Provably Safe Deep Reinforcement Learning for Robotic Manipulation in Human Environments

12 May 2022

Papers citing "Provably Safe Deep Reinforcement Learning for Robotic Manipulation in Human Environments"

12 / 12 papers shown

Title
A Parametric Model for Near-Optimal Online Synthesis with Robust Reach-Avoid Guarantees Mario Gleirscher Philip Hönnecke 40 0 0 01 Apr 2025
RAIL: Reachability-Aided Imitation Learning for Safe Policy Execution Wonsuhk Jung Dennis Anthony Utkarsh Aashu Mishra Nadun Ranawaka Arachchige Matthew Bronars Danfei Xu Shreyas Kousik 36 0 0 28 Sep 2024
Safety-Driven Deep Reinforcement Learning Framework for Cobots: A Sim2Real Approach Ammar N. Abbas Shakra Mehak Georgios C. Chasparis John D. Kelleher Michael Guilfoyle M. Leva Aswin K Ramasubramanian 56 1 0 02 Jul 2024
Adaptive Distance Functions via Kelvin Transformation Rafael I. Cabral Muchacho Florian T. Pokorny 37 2 0 05 Jun 2024
Learning Control Barrier Functions and their application in Reinforcement Learning: A Survey Maeva Guerrier Hassan Fouad Giovanni Beltrame OffRL 37 1 0 22 Apr 2024
Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications Puze Liu Haitham Bou-Ammar Jan Peters Davide Tateo 49 7 0 13 Apr 2024
Goal-Reaching Trajectory Design Near Danger with Piecewise Affine Reach-avoid Computation Long Kiu Chung Wonsuhk Jung Chuizheng Kong Shreyas Kousik 41 3 0 23 Feb 2024
Human-Robot Gym: Benchmarking Reinforcement Learning in Human-Robot Collaboration Jakob Thumm Felix Trost Matthias Althoff OffRL 36 6 0 09 Oct 2023
Reducing Safety Interventions in Provably Safe Reinforcement Learning Jakob Thumm Guillaume Pelat Matthias Althoff 22 3 0 06 Mar 2023
Provably Safe Reinforcement Learning via Action Projection using Reachability Analysis and Polynomial Zonotopes Niklas Kochdumper Hanna Krasowski Xiao Wang Stanley Bak Matthias Althoff 32 28 0 19 Oct 2022
Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction Puze Liu Kuo Zhang Davide Tateo Snehal Jauhri Zhiyuan Hu Jan Peters Georgia Chalvatzaki 47 17 0 27 Sep 2022
Provably Safe Reinforcement Learning: Conceptual Analysis, Survey, and Benchmarking Hanna Krasowski Jakob Thumm Marlon Müller Lukas Schäfer Xiao Wang Matthias Althoff 88 19 0 13 May 2022