Learning-driven nonlinear optimal control via gaussian process regression L Sforni, I Notarnicola, G Notarstefano 2021 60th IEEE Conference on Decision and Control (CDC), 4412-4417, 2021 | 8 | 2021 |
A distributed online optimization strategy for cooperative robotic surveillance L Pichierri, G Carnevale, L Sforni, A Testa, G Notarstefano 2023 IEEE International Conference on Robotics and Automation (ICRA), 5537-5543, 2023 | 7 | 2023 |
On-Policy Data-Driven Linear Quadratic Regulator via Combined Policy Iteration and Recursive Least Squares L Sforni, G Carnevale, I Notarnicola, G Notarstefano 2023 62nd IEEE Conference on Decision and Control (CDC), 5047-5052, 2023 | 3 | 2023 |
Stability-Certified On-Policy Data-Driven LQR via Recursive Learning and Policy Gradient L Sforni, G Carnevale, I Notarnicola, G Notarstefano arXiv preprint arXiv:2403.05367, 2024 | 2 | 2024 |
Structured-policy Q-learning: an LMI-based design strategy for distributed reinforcement learning L Sforni, A Camisa, G Notarstefano 2022 IEEE 61st Conference on Decision and Control (CDC), 4059-4064, 2022 | 2 | 2022 |
Gopronto: A feedback-based framework for nonlinear optimal control L Sforni, S Spedicato, I Notarnicola, G Notarstefano arXiv preprint arXiv:2108.13308, 2021 | 2 | 2021 |
Receding Horizon CBF-Based Multi-Layer Controllers for Safe Trajectory Generation L Sforni, G Notarstefano, AD Ames 2024 American Control Conference (ACC), 4765-4770, 2024 | 1 | 2024 |
Multi-Robot Target Monitoring and Encirclement via Triggered Distributed Feedback Optimization L Pichierri, G Carnevale, L Sforni, G Notarstefano arXiv preprint arXiv:2409.20399, 2024 | | 2024 |
Learning-driven and distributed optimal control methods for large-scale and multi-agent systems L Sforni alma, 2024 | | 2024 |