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Minor bodies exhibit considerable variability in shape and surface morphology, posing challenges for spacecraft operations, which are further compounded by highly non-linear dynamics and limited communication windows with Earth. Additionally, uncertainties persist in the shape and surface morphology of minor bodies due to errors in ground-based estimation techniques. The growing need for autonomy underscores the importance of robust image processing and visual-based navigation methods. To address this demand, it is essential to conduct tests on a variety of body shapes and with different surface morphological features. This work introduces the procedural Minor bOdy geNErator Tool (MONET), implemented using an open-source 3D computer graphics software. The starting point of MONET is the three-dimensional mesh of a generic minor body, which is procedurally modified by introducing craters, boulders, and surface roughness, resulting in a photorealistic model. MONET offers the flexibility to generate a diverse range of shapes and surface morphological features, aiding in the recreation of various minor bodies. Users can fine-tune relevant parameters to create the desired conditions based on the specific application requirements. The tool offers the capability to generate two default families of models: rubble-pile, characterized by numerous different-sized boulders, and comet-like, reflecting the typical morphology of comets. MONET serves as a valuable resource for researchers and engineers involved in minor body exploration missions and related projects, providing insights into the adaptability and effectiveness of guidance and navigation techniques across a wide range of morphological scenarios.
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Detecting celestial bodies while in deep-space travel is a critical task for the correct execution of space missions. Major bodies such as planets are bright and therefore easy to observe, while small bodies can be faint and therefore difficult to observe. A critical task for both rendezvous and fly-by missions is to detect asteroid targets, either for relative navigation or for opportunistic observations. Traditional, large spacecraft missions can detect small bodies from far away, owing to the large aperture of the onboard optical cameras. This is not the case for deep-space miniaturized satellites, whose small-aperture cameras pose new challenges in detecting and tracking the line-of-sight directions to small bodies. This paper investigates the celestial bodies far-range detection limits for deep-space CubeSats, suggesting active measures for small bodies detection. The M-ARGO CubeSat mission is considered as the study case for this activity. The analyses show that the detection of small asteroids (with absolute magnitude fainter than 24) is expected to be in the range of 30,000-50,000 km, exploiting typical miniaturized cameras for deep-space CubeSats. Given the limited detection range, this paper recommends to include a zero-phase-angle way point at close range in the mission design phase of asteroid rendezvous missions exploiting deep-space CubeSats to allow detection.
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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.
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The increase in number of interplanetary probes has emphasized the need for spacecraft autonomy to reduce overall mission costs and to enable riskier operations without ground support. The perception of the external environment is a critical task for autonomous probes, being fundamental for both motion planning and actuation. Perception is often achieved using navigation sensors which provide measurements of the external environment. For space exploration purposes, cameras are among the sensors that provide navigation information with few constraints at the spacecraft system level. Image processing and vision-based navigation algorithms are exploited to extract information about the external environment and the probe's position within it from images. It is thus crucial to have the capability to generate realistic image datasets to design, validate, and test autonomous algorithms. This goal is achieved with high-fidelity rendering engines and with hardware-in-the-loop simulations. This work focuses on the latter by presenting a facility developed and used at the Deep-space Astrodynamics Research and Technology (DART) Laboratory at Politecnico di Milano. First, the facility design relationships are established to select hardware components. The critical design parameters of the camera, lens system, and screen are identified and analytical relationships are developed among these parameters. Second, the performances achievable with the chosen components are analytically and numerically studied in terms of geometrical accuracy and optical distortions. Third, the calibration procedures compensating for hardware misalignment and errors are defined. Their performances are evaluated in a laboratory experiment to display the calibration quality. Finally, the facility applicability is demonstrated by testing imageprocessing algorithms for space exploration scenarios.
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Algoritmos , Processamento de Imagem Assistida por Computador , Astronave , Visão Ocular , ComputadoresRESUMO
MOTIVATION: Although results from phase III clinical trials substantially support the use of prophylactic and therapeutic vaccines against cancer, what has yet to be defined is how many and how frequent boosts are needed to sustain a long-lasting and protecting memory T-cell response against tumor antigens. Common experience is that such preclinical tests require the sacrifice of a relatively large number of animals, and are particularly time- and money-consuming. RESULTS: As a first step to overcome these hurdles, we have developed an ordinary differential equation model that includes all relevant entities (such as activated cytotoxic T lymphocytes and memory T cells), and investigated the induction of immunological memory in the context of wild-type mice injected with a dendritic cell-based vaccine. We have simulated the biological behavior both in the presence and in the absence of memory T cells. Comparing results of ex vivo and in silico experiments, we show that the model is able to envisage the expansion and persistence of antigen-specific memory T cells. The model might be applicable to more complex vaccination schedules and substantially in any biological condition of prime-boosting. AVAILABILITY AND IMPLEMENTATION: The model is fully described in the article.
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Células Dendríticas/imunologia , Memória Imunológica , Linfócitos T/imunologia , Animais , Antígenos/imunologia , Vacinas Anticâncer/imunologia , Memória Imunológica/imunologia , Camundongos Endogâmicos C57BL , Vacinas/imunologiaRESUMO
Stand-alone deep-space CubeSats are the future of the space sector. For limited budget reasons, these spacecraft need to follow operational-compliant (OC) trajectories: transfers with thrusting and coasting periods imposed at pre-defined time instants. Traditional trajectory optimisation algorithms exhibit convergence problems when handling discontinuous constraints. In this work, a homotopic direct collocation approach is presented. It employs a continuation algorithm that maps the classical bang-bang trajectory of a fuel-optimal low-thrust problem into an OC solution. M-ARGO CubeSat mission is considered as case study for validation, including a realistic thruster model with variable specific impulse and maximum thrust. The trajectories computed with the developed algorithm are compared with non-operational-compliant solutions. Our algorithm produces transfers similar to the optimal solutions with no operational constraint, both in terms of thrusting profile and propellant mass.
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In the frame of the lunar exploration, numerous future space missions will require maximization of payload mass, and simultaneously achieving reasonable transfer times. To fulfill this request, low energy non-Keplerian orbits could be used to reach the Moon instead of high energetic transfers. The low energy solutions can be separated into two main categories depending on the nature of the trajectory approaching the Moon: low energy transit orbits that approach the Moon from the interior equilibrium point L(1) and weak stability boundary transfers that reach the Moon after passing through L(2). This paper proposes an alternative way to exploit the opportunities offered by L(1) transit orbits for the design of Earth-Moon transfers. First, in a neighborhood of the L(1) point, the three-body dynamics is linearized and written in normal form; then the entire family of nonlinear transit orbits is obtained by selecting the appropriate nontrivial amplitudes associated with the hyperbolic part. The L(1)-Earth arc is close to a 5:2 resonant orbit with the Moon, whose perturbations cause the apogee to rise. In a second step, two selected low altitude parking orbits around the Earth and the Moon are linked with the transit orbit by means of two three-body Lambert arcs, solutions of two two-point boundary value problems. The resulting Earth-to-Moon trajectories prove to be very efficient in the Moon captured arc and save approximately 100 m/sec in Deltav cost when compared to the Hohmann transfer. Furthermore, such solutions demonstrate that Moon capture could be obtained in the frame of the Earth-Moon R3BP neglecting the presence of the Sun.