56 citations · 111 across the 25 of their papers we have counts for
4 papers · 1 filter
Beyond Terminal Constraints: Reliable Robot Control with Learned Safe Sets
Gianni Lunardi, Elias Fontanari, Matteo Saveriano +1
Ensuring safety in advanced robot control methods such as Model Predictive Control (MPC) and Reinforcement Learning remains an open challenge. A common approach relies on control-i…
CAST: Alternating State-Value Targets and Expanded Policy Gradients for Model-Based Reinforcement Learning
Pietro Noah Crestaz, Mohamed Yassine Kabouri, Nicolas Mansard +1
Model-based reinforcement learning (MBRL) is a family of RL methods that learn a model of the environment and use it for action selection, making it well suited to robotics due to…
Towards safe and optimal flight: Viability Kernel MPC for Fully Actuated Multirotor
Massimiliano Bertoni, Alberto Piccina, Gianni Lunardi +4
Industrial aerial robotics demands safety guarantees for navigation in unstructured environments while optimizing performance and computational efficiency. This paper presents a me…
PAC-DP: PAC-Bayesian Diffusion Policy Learning
Mohammad Hasan Yeganegi, Dian Yu, Andrea Del Prete +2
Diffusion Policies (DPs) are able to perform complex manipulation tasks. However, DPs are typically trained by minimizing a denoising objective, which provides limited control over…