Supporting Material for "An AI-assisted Vision-based Navigation Approach for Pinpoint Lunar Landing: Development, Validation and Testing"

This dataset contains the simulated landing trajectory of a lunar lander in addition to synthetic images collected by the onboard navigation camera. The materials support the study "An AI-assisted Vision-based Navigation Approach for Pinpoint Lunar Landing: Development, Validation and Testing". The dataset contains the following files: trajMCI.csv: spacecraft trajectory with respect to Moon-Centered Inertial (MCI) frame image_acquisition.csv: image acquisition epoch (in seconds past J2000) and associated frame ID camera.yaml: camera parameters moon-viper-IMU100Hz-CAM1Hz-100x30km-Batch1.zip: 1st image batch (#1000-1999) + auxiliary info moon-viper-IMU100Hz-CAM1Hz-100x30km-Batch2.zip: 2nd image batch (#2000-2999) + auxiliary info moon-viper-IMU100Hz-CAM1Hz-100x30km-Batch3.zip: 3rd image batch (#3000-3963) + auxiliary info Citation. S. Andolfo, M. El Awag, F. V. Buonomo, A. M. Gargiulo, L. Cavalieri & A. Genova (2025) "An AI-assisted Vision-based Navigation Approach for Pinpoint Lunar Landing: Development, Validation and Testing," 2025 AIAA/AAS Astrodynamics Specialist Conference, AAS 25-820, Boston, MA, USA.