mlsanityData to 14 Oct 2026

Safe Reinforcement Learning Using Robust Control Barrier Functions

arXiv 2110.05415 ↗First posted 11 Oct 2021eess.SY cs.AI cs.LGcited by 59

Not on the map. Why?

Cited by 36 in Deep reinforcement learning methods, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Reinforcement Learning (RL) has been shown to be effective in many scenarios. However, it typically requires the exploration of a sufficiently large number of state-action pairs, some of which may be unsafe. Consequently, its application to safety-critical systems remains a challenge. An increasingly common approach to address safety involves the addition of a safety layer that projects the RL actions onto a safe set of actions. In turn, a difficulty for such frameworks is how to effectively couple RL with the safety layer to improve the learning performance. In this paper, we frame safety as a differentiable robust-control-barrier-function layer in a model-based RL framework. Moreover, we also propose an approach to modularly learn the underlying reward-driven task, independent of safety constraints. We demonstrate that this approach both ensures safety and effectively guides exploration during training in a range of experiments, including zero-shot transfer when the reward is learned in a modular way.

Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). Builds on 26 of its 43 references that are in the map. First posted on arXiv 11 Oct 2021.

Builds on

26 of 43 references.

References · 26

  1. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,885
  2. 2021Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learningcited by 998
  3. 2019When to Trust Your Model: Model-Based Policy Optimizationcited by 773
  4. 2017OptNet: Differentiable Optimization as a Layer in Neural Networkscited by 599
  5. 2017A Brief Survey of Deep Reinforcement Learningcited by 483
  6. 2019Differentiable Convex Optimization Layerscited by 465
  7. 2019Control Barrier Functions: Theory and Applicationscited by 372
  8. 2021Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learningcited by 371
  9. 2017Safe Model-based Reinforcement Learning with Stability Guaranteescited by 366
  10. 2015Risk-Constrained Reinforcement Learning with Percentile Risk Criteriacited by 337
  11. 2018A Lyapunov-based Approach to Safe Reinforcement Learningcited by 297
  12. 2019End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Taskscited by 289
14 more
  1. 2016Control Barrier Function Based Quadratic Programs for Safety Critical Systemscited by 287
  2. 2020Recovery RL: Safe Reinforcement Learning with Learned Recovery Zonescited by 175
  3. 2017A General Safety Framework for Learning-Based Control in Uncertain Robotic Systemscited by 163
  4. 2019Lyapunov-based Safe Policy Optimization for Continuous Controlcited by 145
  5. 2020Reinforcement Learning for Safety-Critical Control under Model Uncertainty, using Control Lyapunov Functions and Control Barrier Functionscited by 68
  6. 2020Safety-Critical Model Predictive Control with Discrete-Time Control Barrier Functioncited by 49
  7. 2016Robustness of Control Barrier Functions for Safety Critical Controlcited by 30
  8. 2020SAMBA: Safe Model-Based & Active Reinforcement Learningcited by 30
  9. 2020Control Barriers in Bayesian Learning of System Dynamicscited by 17
  10. 2021Safety-Critical Control using Optimal-decay Control Barrier Function with Guaranteed Point-wise Feasibilitycited by 7
  11. 2019Robust Barrier Functions for a Fully Autonomous, Remotely Accessible Swarm-Robotics Testbedcited by 4
  12. 2021Data-Driven Robust Barrier Functions for Safe, Long-Term Operationcited by 4
  13. 2019Constraint Learning for Control Tasks with Limited Duration Barrier Functionscited by 3
  14. 2019Persistification of Robotic Taskscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 11; 2024: 13; 2025: 14; 2026: 21.

59 papers.

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  1. 2023A Survey on Physics Informed Reinforcement Learning: Review and Open Problemscited by 24
  2. 2025CBF-RL: Safety Filtering Reinforcement Learning in Training with Control Barrier Functionscited by 17
  3. 2024Safe Reinforcement Learning on the Constraint Manifold: Theory and Applicationscited by 15
  4. 2023Stable and Safe Reinforcement Learning via a Barrier-Lyapunov Actor-Critic Approachcited by 13
  5. 2024Safety Filters for Black-Box Dynamical Systems by Learning Discriminating Hyperplanescited by 12
  6. 2025Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Controlcited by 8
  7. 2023Multi-Agent Reinforcement Learning Guided by Signal Temporal Logic Specificationscited by 7
  8. 2023Towards Safe Autonomous Driving Policies using a Neuro-Symbolic Deep Reinforcement Learning Approachcited by 7
  9. 2024Verified Safe Reinforcement Learning for Neural Network Dynamic Modelscited by 7
  10. 2025Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systemscited by 5
  11. 2023On the Optimality, Stability, and Feasibility of Control Barrier Functions: An Adaptive Learning-Based Approachcited by 4
  12. 2024Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learningcited by 4
38 more
  1. 2025A Survey of Reinforcement Learning for Optimization in Automationcited by 4
  2. 2025Improved Robustness of Deep Reinforcement Learning for Control of Time-Varying Systems by Bounded Extremum Seekingcited by 4
  3. 2023Learning Adaptive Safety for Multi-Agent Systemscited by 3
  4. 2023Learning Predictive Safety Filter via Decomposition of Robust Invariant Setcited by 3
  5. 2024Implicit Safe Set Algorithm for Provably Safe Reinforcement Learningcited by 3
  6. 2025Provably Optimal Reinforcement Learning under Safety Filteringcited by 3
  7. 2023Machine Learning Meets Advanced Robotic Manipulationcited by 2
  8. 2024WROOM: An Autonomous Driving Approach for Off-Road Navigationcited by 2
  9. 2024Toward Scalable Multirobot Control: Fast Policy Learning in Distributed MPCcited by 2
  10. 2025Back to Base: Towards Hands-Off Learning via Safe Resets with Reach-Avoid Safety Filterscited by 2
  11. 2025Certificated Actor-Critic: Hierarchical Reinforcement Learning with Control Barrier Functions for Safe Navigationcited by 2
  12. 2025T-CBF: Traversability-based Control Barrier Function to Navigate Vertically Challenging Terraincited by 2
  13. 2025Multi-Constraint Safe Reinforcement Learning via Closed-form Solution for Log-Sum-Exp Approximation of Control Barrier Functionscited by 2
  14. 2025End-to-End Humanoid Robot Safe and Comfortable Locomotion Policycited by 2
  15. 2023Safety Filter Design for Neural Network Systems via Convex Optimizationcited by 1
  16. 2023Towards Optimal Head-to-head Autonomous Racing with Curriculum Reinforcement Learningcited by 1
  17. 2023Distributionally Safe Reinforcement Learning under Model Uncertainty: A Single-Level Approach by Differentiable Convex Programmingcited by 1
  18. 2024The Feasibility Theory of Constrained Reinforcement Learning: A Tutorial Studycited by 1
  19. 2024Myopically Verifiable Probabilistic Certificates for Safe Control and Learningcited by 1
  20. 2024A novel agent with formal goal-reaching guarantees: an experimental study with a mobile robotcited by 1
  21. 2024Q-learning-based Model-free Safety Filtercited by 1
  22. 2025Learning Vision-Based Neural Network Controllers with Semi-Probabilistic Safety Guaranteescited by 1
  23. 2026Vision-based Goal-Reaching Control for Mobile Robots Using a Hierarchical Learning Frameworkcited by 1
  24. 2026Reinforcement Learning for Control Systems with Time Delays: A Comprehensive Surveycited by 1
  25. 2026High-Speed Vision-Based Flight in Clutter with Safety-Shielded Reinforcement Learningcited by 1
  26. 2026Shielded Reinforcement Learning Under Dynamic Temporal Logic Constraintscited by 1
  27. 2026CMP: Robust Whole-Body Tracking for Loco-Manipulation via Competence Manifold Projectioncited by 1
  28. 2026Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertaintycited by 1
  29. 2026DiffCVaR: Reinforcement Learning for Risk Adaptation via Differentiable CVaR Barrier Functionscited by 1
  30. 2026Safe Execution of RL Policies Via Acceleration-Based CBF-QP Constraint Enforcement for Real-World Robotic Deploymentscited by 1
  31. 2024SOMTP: Self-Supervised Learning-Based Optimizer for MPC-Based Safe Trajectory Planning Problems in Roboticscited by 0
  32. 2024Enforcing Cooperative Safety for Reinforcement Learning-based Mixed-Autonomy Platoon Controlcited by 0
  33. 2025Sample Efficient Certification of Discrete-Time Control Barrier Functionscited by 0
  34. 2025Game-Theoretic Risk-Shaped Reinforcement Learning for Safe Autonomous Drivingcited by 0
  35. 2026C-STEP: Continuous Space-Time Empowerment for Physics-informed Safe Reinforcement Learning of Mobile Agentscited by 0
  36. 2026A Control Barrier Function-Constrained Model Predictive Control Framework for Safe Reinforcement Learningcited by 0
  37. 2026Online Reinforcement Learning for Safe Gain Scheduling in Nonlinear Quadrotor Controlcited by 0
  38. 2026Safe Continual Reinforcement Learning in Non-stationary Environmentscited by 0

50 most cited of 59 All 59 (JSON)