mlsanityData to 14 Oct 2026

SRL-VIC: A Variable Stiffness-Based Safe Reinforcement Learning for Contact-Rich Robotic Tasks

arXiv 2406.13744 ↗First posted 19 Jun 2024cs.ROcited by 15

On the map: Deep reinforcement learning methods → RL for robot locomotion and manipulation

Abstract (arXiv)

Reinforcement learning (RL) has emerged as a promising paradigm in complex and continuous robotic tasks, however, safe exploration has been one of the main challenges, especially in contact-rich manipulation tasks in unstructured environments. Focusing on this issue, we propose SRL-VIC: a model-free safe RL framework combined with a variable impedance controller (VIC). Specifically, safety critic and recovery policy networks are pre-trained where safety critic evaluates the safety of the next action using a risk value before it is executed and the recovery policy suggests a corrective action if the risk value is high. Furthermore, the policies are updated online where the task policy not only achieves the task but also modulates the stiffness parameters to keep a safe and compliant profile. A set of experiments in contact-rich maze tasks demonstrate that our framework outperforms the baselines (without the recovery mechanism and without the VIC), yielding a good trade-off between efficient task accomplishment and safety guarantee. We show our policy trained on simulation can be deployed on a physical robot without fine-tuning, achieving successful task completion with robustness and generalization. The video is available at https://youtu.be/ksWXR3vByoQ.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). Placed in RL for robot locomotion and manipulation, one of 15 directions in Deep reinforcement learning methods. Builds on 14 of its 25 references that are in the map. First posted on arXiv 19 Jun 2024.

Builds on

14 of 25 references.

References · 14

  1. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,885
  2. 2015Continuous control with deep reinforcement learningcited by 3,407
  3. 2021Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learningcited by 371
  4. 2020Recovery RL: Safe Reinforcement Learning with Learned Recovery Zonescited by 175
  5. 2020Learning to be Safe: Deep RL with a Safety Criticcited by 116
  6. 2020Conservative Safety Critics for Explorationcited by 113
  7. 2019Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Taskscited by 84
  8. 2019Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Taskscited by 67
  9. 2020Meta-Reinforcement Learning for Robotic Industrial Insertion Taskscited by 34
  10. 2020Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environmentscited by 23
  11. 2020Variable impedance control and learning -- A reviewcited by 17
  12. 2021Learning Variable Impedance Control via Inverse Reinforcement Learning for Force-Related Taskscited by 12
2 more
  1. 2022Impedance Adaptation by Reinforcement Learning with Contact Dynamic Movement Primitivescited by 3
  2. 2022A Self-Tuning Impedance-based Interaction Planner for Robotic Haptic Explorationcited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 6; 2026: 6.

15 papers.

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  1. 2025A Survey on Imitation Learning for Contact-Rich Tasks in Roboticscited by 14
  2. 2024Don't Let Your Robot be Harmful: Responsible Robotic Manipulation via Safety-as-Policycited by 9
  3. 2024HYPERmotion: Learning Hybrid Behavior Planning for Autonomous Loco-manipulationcited by 7
  4. 2025Scaling Laws in Scientific Discovery with AI and Robot Scientistscited by 5
  5. 2025Bresa: Bio-inspired Reflexive Safe Reinforcement Learning for Contact-Rich Robotic Taskscited by 3
  6. 2025Passivity-Centric Safe Reinforcement Learning for Contact-Rich Robotic Taskscited by 2
  7. 2025HiBerNAC: Hierarchical Brain-inspired Robotic Neural Agent Collective for Disentangling Complex Manipulationcited by 1
  8. 2025INTENTION: Inferring Tendencies of Humanoid Robot Motion Through Interactive Intuition and Grounded VLMcited by 1
  9. 2026VIDP: Variable Impedance Diffusion Policy for Compliant Robot Manipulation from Diverse Demonstrationscited by 1
  10. 2026CR-VLA-Force: Learning Control-aware Compliance VLA Model for Robust Contact-rich Robotic Manipulationcited by 1
  11. 2024On the role of Artificial Intelligence methods in modern force-controlled manufacturing robotic taskscited by 0
  12. 2026Reversible Simplex Supervision with Post-Action Debt Accounting for Goal-Reaching RLcited by 0
3 more
  1. 2026Reward-Zero: Language Embedding Driven Implicit Reward Mechanisms for Reinforcement Learningcited by 0
  2. 2026Efficient Real-World Online Reinforcement Learning for Robot Manipulation via Centralized Training and Critic Decompositioncited by 0
  3. 2026Potential-Field Action Representation for Reinforcement Learning in Contact-Rich Manipulationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Safe Learning for Contact-Rich Robot Tasks: A Survey from Classical Learning-Based Methods to Safe Foundation Models
  2. 2025Contact-Safe Reinforcement Learning with ProMP Reparameterization and Energy Awareness
  3. 2025ContactRL: Safe Reinforcement Learning based Motion Planning for Contact based Human Robot Collaboration
  4. 2025Impedance Primitive-augmented Hierarchical Reinforcement Learning for Sequential Tasks
  5. 2026Constraint-Grounded Reinforcement Learning for Variable Impedance Control in Contact-Rich Robotic Insertion
  6. 2025Skill-based Safe Reinforcement Learning with Risk Planning
  7. 2024A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks
  8. 2026CompliantVLA-adaptor: VLM-Guided Variable Impedance Action for Safe Contact-Rich Manipulation