Research/ SPACE AI & AUTONOMY
Space Navigator: a Tool for the Optimization of Collision Avoidance Maneuvers
Leonid Gremyachikh, Dmitrii Dubov, Nikita Kazeev, Andrey Kulibaba, Andrey Skuratov, Anton Tereshkin, Andrey Ustyuzhanin, Lubov Shiryaeva, Sergej Shishkin
Motion Planning & NavigationOpenAlex topic: Robotic Path Planning Algorithms · Guidance, Dynamics & ControlarXiv: eess.SY · Learning-based MethodsarXiv: cs.LG
arXiveess.SY · cs.LG · cs.SYOpenAlexSpace Satellite Systems and Control · Spacecraft Dynamics and Control · Robotic Path Planning Algorithms
The number of space objects will grow several times in a few years due to the planned launches of constellations of thousands microsatellites. It leads to a significant increase in the threat of satellite collisions. Spacecraft must undertake collision avoidance maneuvers to mitigate the risk. According to publicly available information, conjunction events are now manually handled by operators on the Earth. The manual maneuver planning requires qualified personnel and will be impractical for constellations of thousands satellites. In this paper we propose a new modular autonomous collision avoidance system called "Space Navigator". It is based on a novel maneuver optimization approach that combines domain knowledge with Reinforcement Learning methods.
Comments: Submitted to AAS Advances in the Astronautical Sciences, presented at IAA SciTech Forum 2018
Journal ref: Advances in the Astronautical Sciences 2020 First IAA/AAS SciTech Forum on Space Flight Mechanics and Space Structures and Materials Conference, volume 170