The objective of this project is to devise real-time, efficient and dependable algorithms for spacecraft autonomous maneuvering, with a special focus on dynamic and cluttered environments typically encountered during proximity operations. Specifically, this project will devise a technology for the online planning of trajectories, which together with reliable environmental sensing and autonomous high-level decision making is a key enabler for autonomous spacecraft navigation. The approach will be to leverage recent algorithmic advances in the field of robotic motion planning to spacecraft control. This will entail the study of the theoretical underpinnings for applying robotic planning algorithms to spacecraft control, and of practical algorithms for integration within the overall spacecraft autonomy module. The proposed technology has the potential to be a key enabler for both near-Earth and deep-space missions; examples include on-orbit satellite servicing and missions to satellites in the Saturnian and Uranian systems.
More »The technology has the potential to be a key enabler for both near-Earth and deep-space missions; examples include on-orbit satellite servicing and missions to satellites in the Saturnian and Uranian systems.
More »Organizations Performing Work | Role | Type | Location |
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Stanford University (Stanford) | Lead Organization | Academia | Redwood City, California |
Goddard Space Flight Center (GSFC) | Supporting Organization | NASA Center | Greenbelt, Maryland |