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2011.08421
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Reachability-based Trajectory Safeguard (RTS): A Safe and Fast Reinforcement Learning Safety Layer for Continuous Control
IEEE Robotics and Automation Letters (RA-L), 2020
17 November 2020
Y. Shao
Chao Chen
Shreyas Kousik
Ram Vasudevan
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Papers citing
"Reachability-based Trajectory Safeguard (RTS): A Safe and Fast Reinforcement Learning Safety Layer for Continuous Control"
32 / 32 papers shown
Predictive Safety Shield for Dyna-Q Reinforcement Learning
European Control Conference (ECC), 2025
Jin Pin
Krasowski Hanna
Vanneaux Elena
168
0
0
26 Nov 2025
From Demonstrations to Safe Deployment: Path-Consistent Safety Filtering for Diffusion Policies
Ralf Romer
Julian Balletshofer
Jakob Thumm
Marco Pavone
Angela P. Schoellig
Matthias Althoff
211
1
0
09 Nov 2025
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces
International Conference on Learning Representations (ICLR), 2025
Saket Tiwari
Omer Gottesman
George Konidaris
383
3
0
28 Jul 2025
Towards Safe Robot Foundation Models
Maximilian Tölle
Theo Gruner
Daniel Palenicek
Jonas Günster
Puze Liu
Joe Watson
Davide Tateo
Jan Peters
OffRL
488
0
0
10 Mar 2025
Traffic-Rule-Compliant Trajectory Repair via Satisfiability Modulo Theories and Reachability Analysis
IEEE Transactions on robotics (IEEE Trans. Robot.), 2024
Yuanfei Lin
Zekun Xing
Xuyuan Han
Matthias Althoff
479
3
0
20 Dec 2024
Absolute State-wise Constrained Policy Optimization: High-Probability State-wise Constraints Satisfaction
Weiye Zhao
Feihan Li
Yifan Sun
Yujie Wang
Rui Chen
Tianhao Wei
Changliu Liu
290
2
0
02 Oct 2024
RAIL: Reachability-Aided Imitation Learning for Safe Policy Execution
IEEE International Conference on Robotics and Automation (ICRA), 2024
Wonsuhk Jung
Dennis Anthony
Utkarsh Aashu Mishra
Nadun Ranawaka Arachchige
Matthew Bronars
Danfei Xu
Shreyas Kousik
368
3
0
28 Sep 2024
Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning
Conference on Robot Learning (CoRL), 2024
Piotr Kicki
Davide Tateo
Puze Liu
Jonas Guenster
Jan Peters
Krzysztof Walas
256
6
0
26 Aug 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
399
4
0
02 Jul 2024
ZAPP! Zonotope Agreement of Prediction and Planning for Continuous-Time Collision Avoidance with Discrete-Time Dynamics
Luca Paparusso
Shreyas Kousik
Edward Schmerling
Francesco Braghin
Marco Pavone
289
3
0
03 Jun 2024
Do No Harm: A Counterfactual Approach to Safe Reinforcement Learning
Sean Vaskov
Wilko Schwarting
Chris Baker
327
2
0
19 May 2024
Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications
Puze Liu
Haitham Bou-Ammar
Jan Peters
Davide Tateo
282
21
0
13 Apr 2024
RAnGE: Reachability Analysis for Guaranteed Ergodicity
Henry Berger
Ian Abraham
271
0
0
04 Apr 2024
Goal-Reaching Trajectory Design Near Danger with Piecewise Affine Reach-avoid Computation
Long Kiu Chung
Wonsuhk Jung
Chuizheng Kong
Shreyas Kousik
455
4
0
23 Feb 2024
Learn With Imagination: Safe Set Guided State-wise Constrained Policy Optimization
Conference on Learning for Dynamics & Control (L4DC), 2023
Weiye Zhao
Yifan Sun
Fei Li
Rui Chen
Tianhao Wei
Changliu Liu
496
7
0
25 Aug 2023
Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion
Simon Guist
Jan Schneider
Hao Ma
Tianyu Cui
V. Berenz
...
Felix Gruninger
M. Muhlebach
J. Fiene
Bernhard Schölkopf
Le Chen
401
12
0
05 Jul 2023
Safe Reinforcement Learning with Dead-Ends Avoidance and Recovery
IEEE Robotics and Automation Letters (RA-L), 2023
Xiao Zhang
Hai Zhang
Hongtu Zhou
Chang Huang
Di Zhang
Chen Ye
Siyue Tao
OffRL
267
10
0
24 Jun 2023
Adaptive Policy Learning to Additional Tasks
Wenjian Hao
Zehui Lu
Zihao Liang
Tianyu Zhou
Shaoshuai Mou
343
0
0
24 May 2023
Safe Deep RL for Intraoperative Planning of Pedicle Screw Placement
Yu Ao
H. Esfandiari
F. Carrillo
Yarden As
Mazda Farshad
Benjamin Grewe
Andreas Krause
Philipp Fuernstahl
259
1
0
09 May 2023
Reducing Safety Interventions in Provably Safe Reinforcement Learning
IEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2023
Jakob Thumm
Guillaume Pelat
Matthias Althoff
256
5
0
06 Mar 2023
State-wise Safe Reinforcement Learning: A Survey
International Joint Conference on Artificial Intelligence (IJCAI), 2023
Weiye Zhao
Tairan He
Rui Chen
Tianhao Wei
Changliu Liu
470
92
0
06 Feb 2023
Safe Reinforcement Learning with Probabilistic Guarantees Satisfying Temporal Logic Specifications in Continuous Action Spaces
IEEE Conference on Decision and Control (CDC), 2022
Hanna Krasowski
Prithvi Akella
Aaron D. Ames
Matthias Althoff
362
3
0
12 Dec 2022
Safe Reinforcement Learning using Data-Driven Predictive Control
International Conference on Communications, Signal Processing, and their Applications (ICCSPA), 2022
Mahmoud Selim
Amr Alanwar
M. El-Kharashi
Hazem Abbas
Karl H. Johansson
OffRL
282
7
0
20 Nov 2022
Provably Safe Reinforcement Learning via Action Projection using Reachability Analysis and Polynomial Zonotopes
Niklas Kochdumper
Hanna Krasowski
Xiao Wang
Stanley Bak
Matthias Althoff
367
48
0
19 Oct 2022
Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments
International Conference on Machine Learning (ICML), 2022
Yixuan Wang
S. Zhan
Ruochen Jiao
Zhilu Wang
Wanxin Jin
Zhuoran Yang
Zhaoran Wang
Chao Huang
Qi Zhu
420
78
0
29 Sep 2022
Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction
IEEE International Conference on Robotics and Automation (ICRA), 2022
Puze Liu
Kuo Zhang
Davide Tateo
Snehal Jauhri
Zhiyuan Hu
Jan Peters
Georgia Chalvatzaki
265
23
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
463
43
0
13 May 2022
Provably Safe Deep Reinforcement Learning for Robotic Manipulation in Human Environments
IEEE International Conference on Robotics and Automation (ICRA), 2022
Jakob Thumm
Matthias Althoff
296
45
0
12 May 2022
Safe Reinforcement Learning Using Black-Box Reachability Analysis
IEEE Robotics and Automation Letters (RA-L), 2022
Mahmoud Selim
Amr Alanwar
Shreyas Kousik
Grace Gao
Marco Pavone
Karl H. Johansson
265
41
0
15 Apr 2022
A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis
T. Lew
Lucas Janson
Riccardo Bonalli
Marco Pavone
385
24
0
10 Dec 2021
Risk Conditioned Neural Motion Planning
Xin Huang
Meng Feng
A. Jasour
Guy Rosman
B. Williams
193
8
0
04 Aug 2021
Distributionally robust risk map for learning-based motion planning and control: A semidefinite programming approach
IEEE Transactions on robotics (TRO), 2021
A. Hakobyan
Insoon Yang
316
29
0
03 May 2021
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