth orbit, causing them to disintegrate fully in a controlled manner.

Another method is to avoid any potential collisions in space, so avoiding the formation of debris. In a recent study, researchers used machine-learning (ML) techniques to construct collision avoidance maneuvers.

Novel Approach

Another unique strategy is to train ML models on Earth, then transfer such models to spacecraft already in orbit or on their way, and use them on board for various decisions. One new proposal to ensure the safety of space journeys is to use pre-trained networks on board the spaceship. This allows for greater flexibility in satellite design while reducing the risk of in-orbit collision.

Systems of navigation

On Earth, we are accustomed to tools that employ GPS or other navigation systems, such as Google Maps. However, there is currently no comparable mechanism in place for other extraterrestrial bodies.

We don't have any navigation satellites orbiting the Moon or Mars, but we could use the millions of photographs collected by observation satellites like the Lunar Reconnaissance Orbiter (LRO). In 2018, a NASA team of researchers collaborated with Intel to develop an intelligent navigation system for planet exploration utilizing AI. They generated a simulated Moon map by training the algorithm on millions of photos from several missions.