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AI in Space is helping us to go to space effectively and efficiently

There’s no denying the fact that we live in a period where technology has inevitably become less counterfeit but rather more intelligent. Regardless of whether we talk about AI applications or the uses of its subsets specifically machine learning and deep learning, the scope is huge on what people could have or can envision. Given that, would it be bizarre to realize that AI applications have outperformed our customary lives and are currently taking control over space (Indian moon mission – Chandrayaan-2, for example)?

Expanding the levels of automation and autonomy utilizing strategies from artificial intelligence takes into account a more extensive variety of space missions and furthermore frees people to zero in on tasks for which they are more qualified. At times, autonomy and automation are crucial to the success of the mission. For instance, deep space exploration may require more autonomy in the rocket, as communication with ground operators is adequately inconsistent to block persistent human monitoring for conceivably hazardous situations.

Artificial intelligence-based automated planning has discovered a characteristic role to deal with these exceptionally constrained, complex activities. Early triumphs here incorporate the ground processing scheduling system (Deale et al.1994) for NASA space shuttle refurbishment and the SPIKE framework used to plan Hubble Space Telescope tasks (Johnston and Miller 1994). SPIKE empowered a 30% increment in observation utilization (Johnston et al. 1993) for Hubble, a significant effect for a multi-billion dollar mission. Likewise amazing is that SPIKE or elements of SPIKE have been or are being utilized for the FUSE, Chandra, Subaru, and Spitzer missions

Applications of AI in Space

Earth Observation

Robots with AI are being implemented to screen certain regions, like perilous environments. Satellites can notice them from above, saving individuals from entering hazardous or dangerous spots. Any information would then be gathered and fed to robots with artificial intelligence, that can process it and choose the preferred action.

The satellite EO-1 (Earth Observing 1) has been effective in the past in collecting pictures of natural calamities. The AI began to take photos of the catastrophes even before the ground team realized that the episode had occurred. It was the first satellite to detect active lava flows from space, to gauge a facility’s methane spill from space and to track redevelopment in a mostly logged Amazon forest from space. View More