44 citations · 68 across the 7 of their papers we have counts for
7 papers
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…
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…
Towards Robust Spacecraft Trajectory Optimization via Transformers
Yuji Takubo, Tommaso Guffanti, Daniele Gammelli +2
Future multi-spacecraft missions require robust autonomous trajectory optimization capabilities to ensure safe and efficient rendezvous operations. This capability hinges on solvin…
Space-LLaVA: a Vision-Language Model Adapted to Extraterrestrial Applications
Matthew Foutter, Daniele Gammelli, Justin Kruger +5
Foundation Models (FMs), e.g., large language models, possess attributes of intelligence which offer promise to endow a robot with the contextual understanding necessary to navigat…
Transformers for Trajectory Optimization with Application to Spacecraft Rendezvous
Tommaso Guffanti, Daniele Gammelli, Simone D'Amico +1
Reliable and efficient trajectory optimization methods are a fundamental need for autonomous dynamical systems, effectively enabling applications including rocket landing, hyperson…
Autonomous Guidance Navigation and Control of the VISORS Formation-Flying Mission
Tommaso Guffanti, Toby Bell, Samuel Y. W. Low +2
Virtual Super-resolution Optics with Reconfigurable Swarms (VISORS) is a distributed telescope mission for high-resolution imaging of the Sun using two 6U CubeSats flying in format…
Passively-Safe and Robust Multi-Agent Optimal Control with Application to Distributed Space Systems
Tommaso Guffanti, Simone D'Amico
This paper presents a novel methodology to enforce motion safety guarantees even in the event of a sudden loss of control capabilities by any agent within a multi-agent system. Thi…