Towards a Taxonomy for Automatic and Autonomous Cooperative Spacecraft Maneuvering in a Space Traffic Management Framework
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
King Abdullah University Of Science and Technology, Thuwal, Saudi Arabia
Online Publication Date2020-11-02
Print Publication Date2020-11-16
Permanent link to this recordhttp://hdl.handle.net/10754/666043
MetadataShow full item record
AbstractAs the number of objects in Earth orbit continues to grow, automatic maneuvering of spacecraft may play an important role in a comprehensive space traffic management framework. Automatic collision avoidance, rendezvous and proximity operations, and station keeping are all possible spacecraft missions where two or more spacecraft may interact in an automatic maneuver scenario. Interaction may be limited to awareness of state information such as the other object’s position and velocity relative to an ownship position and velocity, or it may be as extensive as two spacecraft that communicate and coordinate maneuvers to optimize resource use while still meeting mission objectives. Before standards and policies can be determined, a common vocabulary describing spacecraft interactions is needed. This paper proposes a spacecraft maneuver taxonomy that provides a common set of definitions for categories of spacecraft interactions, maneuver coordination, intent, and maneuver efficiency, as well as related concepts such as centralized, distributed, and hierarchical control. It is envisioned that this taxonomy will provide a basis for specifications, planning, coordination, and on-orbit synchronization of spacecraft automatic maneuvering.
CitationHobbs, K., Collins, A. R., & Feron, E. (2020). Towards a Taxonomy for Automatic and Autonomous Cooperative Spacecraft Maneuvering in a Space Traffic Management Framework. ASCEND 2020. doi:10.2514/6.2020-4240
SponsorsThe authors would like to thank Alwyn Goodloe, Paul Minor, Ivan Perez, Natasha Neogi, Eloy Garcia, David Casbeer, Derek Kingston, Laura Humphrey, Adam Gerlach, and Ryan Weismann for enlightening conversations that inspired the development of this taxonomy.