Daniele Gammelli

According to our database, Daniele Gammelli authored at least 28 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

GRAND: Guidance, Rebalancing, and Assignment for Networked Dispatch in Multi-Agent Path Finding.

Johannes Gaber, Meshal Alharbi, Daniele Gammelli, Gioele Zardini

IEEE Robotics Autom. Lett., May, 2026

Accelerating High-Capacity Ridepooling in Robo-Taxi Systems.

Xinling Li, Daniele Gammelli, Alex Wallar, Jinhua Zhao, Gioele Zardini

IEEE Robotics Autom. Lett., March, 2026

Competitive Multi-Operator Reinforcement Learning for Joint Pricing and Fleet Rebalancing in AMoD Systems.

Emil Kragh Toft, Carolin Schmidt, Daniele Gammelli, Filipe Rodrigues

CoRR, March, 2026

Graph Neural Model Predictive Control for High-Dimensional Systems.

Patrick Benito Eberhard, Luis A. Pabon, Daniele Gammelli, Hugo Buurmeijer, Amon Lahr, Mark Leone, Andrea Carron, Marco Pavone

CoRR, February, 2026

Reproducibility in the Control of Autonomous Mobility-on-Demand Systems.

Xinling Li, Meshal Alharbi, Daniele Gammelli, James Harrison, Filipe Rodrigues, Maximilian Schiffer, Marco Pavone, Emilio Frazzoli, Jinhua Zhao, Gioele Zardini

IEEE Trans. Robotics, 2026

2025

Semantic Trajectory Generation for Goal-Oriented Spacecraft Rendezvous.

Yuji Takubo, Arpit Dwivedi, Sukeerth Ramkumar, Luis A. Pabon, Daniele Gammelli, Marco Pavone, Simone D'Amico

CoRR, December, 2025

Multi-Timescale Model Predictive Control for Slow-Fast Systems.

Lukas Schroth, Daniel Morton, Amon Lahr, Daniele Gammelli, Andrea Carron, Marco Pavone

CoRR, November, 2025

Learning Joint Rebalancing and Dynamic Pricing Policies for Autonomous Mobility-on-Demand.

Xinling Li, Carolin Schmidt, Daniele Gammelli, Filipe Rodrigues

IEEE Trans. Intell. Transp. Syst., October, 2025

Agile Tradespace Exploration for Space Rendezvous Mission Design via Transformers.

Yuji Takubo, Daniele Gammelli, Marco Pavone, Simone D'Amico

CoRR, October, 2025

Vision Foundation Model Embedding-Based Semantic Anomaly Detection.

Max Peter Ronecker, Matthew Foutter, Amine Elhafsi, Daniele Gammelli, Ihor Barakaiev, Marco Pavone, Daniel Watzenig

CoRR, May, 2025

Robo-taxi Fleet Coordination at Scale via Reinforcement Learning.

Luigi Tresca, Carolin Schmidt, James Harrison, Filipe Rodrigues, Gioele Zardini, Daniele Gammelli, Marco Pavone

CoRR, April, 2025

Learning Traffic Flows: Graph Neural Networks for Metamodelling Traffic Assignment.

Oskar Bohn Lassen, Serio Agriesti, Mohamed Eldafrawi, Daniele Gammelli, Guido Cantelmo, Guido Gentile, Francisco Câmara Pereira

Proceedings of the 9th International Conference on Models and Technologies for Intelligent Transportation Systems, 2025

Offline Hierarchical Reinforcement Learning via Inverse Optimization.

Carolin Schmidt, Daniele Gammelli, James Harrison, Marco Pavone, Filipe Rodrigues

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Generalizable Spacecraft Trajectory Generation via Multimodal Learning with Transformers.

Davide Celestini, Amirhossein Afsharrad, Daniele Gammelli, Tommaso Guffanti, Gioele Zardini, Sanjay Lall, Elisa Capello, Simone D'Amico, Marco Pavone

Proceedings of the 2025 American Control Conference, 2025

2024

Transformer-Based Model Predictive Control: Trajectory Optimization via Sequence Modeling.

Davide Celestini, Daniele Gammelli, Tommaso Guffanti, Simone D'Amico, Elisa Capello, Marco Pavone

IEEE Robotics Autom. Lett., November, 2024

Towards Robust Spacecraft Trajectory Optimization via Transformers.

Yuji Takubo, Tommaso Guffanti, Daniele Gammelli, Marco Pavone, Simone D'Amico

CoRR, 2024

Adapting a Foundation Model for Space-based Tasks.

Matthew Foutter, Praneet Bhoj, Rohan Sinha, Amine Elhafsi, Somrita Banerjee, Christopher Agia, Justin Kruger, Tommaso Guffanti, Daniele Gammelli, Simone D'Amico, Marco Pavone

CoRR, 2024

Real-Time Control of Electric Autonomous Mobility-on-Demand Systems via Graph Reinforcement Learning.

Aaryan Singhal, Daniele Gammelli, Justin Luke, Karthik Gopalakrishnan, Dominik Helmreich, Marco Pavone

Proceedings of the European Control Conference, 2024

Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning.

Carolin Schmidt, Daniele Gammelli, Francisco Câmara Pereira, Filipe Rodrigues

Proceedings of the European Control Conference, 2024

2023

Transformers for Trajectory Optimization with Application to Spacecraft Rendezvous.

Tommaso Guffanti, Daniele Gammelli, Simone D'Amico, Marco Pavone

CoRR, 2023

Graph Reinforcement Learning for Network Control via Bi-Level Optimization.

Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira

Proceedings of the International Conference on Machine Learning, 2023

2022

Generalized multi-output Gaussian process censored regression.

Daniele Gammelli, Kasper Pryds Rolsted, Dario Pacino, Filipe Rodrigues

Pattern Recognit., 2022

Recurrent flow networks: A recurrent latent variable model for density estimation of urban mobility.

Daniele Gammelli, Filipe Rodrigues

Pattern Recognit., 2022

Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand.

Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management.

Daniele Gammelli, Yihua Wang, Dennis Prak, Filipe Rodrigues, Stefan Minner, Francisco Câmara Pereira

CoRR, 2021

Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems.

Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Recurrent Flow Networks: A Recurrent Latent Variable Model for Spatio-Temporal Density Modelling.

Daniele Gammelli, Filipe Rodrigues

CoRR, 2020

Estimating Latent Demand of Shared Mobility through Censored Gaussian Processes.

Daniele Gammelli, Inon Peled, Filipe Rodrigues, Dario Pacino, Haci A. Kurtaran, Francisco C. Pereira

CoRR, 2020