Guided by Guardrails: Control Barrier Functions as Safety Instructors for Robotic Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Guerrier, Maeva, Soma, Karthik, Fouad, Hassan, Beltrame, Giovanni |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning Control Barrier Functions and their application in Reinforcement Learning: A Survey
by: Guerrier, Maeva, et al.
Published: (2024)
by: Guerrier, Maeva, et al.
Published: (2024)
Can Vision Foundation Models Navigate? Zero-Shot Real-World Evaluation and Lessons Learned
by: Guerrier, Maeva, et al.
Published: (2026)
by: Guerrier, Maeva, et al.
Published: (2026)
Reinforcement Learning with Elastic Time Steps
by: Wang, Dong, et al.
Published: (2024)
by: Wang, Dong, et al.
Published: (2024)
MOSEAC: Streamlined Variable Time Step Reinforcement Learning
by: Wang, Dong, et al.
Published: (2024)
by: Wang, Dong, et al.
Published: (2024)
Learning Multi-agent Multi-machine Tending by Mobile Robots
by: Abdalwhab, Abdalwhab, et al.
Published: (2024)
by: Abdalwhab, Abdalwhab, et al.
Published: (2024)
Learning for Layered Safety-Critical Control with Predictive Control Barrier Functions
by: Compton, William D., et al.
Published: (2024)
by: Compton, William D., et al.
Published: (2024)
Evolution of Societies via Reinforcement Learning
by: Bouteiller, Yann, et al.
Published: (2024)
by: Bouteiller, Yann, et al.
Published: (2024)
Physical Simulation for Multi-agent Multi-machine Tending
by: Abdalwhab, Abdalwhab, et al.
Published: (2024)
by: Abdalwhab, Abdalwhab, et al.
Published: (2024)
Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems
by: Ahmad, H. M. Sabbir, et al.
Published: (2025)
by: Ahmad, H. M. Sabbir, et al.
Published: (2025)
CBF-RL: Safety Filtering Reinforcement Learning in Training with Control Barrier Functions
by: Yang, Lizhi, et al.
Published: (2025)
by: Yang, Lizhi, et al.
Published: (2025)
How to Train Your Latent Control Barrier Function: Smooth Safety Filtering Under Hard-to-Model Constraints
by: Nakamura, Kensuke, et al.
Published: (2025)
by: Nakamura, Kensuke, et al.
Published: (2025)
Learning Local Control Barrier Functions for Hybrid Systems
by: Yang, Shuo, et al.
Published: (2024)
by: Yang, Shuo, et al.
Published: (2024)
Certificated Actor-Critic: Hierarchical Reinforcement Learning with Control Barrier Functions for Safe Navigation
by: Xie, Junjun, et al.
Published: (2025)
by: Xie, Junjun, et al.
Published: (2025)
Efficient Motion Planning for Manipulators with Control Barrier Function-Induced Neural Controller
by: Yu, Mingxin, et al.
Published: (2024)
by: Yu, Mingxin, et al.
Published: (2024)
CN-CBF: Composite Neural Control Barrier Function for Safe Robot Navigation in Dynamic Environments
by: Derajić, Bojan, et al.
Published: (2026)
by: Derajić, Bojan, et al.
Published: (2026)
Dynamic High-Order Control Barrier Functions with Diffuser for Safety-Critical Trajectory Planning at Signal-Free Intersections
by: Chen, Di, et al.
Published: (2024)
by: Chen, Di, et al.
Published: (2024)
Interpretable Robot Control via Structured Behavior Trees and Large Language Models
by: Chekam, Ingrid Maéva, et al.
Published: (2025)
by: Chekam, Ingrid Maéva, et al.
Published: (2025)
Variable Time Step Reinforcement Learning for Robotic Applications
by: Wang, Dong, et al.
Published: (2024)
by: Wang, Dong, et al.
Published: (2024)
Safe Neural Control for Non-Affine Control Systems with Differentiable Control Barrier Functions
by: Xiao, Wei, et al.
Published: (2023)
by: Xiao, Wei, et al.
Published: (2023)
Safety Certification in the Latent space using Control Barrier Functions and World Models
by: Anand, Mehul, et al.
Published: (2025)
by: Anand, Mehul, et al.
Published: (2025)
Robot Control Stack: A Lean Ecosystem for Robot Learning at Scale
by: Jülg, Tobias, et al.
Published: (2025)
by: Jülg, Tobias, et al.
Published: (2025)
ORN-CBF: Learning Observation-conditioned Residual Neural Control Barrier Functions via Hypernetworks
by: Derajić, Bojan, et al.
Published: (2025)
by: Derajić, Bojan, et al.
Published: (2025)
Learning Aerodynamics for the Control of Flying Humanoid Robots
by: Paolino, Antonello, et al.
Published: (2025)
by: Paolino, Antonello, et al.
Published: (2025)
Robotic Paper Wrapping by Learning Force Control
by: Hanai, Hiroki, et al.
Published: (2025)
by: Hanai, Hiroki, et al.
Published: (2025)
ABNet: Attention BarrierNet for Safe and Scalable Robot Learning
by: Xiao, Wei, et al.
Published: (2024)
by: Xiao, Wei, et al.
Published: (2024)
Can Tabular Foundation Models Guide Exploration in Robot Policy Learning?
by: Ou, Buqing, et al.
Published: (2026)
by: Ou, Buqing, et al.
Published: (2026)
Safety Guardrails in the Sky: Realizing Control Barrier Functions on the VISTA F-16 Jet
by: Singletary, Andrew W., et al.
Published: (2026)
by: Singletary, Andrew W., et al.
Published: (2026)
Multi-Robot Decentralized Collaborative SLAM in Planetary Analogue Environments: Dataset, Challenges, and Lessons Learned
by: Lajoie, Pierre-Yves, et al.
Published: (2026)
by: Lajoie, Pierre-Yves, et al.
Published: (2026)
Enhancing Tactile-based Reinforcement Learning for Robotic Control
by: Miller, Elle, et al.
Published: (2025)
by: Miller, Elle, et al.
Published: (2025)
Learning to Control an Android Robot Head for Facial Animation
by: Heisler, Marcel, et al.
Published: (2024)
by: Heisler, Marcel, et al.
Published: (2024)
Improving Generalization Ability of Robotic Imitation Learning by Resolving Causal Confusion in Observations
by: Chen, Yifei, et al.
Published: (2025)
by: Chen, Yifei, et al.
Published: (2025)
Hierarchies define the scalability of robot swarms
by: Varadharajan, Vivek Shankar, et al.
Published: (2024)
by: Varadharajan, Vivek Shankar, et al.
Published: (2024)
DittoGym: Learning to Control Soft Shape-Shifting Robots
by: Huang, Suning, et al.
Published: (2024)
by: Huang, Suning, et al.
Published: (2024)
Extracting Forward Invariant Sets from Neural Network-Based Control Barrier Functions
by: Vaisi, Goli, et al.
Published: (2025)
by: Vaisi, Goli, et al.
Published: (2025)
Zero-shot Safety Prediction for Autonomous Robots with Foundation World Models
by: Mao, Zhenjiang, et al.
Published: (2024)
by: Mao, Zhenjiang, et al.
Published: (2024)
Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control
by: Pflueger, Jeff, et al.
Published: (2025)
by: Pflueger, Jeff, et al.
Published: (2025)
Learning-based Cooperative Robotic Paper Wrapping: A Unified Control Policy with Residual Force Control
by: Ali, Rewida, et al.
Published: (2025)
by: Ali, Rewida, et al.
Published: (2025)
An Interpretable Neural Control Network with Adaptable Online Learning for Sample Efficient Robot Locomotion Learning
by: Srisuchinnawong, Arthicha, et al.
Published: (2025)
by: Srisuchinnawong, Arthicha, et al.
Published: (2025)
Guided Decoding for Robot On-line Motion Generation and Adaption
by: Chen, Nutan, et al.
Published: (2024)
by: Chen, Nutan, et al.
Published: (2024)
Contrast Sets for Evaluating Language-Guided Robot Policies
by: Anwar, Abrar, et al.
Published: (2024)
by: Anwar, Abrar, et al.
Published: (2024)
Similar Items
-
Learning Control Barrier Functions and their application in Reinforcement Learning: A Survey
by: Guerrier, Maeva, et al.
Published: (2024) -
Can Vision Foundation Models Navigate? Zero-Shot Real-World Evaluation and Lessons Learned
by: Guerrier, Maeva, et al.
Published: (2026) -
Reinforcement Learning with Elastic Time Steps
by: Wang, Dong, et al.
Published: (2024) -
MOSEAC: Streamlined Variable Time Step Reinforcement Learning
by: Wang, Dong, et al.
Published: (2024) -
Learning Multi-agent Multi-machine Tending by Mobile Robots
by: Abdalwhab, Abdalwhab, et al.
Published: (2024)