Periodic Reporting for period 2 - Stardust-R (Stardust Reloaded)
Reporting period: 2021-01-01 to 2023-06-30
Stardust-R addresses the growing need for a sustainable exploitation of space, the resilience of the space environment, the threat and opportunities coming from asteroids and comets.
Asteroids and space debris represent a significant hazard for both space and terrestrial assets, but they also represent an important commercial and scientific opportunity. From the exploitation of in-situ resources on asteroids, to on orbit servicing, from the exploration and characterisation of minor bodies to advanced concepts like the Phoenix programme of DARPA, both asteroids and space debris represent one of the most interesting challenges of space science and technology. Some scholars theorise that the Kessler syndrome (where the density of objects in orbit is high enough that collisions could set off a cascade) has already begun and is simply proceeding at a slow pace. Furthermore, current plans to inject increasingly larger constellations of small satellites into space and the emergence of the New Space trend, will critically increase the traffic. This requires a substantially new approach to collision avoidance and satellite operations, even before thinking of debris removal and satellite disposal. The impact on the space environment is going to be unprecedented, posing a serious question on its stability and resilience to any incident or anomalous event.
Although statistically less likely to occur, an asteroid impact would have devastating consequences for our planet. An impact with a large to medium (~10 km to ~300 m diameter) asteroid is unlikely, but not negligible and the long-term prediction of the probability of an impact is not a trivial matter. Furthermore, impacts with smaller size objects, between 10 m to 100 m diameter, are expected to occur more frequently and hence are, proportionally, equally dangerous for humans and assets on Earth and in space.
The aim of Stardust-R is to develop enabling technologies and effective solutions to critical and emerging problems in planetary defence, minor body exploration and the sustainable exploitation of space.
The key scientific objectives are: 1) to globally characterise the dynamics of objects around the Earth to define disposal solutions, 2) to correlate spatially and temporally distant events and families of debris to their parent object, 3) to quantify uncertainty in celestial mechanics to accurately predict the probability of impact and collision and quantify the resilience of space systems and environment, 4) to develop tools and methods for space traffic management, 5) to define a criticality index for small asteroids to identify the need for exploration/characterisation, the possibility for exploitation and the method of deflection, 6) to develop a new distribution model for small size asteroids(<100m), 7) to develop systems and algorithms to explore and land on minor bodies with small spacecraft.
Conclusions of the Action
By the end of the action and despite COVID, Stardust-R achieved most of the planned objectives and developed essential tools and capabilities to support the sustainable use of space, manage the space environment, and explore minor bodies in view of future planetary defence missions but also in view of a future sustainable exploitation of their resources.
Asteroids and space debris represent a significant hazard for both space and terrestrial assets, but they also represent an important commercial and scientific opportunity. From the exploitation of in-situ resources on asteroids, to on orbit servicing, from the exploration and characterisation of minor bodies to advanced concepts like the Phoenix programme of DARPA, both asteroids and space debris represent one of the most interesting challenges of space science and technology. Some scholars theorise that the Kessler syndrome (where the density of objects in orbit is high enough that collisions could set off a cascade) has already begun and is simply proceeding at a slow pace. Furthermore, current plans to inject increasingly larger constellations of small satellites into space and the emergence of the New Space trend, will critically increase the traffic. This requires a substantially new approach to collision avoidance and satellite operations, even before thinking of debris removal and satellite disposal. The impact on the space environment is going to be unprecedented, posing a serious question on its stability and resilience to any incident or anomalous event.
Although statistically less likely to occur, an asteroid impact would have devastating consequences for our planet. An impact with a large to medium (~10 km to ~300 m diameter) asteroid is unlikely, but not negligible and the long-term prediction of the probability of an impact is not a trivial matter. Furthermore, impacts with smaller size objects, between 10 m to 100 m diameter, are expected to occur more frequently and hence are, proportionally, equally dangerous for humans and assets on Earth and in space.
The aim of Stardust-R is to develop enabling technologies and effective solutions to critical and emerging problems in planetary defence, minor body exploration and the sustainable exploitation of space.
The key scientific objectives are: 1) to globally characterise the dynamics of objects around the Earth to define disposal solutions, 2) to correlate spatially and temporally distant events and families of debris to their parent object, 3) to quantify uncertainty in celestial mechanics to accurately predict the probability of impact and collision and quantify the resilience of space systems and environment, 4) to develop tools and methods for space traffic management, 5) to define a criticality index for small asteroids to identify the need for exploration/characterisation, the possibility for exploitation and the method of deflection, 6) to develop a new distribution model for small size asteroids(<100m), 7) to develop systems and algorithms to explore and land on minor bodies with small spacecraft.
Conclusions of the Action
By the end of the action and despite COVID, Stardust-R achieved most of the planned objectives and developed essential tools and capabilities to support the sustainable use of space, manage the space environment, and explore minor bodies in view of future planetary defence missions but also in view of a future sustainable exploitation of their resources.
The research, training and outreach programmes within Stardust-R started in December 2019 when recruitment of all 15 ESR was completed.
Since then Stardust-R completed all the training events and organised a number of outreach events to raise awareness and communicate to the general public. One of which during COP26.
The scientists in charge in Stardust-R played a pivotal role within their respective counties an on the international scene through the UN Space Mission Planning Advisory Group and the Inter-Agency Space Debris Coordination Committee.
During both reporting periods a number of outreach events have been organised including 3 public lectures, several school visits, podcast, Instagram account, etc. http://www.stardust-network.eu/outreach/.
Some major results were achieved in the use of AI and machine learning for space traffic management, the analysis of re-entry and demise of space objects and the understanding of the evolution of the space environment with a new model base don network theory.
Further key results were achieved in our understanding of the chaotic and regular motion of space objects and our understanding of the evolution of space debris fragments. Stardust-R achieved significant results also on our understanding of the dynamics of small asteroids and the criticality of some of them for planetary defence, resource exploitation and scientific exploration. Stardust-R pushed the boundary of small satellite technology for minor body exploration and achieved significant results on the use of machine learning for autonomy. Key advancements were also obtained on in orbit servicing and robotics for space sustainability.
Many of the achievements of Stardust can be found on the the project website (http://www.stardust-network.eu) and Twitter account (@Stardust_H2020).
Since then Stardust-R completed all the training events and organised a number of outreach events to raise awareness and communicate to the general public. One of which during COP26.
The scientists in charge in Stardust-R played a pivotal role within their respective counties an on the international scene through the UN Space Mission Planning Advisory Group and the Inter-Agency Space Debris Coordination Committee.
During both reporting periods a number of outreach events have been organised including 3 public lectures, several school visits, podcast, Instagram account, etc. http://www.stardust-network.eu/outreach/.
Some major results were achieved in the use of AI and machine learning for space traffic management, the analysis of re-entry and demise of space objects and the understanding of the evolution of the space environment with a new model base don network theory.
Further key results were achieved in our understanding of the chaotic and regular motion of space objects and our understanding of the evolution of space debris fragments. Stardust-R achieved significant results also on our understanding of the dynamics of small asteroids and the criticality of some of them for planetary defence, resource exploitation and scientific exploration. Stardust-R pushed the boundary of small satellite technology for minor body exploration and achieved significant results on the use of machine learning for autonomy. Key advancements were also obtained on in orbit servicing and robotics for space sustainability.
Many of the achievements of Stardust can be found on the the project website (http://www.stardust-network.eu) and Twitter account (@Stardust_H2020).
Progress beyond the state of the art has been made in different directions.
Cutting edge computational intelligence techniques to multiple aspects of the resilience of the space environment. More concretely, novel neural network architectures have been employed in the task of forecasting space weather indices, and to build reduced order models of the atmospheric density. Deep symbolic regression was used to model epistemic uncertainty in the dynamic model of space objects.
Progress have been made on the characterization of the regular and chaotic dynamics, as well as the theoretical modelling and exploration of disposal strategies near lunisolar resonances for space debris at MEO, on the study of the orbital and rotational dynamics of a variety of space objects, on the use of machine learning in Celestial Mechanics, and on the study of the effect of lunisolar perturbations on highly eccentric orbits (HEO) and highly inclined orbits, and on the resonances connected to the effect of solar radiation pressure.
On the dynamics of small asteroids we identified the mechanisms that may affect especially the transport of small asteroids from the main belt, between Mars and Jupiter, to the vicinity of Earth.
Advanced machine learning techniques have been developed for Image segmentation, and for navigation about irregular bodies.
On the sustainability of the space environment good progress have been made on a problem often disregarded in the study of sustainable operations in a high traffic environment, due to its large scale. This is the all versus all problem, in which, instead of placing the focus on the potential high risk collisions of one single object versus the rest of the catalogue, the whole catalogue of objects is analysed. To reduce the computational complexity of this problem, the use of AI techniques is being investigated.
Stardust-R also enabled the development of key tools for the analysis of the evolution of the space environment, NESSY, the analysis of re-entry, TITAN, the analysis of collision events, CASSANDRA, and the analysis of fragmentations and debris propagation, SIMPRO.
All these tools have found applications outside Stardust-R and are now under further development through the national space agencies and ESA.
Cutting edge computational intelligence techniques to multiple aspects of the resilience of the space environment. More concretely, novel neural network architectures have been employed in the task of forecasting space weather indices, and to build reduced order models of the atmospheric density. Deep symbolic regression was used to model epistemic uncertainty in the dynamic model of space objects.
Progress have been made on the characterization of the regular and chaotic dynamics, as well as the theoretical modelling and exploration of disposal strategies near lunisolar resonances for space debris at MEO, on the study of the orbital and rotational dynamics of a variety of space objects, on the use of machine learning in Celestial Mechanics, and on the study of the effect of lunisolar perturbations on highly eccentric orbits (HEO) and highly inclined orbits, and on the resonances connected to the effect of solar radiation pressure.
On the dynamics of small asteroids we identified the mechanisms that may affect especially the transport of small asteroids from the main belt, between Mars and Jupiter, to the vicinity of Earth.
Advanced machine learning techniques have been developed for Image segmentation, and for navigation about irregular bodies.
On the sustainability of the space environment good progress have been made on a problem often disregarded in the study of sustainable operations in a high traffic environment, due to its large scale. This is the all versus all problem, in which, instead of placing the focus on the potential high risk collisions of one single object versus the rest of the catalogue, the whole catalogue of objects is analysed. To reduce the computational complexity of this problem, the use of AI techniques is being investigated.
Stardust-R also enabled the development of key tools for the analysis of the evolution of the space environment, NESSY, the analysis of re-entry, TITAN, the analysis of collision events, CASSANDRA, and the analysis of fragmentations and debris propagation, SIMPRO.
All these tools have found applications outside Stardust-R and are now under further development through the national space agencies and ESA.