NASA and Autodesk are using an AI that designs new interplanetary landers

Despite the fact that a full-fledged mission to Mars has not yet happened, the various space Agency is not only planning a study of the red planet, but already looking into the future, developing and presenting community projects to explore other planets in our Solar system. For example, recently the engineers at the jet propulsion Laboratory NASA (Jet Propulsion Laboratory, JPL), together with colleagues from Autodesk presented AI, who is designing a model of a new interplanetary lander for missions to Saturn and Jupiter.

And in this case, NASA wants to use all possibilities for creation of aircraft, as the journey will be much longer. If in 2012 the Rover Curiosity had to overcome the way in about 35 million miles, to Jupiter and Saturn’s future vehicles will have to fly 365 and 381 million miles, respectively. Moreover, when planning such missions, one of the most difficult tasks is designing the lander. NASA in such projects have come to rely “on what proved itself and works well”, so they considered using a modified version of the Mars lander. However, Autodesk initiated a completely different approach and, according to senior Director of industry research Autodesk Mark Davis,

“Initially, it was clear that they (NASA) are not interested in cooperation, if our technology improves performance by only 10%. But if we were able to provide software tools that will help them to increase productivity by 30% or more, then we would attract their attention. And our current project demonstrates that we have achieved these targets.”

The concept of the landing module created by AI

In space flight the weight is critical because every pound spent on the creation of the body reduces the amount of payload. To solve this problem, Autodesk has used the so-called generative design. Generative design is a relatively new design approach that uses artificial intelligence and cloud computing to quickly create a wide range of design solutions that meet certain constraints set by the engineers. This allows you to obtain many samples of the design of future devices for a short period of time. These samples will conform to all established requirements and standards. For example: AI offers one project every 2-4 weeks, whereas people creating projects like this at least 2 months.

“This flexibility and speed allows you to quickly make changes and see the result and not start from scratch every time.”

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