A modular framework combining reinforcement-learned routing with sequential convex programming designs near-optimal multi-rendezvous trajectories, demonstrated on the OSSIE orbital tug mission.
Large- scale object selection and trajectory planning for multi-target space debris removal missions,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SY 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Design And Optimization Of Multi-rendezvous Manoeuvres Based On Reinforcement Learning And Convex Optimization
A modular framework combining reinforcement-learned routing with sequential convex programming designs near-optimal multi-rendezvous trajectories, demonstrated on the OSSIE orbital tug mission.