| Title: | Test case: optimize lunar outpost specifications |
| Material Type: | ISU Team Project report |
| Publisher: | Illkirch-Graffenstaden (France) : International Space University, 2022 |
| Format: | 1 electronic resource (xi, 33 p.) / col. ill. |
| Bibliography note: | Includes bibliographical references |
| Languages: | English |
| Class number: | TL799.M6 |
| Subjects: | Artificial intelligence ; Lunar bases ; Space flight to the moon |
| Description: | This study undertakes an interdisciplinary investigation into the application of artificial intelligence and machine learning to optimize the establishment of a lunar outpost. It focuses on seven core disciplines: space applications; engineering; management and business; human performance; science; humanities; and policy, ethics, and law. A review of existing literature for each discipline informed the selection of target specifications to optimize. These specifications were evaluated, and outpost location optimization was selected as the primary subject of the study. Five selected specifications were identified as needing to be satisfied: maximizing solar exposure; ease of terrain access; proximity to sites of scientific interest; minimizing environmental impacts on crew health; and access to resources. The report identifies functional requirements that need to be satisfied by an artificial intelligence and machine learning application and develops a final proposed system. It then presents a prototype computational model for optimizing outpost location for terrain access. A discussion of the ethical, policy and legal implications of the proposed system follows, and future extensions and improvements of the system are recommended, including applications for future off-Earth missions and the commercialization of AI as a service. |
| Contents note: | 1.Introduction 2. Background 3. Knowledge gaps 4. Design methodology 5. Discussion and recommendations 6. Roadmap 7. Conclusion 8. References 9. Appendix |
| ISU program : | Space Studies Program |
| Format : | Open Access |
| Permalink: | https://isulibrary.isunet.edu/index.php?lvl=notice_display&id=11454 |
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 2022_Test case_Executive summary (2.02MB) Adobe Acrobat PDF | 2022_Test case_Full report (3.81MB) Adobe Acrobat PDF |
