Speaker
Description
Even with the adoption of increasingly more demanding regulations to curb the generation of debris by space missions, both during operations and at end-of-life, the congestion of commercially relevant orbital regions such as LEO is expected to increase due to two main drivers. First, the existing population of debris will continue to pose a threat, and their number can keep increasing through collisional and fragmentation events. Second, the adoption of large constellations as technological solution for certain uses such as broadband internet access increases the number of active objects, clustered in specific regions of space. Therefore, collision avoidance remains a key pillar in space debris mitigation activities.
A promising approach to deal with this growing congestion is autonomous collision avoidance, where the satellite has the capability to plan and design a collision avoidance manoeuvre based on SSA information received from external sources and its own navigation data. However, this requires algorithms that are both robust, so a valid solution is always reached, and algorithmically lightweight, so they can be executed on board.
In this talk, recent advances in impulsive and low-thrust collision avoidance models suitable for autonomous on-board execution are presented. The trade-off between accuracy, optimality, and robustness is discussed, considering also the key feature of being flexible enough to accommodate the main operational constraints. We will also show an overview or recent projects where these models have been used as part of autonomous collision avoidance pipelines, and how this application has driven the development roadmap. The performance of the models will be shown through sample cases, discussing their current limitations and way forward for development.
| Which section would you like to submit your abstract to? | Session 4: “How space debris mitigation can adapt to the space environment?” |
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