Adriana Mitchell is a PhD candidate whose research interests are focused on space exploration, and the application of machine learning (ML) techniques to improve space-based optical navigation under variable illumination conditions during entry, descent, and landing on planetary bodies. A MathWorks Fellowship will support her ongoing project to develop terrain-relative navigation applications, drawing on MATLAB, by creating deep learning approaches for this application.
Adriana has worked with fellow researchers at NASA’s Jet Propulsion Laboratory (JPL) to validate and implement an ML method to robustify terrain-relative navigation during entry, descent, and landing under variable illumination conditions on NASA orbital lunar and Mars imagery. She has also collaborated on an ESA project to validate and implement a tool to determine camera and orbit requirements for visual navigation of a CubeSat around a near-Earth asteroid for ESA’s M-ARGO mission. Adriana’s work holds the potential to give rise to ML techniques that advance space exploration and innovations in aerospace engineering.