3 citations · 6 across the 14 of their papers we have counts for
5 papers · 1 filter
Learning Robot Policies from Sparse Success Signals via STL-Guided Stein Variational Policy Gradient
Hongrui Zheng, Cristian Ioan Vasile, Antonio Loquercio +1
Learning robot policies for tasks with sparse success signals is challenging when completion depends on coordinated actions, precise contact outcomes, or satisfying several conditi…
AI Coaching for Accelerating Human Skill Development with Reinforcement Learning
Wei Wang, Enlin Gu, Antonio Loquercio +2
AI copilots can substantially boost human performance through shared control, but excessive assistance can induce over-reliance and skill atrophy. This paper studies how an embodie…
Failure-Aware Iterative Learning of State-Control Invariant Sets
Ahmad Amine, Nick-Marios T. Kokolakis, Ugo Rosolia +2
In this paper, we address the problem of computing maximal state-control invariant sets for deterministic linear systems using failing trajectories. We introduce the concept of sta…
Toward Single-Step MPPI via Differentiable Predictive Control
Viet-Anh Le, Renukanandan Tumu, Rahul Mangharam
Model predictive path integral (MPPI) is a sampling-based method for solving complex model predictive control (MPC) problems, but its real-time implementation is challenged by comp…
AdaptNC: Adaptive Nonconformity Scores for Conformal Prediction under Distribution Shift
Renukanandan Tumu, Aditya Singh, Rahul Mangharam
Rigorous uncertainty quantification is essential for the safe deployment of autonomous systems in unconstrained environments. Conformal Prediction (CP) provides a distribution-free…