3 citations · 6 across the 8 of their papers we have counts for
4 papers · 1 filter
Safe Reinforcement Learning via Confidence-Based Filters
Sebastian Curi, Armin Lederer, Sandra Hirche +1
Ensuring safety is a crucial challenge when deploying reinforcement learning (RL) to real-world systems. We develop confidence-based safety filters, a control-theoretic approach fo…
Dext-Gen: Dexterous Grasping in Sparse Reward Environments with Full Orientation Control
Martin Schuck, Jan Brüdigam, Alexandre Capone +2
Reinforcement learning is a promising method for robotic grasping as it can learn effective reaching and grasping policies in difficult scenarios. However, achieving human-like man…
Actuator Scheduling for Linear Systems: A Convex Relaxation Approach
Junjie Jiao, Dipankar Maity, John S. Baras +1
In this letter, we investigate the problem of actuator scheduling for networked control systems. Given a stochastic linear system with a number of actuators, we consider the case t…
Towards Data-driven LQR with Koopmanizing Flows
Petar Bevanda, Max Beier, Shahab Heshmati-Alamdari +2
We propose a novel framework for learning linear time-invariant (LTI) models for a class of continuous-time non-autonomous nonlinear dynamics based on a representation of Koopman o…