2 papers
cs.RO2024
Transformer-based Model Predictive Control: Trajectory Optimization via Sequence Modeling
Davide Celestini, Daniele Gammelli, Tommaso Guffanti +3
Model predictive control (MPC) has established itself as the primary methodology for constrained control, enabling general-purpose robot autonomy in diverse real-world scenarios. H…
cs.RO2024
Generalizable Spacecraft Trajectory Generation via Multimodal Learning with Transformers
Davide Celestini, Amirhossein Afsharrad, Daniele Gammelli +6
Effective trajectory generation is essential for reliable on-board spacecraft autonomy. Among other approaches, learning-based warm-starting represents an appealing paradigm for so…