Experimental Validation of Synthetic Training Set for Deep Learning Vision-Based Navigation Systems for Lunar Landing

Abstract

A vision-based navigation system using AI to solve the task of pinpoint landing on the Moon is being developed at Politecnico di Milano - ASTRA research team. The Moon landing scenario consists in the spacecraft descent on the South Pole from an altitude of 100 km down to 3 km. A 2D planar Moon landing is taken as reference. This paper presents the strategy for the dataset generation for both training and validation, which includes synthetic images and data acquired in ARGOS robotic facility at Politecnico di Milano.

Paolo Lunghi

Assistant Professor of Aerospace Systems

Aiming for autonomous Guidance, Navigation, and Control for spacecraft.