Artificial Intelligence for the Advancement of Lunar and Planetary Science and Exploration
Whitepaper #222 submitted to the Planetary Science and Astrobiology Decadal Survey 2023-2032. Topics: Mercury and/or the Moon; other: Artificial Intelligence and Machine Learning; other science themes: Interdisciplinary Science
by Indhu Varatharajan, Daniel Angerhausen, Eleni Antoniadou, Valentin Bickel, Mario D'Amore, Michele Faragalli, Ignacio López-Francos, Abhisek Maiti, Ross Potter, Carl Shneider, Shashwat Shukla, Frank Soboczenski, Nishan Srishankar, and Ryan Watkins
Published onMar 18, 2021
Artificial Intelligence for the Advancement of Lunar and Planetary Science and Exploration
AI-driven methods have potential to minimise manual labour during planetary data processing and aid ongoing missions with real-time data analysis. This white paper focuses on key areas of AI-driven research, the need for open source training data, and the importance of collaboration between academia and industries to advance AI-driven research.
Creative Commons Attribution 4.0 International License (CC-BY 4.0)
