Space Navigator: a Tool for the Optimization of Collision Avoidance Maneuvers

Autor:	Gremyachikh, Leonid, Dubov, Dmitrii, Kazeev, Nikita, Kulibaba, Andrey, Skuratov, Andrey, Tereshkin, Anton, Ustyuzhanin, Andrey, Shiryaeva, Lubov, Shishkin, Sergej
Rok vydání:	2019
Předmět:	Electrical Engineering and Systems Science - Systems and Control Computer Science - Machine Learning
Zdroj:	Advances in the Astronautical Sciences 2020 First IAA/AAS SciTech Forum on Space Flight Mechanics and Space Structures and Materials Conference, volume 170
Druh dokumentu:	Working Paper
Popis:	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. Comment: Submitted to AAS Advances in the Astronautical Sciences, presented at IAA SciTech Forum 2018
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1902.02095 Zobrazit plný text záznamu View this record from Arxiv