Modelling and Simulation of Microstructural Evolution for Extra-terrestrial Planetary Chemistry Mapping Using Artificial Intelligence – A NASA Mars Rover Study

Development of rovers and development of infrastructure which enables them to probe other planets
(such as Mars) have sparked a lot of interest recently specially with increasing public attention in
Moon and Mars program by National Aeronautics and Space Administration. This is designed to be
achieved by various means such as advanced spectroscopy and artificial intelligent techniques such
as deep learning and transfer learning to enable the rover to not only map the surface of planet but to
get a detailed information about its chemical makeup in layers beneath (deep learning) and in areas
around point of observation (transfer learning). In this work, which is part of a proposal, later approach
is explored. A systematic strategy is presented which make use of aforementioned techniques
developed for metallic glass matrix composites as benchmark and helps develop algorithms for
chemistry mapping of actual Martian surface on Perseverance Rover launched shortly.