The problem of nonlinear uncertainty propagation represents a crucial issue in celestial mechanics. In this paper, a method for nonlinear propagation of uncertainty based on differential algebra is presented. Working in the differential algebra framework enables a general approach to nonlinear uncertainty propagation that can provide highly accurate estimate with low computational cost. The nonlinear mapping of the statistics is shown here, adopting the two-body problem as the working framework, including coordinate system transformations. The general feature of the proposed method is also demonstrated by presenting long-term integrations in complex dynamic systems, such as the n-body problem or the simplified general perturbation model.

The growing interest in Artificial Intelligence is pervading several domains of technology and robotics research. Only recently has the space community started to investigate deep learning methods and artificial neural networks for space systems. This paper aims at introducing the most relevant characteristics of these topics for spacecraft dynamics control, guidance and navigation. The most common artificial neural network architectures and the associated training methods are examined, trying to highlight the advantages and disadvantages of their employment for specific problems. In particular, the applications of artificial neural networks to system identification, control synthesis and optical navigation are reviewed and compared using quantitative and qualitative metrics. This overview presents the end-to-end deep learning frameworks for spacecraft guidance, navigation and control together with the hybrid methods in which the neural techniques are coupled with traditional algorithms to enhance their performance levels.

The smallest member of the Didymos binary near-Earth object system (Dimorphos) is the target of the DART/LICIACube mission, the first attempt to change the orbit of another celestial body via a kinetic impactor. It is important to characterize the unperturbed system prior to the DART impact. In this work we obtained, for the first time, spectral characterization of the system at several rotational phases from TNG+DOLORES in the visible range (0.34–0.81 μm). This is crucial in order to disentangle the primary and secondary bodies and highlight eventual dishomogeneities on their surfaces. We confirm that a subtle but persistent spectral variability appears, even when compared with data obtained from previous 2003 and 2019 apparitions. While the reason for such variability is still under investigation, our analysis hints that different compositions could play a role. Future observations during the brighter 2022 apparition in synergy with data obtained from LUKE on board LICIACube will definitely tackle this conundrum.