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.
Experimental Validation of Synthetic Training Set for Deep Learning Vision-Based Navigation Systems for Lunar Landing
Stefano Silvestrini;Paolo Lunghi;Margherita Piccinin;Giovanni Zanotti;Michele Lavagna
2020-01-01
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.File in questo prodotto:
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