The Celestial Object Rendering TOol (CORTO) offers a powerful solution for generating synthetic images of celestial bodies, catering to the needs of space mission design, algorithm development, and validation. Through rendering, noise modeling, hardware-in-the-loop testing, and post-processing functionalities, CORTO creates realistic scenarios. It offers a versatile and comprehensive solution for generating synthetic images of celestial bodies, aiding the development and validation of image processing and navigation algorithms for space missions. This work illustrates its functionalities in detail for the first time. The importance of a robust validation pipeline to test the tool’s accuracy against real mission images using metrics like normalized cross-correlation and structural similarity is also illustrated. CORTO is a valuable asset for advancing space exploration and navigation algorithm development and has already proven effective in various projects, including CubeSat design, lunar missions, and deep learning applications. While the tool currently covers a range of celestial body simulations, mainly focused on minor bodies and the Moon, future enhancements could broaden its capabilities to encompass additional planetary phenomena and environments.
@article{pugliatti2023corto,title={CORTO: The Celestial Object Rendering TOol at DART Lab},author={Pugliatti, Mattia and Buonagura, Carmine and Topputo, Francesco},journal={Sensors},volume={23},pages={9595},year={2023},issn={1424-8220},doi={10.3390/s23239595},url={https://www.mdpi.com/1424-8220/23/23/9595},preprint={https://www.mdpi.com/1424-8220/23/23/9595}}
Characterization of the Ejecta from the NASA/DART Impact on Dimorphos: Observations and Monte Carlo Models
Fernando Moreno, Adriano Campo Bagatin, Gonzalo Tancredi, Jian-Yang Li, Alessandro Rossi, Fabio Ferrari, Masatoshi Hirabayashi, Eugene Fahnestock, Alain Maury, Robert Sandness, Andrew S. Rivkin, Andy Cheng, and
17 more authors
The NASA Double Asteroid Redirection Test (DART) spacecraft successfully crashed on Dimorphos, the secondary component of the binary (65803) Didymos system. Following the impact, a large dust cloud was released, and a long-lasting dust tail developed. We have extensively monitored the dust tail from the ground and the Hubble Space Telescope. We provide a characterization of the ejecta dust properties, i.e., particle size distribution and ejection speeds, ejection geometric parameters, and mass, by combining both observational data sets and using Monte Carlo models of the observed dust tail. The size distribution function that best fits the imaging data is a broken power law having a power index of –2.5 for particles of r ≤ 3 mm and –3.7 for larger particles. The particles range in size from 1 μm up to 5 cm. The ejecta is characterized by two components, depending on velocity and ejection direction. The northern component of the double tail, observed since 2022 October 8, might be associated with a secondary ejection event from impacting debris on Didymos, although is also possible that this feature results from the binary system dynamics alone. The lower limit to the total dust mass ejected is estimated at ∼6 × 106 kg, half of this mass being ejected to interplanetary space.
@article{moreno2023DART,title={Characterization of the Ejecta from the NASA/DART Impact on Dimorphos: Observations and Monte Carlo Models},author={Moreno, Fernando and Bagatin, Adriano Campo and Tancredi, Gonzalo and Li, Jian-Yang and Rossi, Alessandro and Ferrari, Fabio and Hirabayashi, Masatoshi and Fahnestock, Eugene and Maury, Alain and Sandness, Robert and Rivkin, Andrew S. and Cheng, Andy and Farnham, Tony L. and Soldini, Stefania and Giordano, Carmine and Merisio, Gianmario and Panicucci, Paolo and Pugliatti, Mattia and Castro-Tirado, Alberto J. and Fernández-García, Emilio and ignacio Pérez-García and Ivanovski, Stavro and Penttila, Antti and Kolokolova, Ludmilla and Licandro, Javier and Muñoz, Olga and Gray, Zuri and Ortiz, Jose L. and Lin, Zhong-Yi},journal={The Planetary Science Journal},volume={4},number={8},pages={138},year={2023},month=aug,doi={10.3847/PSJ/ace827},url={https://dx.doi.org/10.3847/PSJ/ace827},publisher={The American Astronomical Society},preprint={https://iopscience.iop.org/article/10.3847/PSJ/ace827}}
Onboard state estimation around Didymos with recurrent neural networks and segmentation maps
Mattia Pugliatti, Andrea Scorsoglio, Roberto Furfaro, and Francesco Topputo
IEEE Transactions on Aerospace and Electronic Systems, Aug 2023
When considering the proximity environment of a small body, the capability to navigate around it is of paramount importance to enable any onboard autonomous decision-making process. Onboard optical-based navigation is often performed by coupling image processing algorithms with filtering techniques to generate position and velocity estimates, providing compelling navigation performance with cost-effective hardware. These same processes could be addressed with data-driven ones, at the expense of a sufficiently large dataset. To investigate to what extent can these methods substitute traditional ones, in this paper we develop a possible onboard methodology based on segmentation masks, convolutional extreme learning machine architectures, and recurrent neural networks to respectively generate simpler image inputs, map single-frame data into position estimates, and process multipleframe position sequences to generate both position and velocity estimates. Considering the primary of the Didymos binary system as a case study and the possibility to complement optical observations with LiDAR data, we show that recurrent neural networks would bring only limited improvement in position reconstruction for the case considered while they would be beneficial in estimating the velocity, especially when considering complementing LiDAR data.
@article{pugliatti2023rnn,title={Onboard state estimation around Didymos with recurrent neural networks and segmentation maps},author={Pugliatti, Mattia and Scorsoglio, Andrea and Furfaro, Roberto and Topputo, Francesco},journal={IEEE Transactions on Aerospace and Electronic Systems},volume={TBD},pages={TBD},year={2023},issn={TBD},doi={10.1109/TAES.2023.3288506},url={https://ieeexplore.ieee.org/document/10159471},keywords={Image Processing, Navigation, Recurrent Neural Networks, Segmentation, Small-Bodies},preprint={https://re.public.polimi.it/handle/11311/1251839}}
The vision-based guidance, navigation, and control system of Hera’s Milani Cubesat
Mattia Pugliatti, Felice Piccolo, Antonio Rizza, Vittorio Franzese, and Francesco Topputo
Milani is a 6U CubeSat that will be released in the Didymos binary asteroid system by ESA’s Hera spacecraft. Its objectives are to study and characterize the system’s asteroids, thus demonstrating the use of miniaturized technologies for asteroid science. Milani adopts sophisticated vision-based technologies for the guidance, navigation, and control system in the asteroid’s close-proximity environment. This work elaborates on the architecture design and on the performance analysis of the image processing and the guidance, navigation, and control system of Milani, showing that they can successfully assure adequate pointing and control of the CubeSat in the Didymos environment.
@article{pugliatti2023Milani,title={The vision-based guidance, navigation, and control system of Hera’s Milani Cubesat},author={Pugliatti, Mattia and Piccolo, Felice and Rizza, Antonio and Franzese, Vittorio and Topputo, Francesco},journal={Acta Astronautica},volume={210},pages={14-28},year={2023},issn={0094-5765},doi={https://doi.org/10.1016/j.actaastro.2023.04.047},url={https://www.sciencedirect.com/science/article/pii/S0094576523002205},keywords={Guidance, navigation , and control, CubeSat, Binary asteroid, Milani, Hera},preprint={https://re.public.polimi.it/handle/11311/1236826}}
2022
Small-body segmentation based on morphological features with a u-shaped network architecture
Small bodies such as asteroids and comets display great variability in terms of surface morphological features. These are often unknown beforehand but can be employed for hazard avoidance during landing, autonomous planning of scientific observations, and navigation purposes. Algorithms performing these tasks are often data driven, which means they require realistic, sizeable, and annotated datasets, which in turn may rely heavily on human intervention. This work develops a methodology to generate synthetic, automatically labeled datasets that are used in conjunction with real, manually labeled ones to train deep-learning architectures in the task of semantic segmentation. This functionality is achieved by designing U-shaped network architectures trained with different strategies. These show good generalization capabilities, implement uncertainty quantification estimates, and can be hybridized to exploit qualities from multiple networks.
@article{pugliatti2022small,title={Small-body segmentation based on morphological features with a u-shaped network architecture},author={Pugliatti, Mattia and Maestrini, Michele},journal={Journal of Spacecraft and Rockets},volume={59},number={6},pages={1821--1835},year={2022},publisher={American Institute of Aeronautics and Astronautics},doi={10.2514/1.A35447},url={https://doi.org/10.2514/1.A35447},preprint={https://re.public.polimi.it/handle/11311/1221269}}
Data-driven image processing for onboard optical navigation around a binary asteroid
Mattia Pugliatti, Vittorio Franzese, and Francesco Topputo
In this work data-driven image processing options for a CubeSat mission around a binary asteroid system are investigated. The methods considered belong to two main branches of image processing methods: centroid and artificial intelligence. The former is represented by three variations of centroiding methods, and the latter by three neural networks and one convolutional neural network. The first contribution of this work is an enhanced center of brightness method with a data-driven scattering law. This method is demonstrated to share similarities with neural networks in terms of both design and performance, with the advantage of relying on a traditional, robust, and fully explainable algorithm. The second contribution is given by the performance assessment between the different families of image processing methods. For this purpose, the Milani mission is considered as a case study: a 6U CubeSat that will visit the Didymos system as part of the Hera mission. From this analysis, it emerges that convolutional networks perform better than other methods across all metrics considered. This hints to the importance of filtering techniques to extract spatial information from images, which is a unique feature of the convolutional approach over the other image processing methods considered.
@article{pugliatti2022data,title={Data-driven image processing for onboard optical navigation around a binary asteroid},author={Pugliatti, Mattia and Franzese, Vittorio and Topputo, Francesco},journal={Journal of Spacecraft and Rockets},volume={59},number={3},pages={943--959},year={2022},publisher={American Institute of Aeronautics and Astronautics},doi={10.2514/1.A35213},url={https://doi.org/10.2514/1.A35213},preprint={https://re.public.polimi.it/handle/11311/1196071}}
CubeSat landing simulations on small bodies using blender
Pelayo Peñarroya, Mattia Pugliatti, Fabio Ferrari, Simone Centuori, Francesco Topputo, Massimo Vetrisano, and Manuel Sanjurjo-Rivo
Landing on small-bodies is a very challenging problem that requires high degrees of robustness and autonomy. Being able to perform simulations with great flexibility and accuracy is paramount for the development and design of landing systems. To this end, contact dynamics plays a fundamental role and is often handled by complex tools that require large amount of development and validation efforts and very specific expertise. In the last decade, the Visual Effects (VFX) industry has developed numerous suites that deal with contact dynamics frameworks. In this work, the possibility of leveraging on the work of the VFX industry by using Blender, one of these tools, as the source for the contact dynamics modelling is investigated. This research focuses on the description of the methodology used for the landing simulations and the validation of the tool developed. A step-by-step guide through the simulation setup is given, discussing how the wrapping GNC simulator and Blender interact. Validation tests for the different parameters and dynamic models involved in the simulations are also presented. The results refer to the landing of a CubeSat in the crater region of an asteroid. In particular, the artificial crater that will be generated on Dimorphos by NASA’s DART impact in late September 2022, is considered in the simulations presented in this work. Safety maps are generated by post-processing these results, and are used to assess different landing strategies or site-selection criteria on the Dimorphos crater study case. Finally, the role of the developed tool in optimising the use of space resources and its contribution to landing design strategies is discussed.
@article{penarroya2022CubeSat,title={CubeSat landing simulations on small bodies using blender},journal={Advances in Space Research},year={2022},issn={0273-1177},doi={10.1016/j.asr.2022.07.044},url={https://www.sciencedirect.com/science/article/pii/S0273117722006676},author={Peñarroya, Pelayo and Pugliatti, Mattia and Ferrari, Fabio and Centuori, Simone and Topputo, Francesco and Vetrisano, Massimo and Sanjurjo-Rivo, Manuel},keywords={Landing, Blender, Contact dynamics, Asteroid, Safety map},preprint={https://re.public.polimi.it/handle/11311/1219289}}
Image Processing Robustness Assessment of Small-Body Shapes
Carmine Buonagura, Mattia Pugliatti, and Francesco Topputo
The Journal of the Astronautical Sciences, Nov 2022
Asteroids and comets are triggering interest due to the richness of precious materials, their scientifc value as well as for their potential hazardousness. Owing to their signifcant diversity, minor bodies do not exhibit uniform shapes: they can range from spherical to irregularly shaped objects with rocky, uneven, and cratered surface. Nowadays, space probes rely more and more on optical navigation techniques, due to the increasing demand for autonomy. When dealing with minor bodies, the diversifed range of shapes can signifcantly afect the performance of these techniques. In order to enable deep space probes to confdently deal with uncertainties, the need for robust image processing methods arises. Commonly, few image processing methods are designed and tested with limited shapes to meet mission requirements. In this work, we depart from this paradigm by developing a new framework, which includes extensive testing of the image processing algorithms with various shapes. The shapes are not randomly analyzed, yet they are arranged in a hierarchical structure called hyper-cube. The cube allows for a better understanding of the methods performance and to infer the way they shift from one shape to the other. The novelty of this approach lies both in the cube representation, which allows a better understanding of the link between the image processing algorithms and shape of the object, but also in the extensive number of shapes that have been tested, which has never been done before. In this analysis, four methods are considered, namely: center of brightness, intensity weighted centroiding, correlation with Lambertian spheres, and least-squares-based ellipse ftting. Results from this test allow us correlating the methods performances to the bodies shape, to suggest the best performing method for each shape family, and to assess their robustness.
@article{Buonagura2022image,doi={10.1007/s40295-022-00348-6},url={https://doi.org/10.1007/s40295-022-00348-6},year={2022},month=nov,publisher={Springer Science and Business Media {LLC}},volume={69},number={6},pages={1744--1765},author={Buonagura, Carmine and Pugliatti, Mattia and Topputo, Francesco},title={Image Processing Robustness Assessment of Small-Body Shapes},journal={The Journal of the Astronautical Sciences},preprint={https://re.public.polimi.it/handle/11311/1223556}}
2021
Preliminary mission profile of Hera’s Milani CubeSat
Fabio Ferrari, Vittorio Franzese, Mattia Pugliatti, Carmine Giordano, and Francesco Topputo
CubeSats offer a flexible and low-cost option to increase the scientific and technological return of small-body exploration missions. ESA’s Hera mission, the European component of the Asteroid Impact and Deflection Assessment (AIDA) international collaboration, plans on deploying two CubeSats in the proximity of binary system 65803 Didymos, after arrival in 2027. In this work, we discuss the feasibility and preliminary mission profile of Hera’s Milani CubeSat. The CubeSat mission is designed to achieve both scientific and technological objectives. We identify the design challenges and discuss design criteria to find suitable solutions in terms of mission analysis, operational trajectories, and Guidance, Navigation, & Control (GNC) design. We present initial trajectories and GNC baseline, as a result of trade-off analyses. We assess the feasibility of the Milani CubeSat mission and provide a preliminary solution to cover the operational mission profile of Milani in the close-proximity of Didymos system.
@article{ferrari2021preliminary,title={Preliminary mission profile of Hera’s Milani CubeSat},author={Ferrari, Fabio and Franzese, Vittorio and Pugliatti, Mattia and Giordano, Carmine and Topputo, Francesco},journal={Advances in Space Research},volume={67},number={6},pages={2010--2029},year={2021},publisher={Elsevier},doi={10.1016/j.asr.2020.12.034},url={https://doi.org/10.1016/j.asr.2020.12.034},preprint={https://re.public.polimi.it/handle/11311/1157810}}
Trajectory options for Hera’s Milani cubesat around (65803) Didymos
Fabio Ferrari, Vittorio Franzese, Mattia Pugliatti, Carmine Giordano, and Francesco Topputo
The Journal of the Astronautical Sciences, Nov 2021
The dynamical environment in the close-proximity of small celestial bodies is characterized by a very weak and irregular gravity field. In this low-acceleration deep-space environment, small dynamical perturbations might affect significantly the dynamics of a spacecraft hovering near the surface of such objects. This poses a challenge to the efficient design of trajectories of space probes for space missions aimed at the exploration of small Solar System bodies. This applies especially to CubeSats, small spacecraft with limited autonomy and maneuvering capabilities. In this case, a careful and efficient design of the operational trajectory is mandatory to accomplish the objective of the mission. As a representative and timely case study, we investigate the dynamics around binary asteroid (65803) Didymos, the target of NASA’s Double Asteroid Redirection Test (DART) and ESA’s Hera missions. We analyze all the relevant dynamical contributions concurring to the acceleration environment near Didymos and provide a subdivision of it into subregions, each identified by a different dynamical regime. With reference to the Hera Milani CubeSat mission scenario, we describe the methodology and design approach to find trajectories in the dayside of Didymos system. Finally, we provide examples of suitable trajectory options to host the operational phase of the Hera Milani CubeSat.
@article{ferrari2021trajectory,title={Trajectory options for Hera’s Milani cubesat around (65803) Didymos},author={Ferrari, Fabio and Franzese, Vittorio and Pugliatti, Mattia and Giordano, Carmine and Topputo, Francesco},journal={The Journal of the Astronautical Sciences},volume={68},number={4},pages={973--994},year={2021},publisher={Springer},doi={10.1007/s40295-021-00282-z},url={https://doi.org/10.1007/s40295-021-00282-z},preprint={https://re.public.polimi.it/handle/11311/1183684}}
