# Variable impedance control and learning -- A review

arXiv: https://arxiv.org/abs/2010.06246 · HTML: https://mlsanity.com/paper/2010.06246/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Oct 2020.

## Built on by (most cited first, 17 of 17)

- [SRL-VIC: A Variable Stiffness-Based Safe Reinforcement Learning for Contact-Rich Robotic Tasks](https://mlsanity.com/paper/2406.13744/) (2024)
- [A Survey on Imitation Learning for Contact-Rich Tasks in Robotics](https://mlsanity.com/paper/2506.13498/) (2025)
- [Learning Variable Compliance Control From a Few Demonstrations for Bimanual Robot with Haptic Feedback Teleoperation System](https://mlsanity.com/paper/2406.14990/) (2024)
- [GenCHiP: Generating Robot Policy Code for High-Precision and Contact-Rich Manipulation Tasks](https://mlsanity.com/paper/2404.06645/) (2024)
- [Mamba as a motion encoder for robotic imitation learning](https://mlsanity.com/paper/2409.02636/) (2024)
- [Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks](https://mlsanity.com/paper/2207.03952/) (2022)
- [Fusion Dynamical Systems with Machine Learning in Imitation Learning: A Comprehensive Overview](https://mlsanity.com/paper/2403.19916/) (2024)
- [DA-VIL: Adaptive Dual-Arm Manipulation with Reinforcement Learning and Variable Impedance Control](https://mlsanity.com/paper/2410.19712/) (2024)
- [A Contact-Safe Reinforcement Learning Framework for Contact-Rich Robot Manipulation](https://mlsanity.com/paper/2207.13438/) (2022)
- [Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation](https://mlsanity.com/paper/2609.01596/) (2026)
- [VIDP: Variable Impedance Diffusion Policy for Compliant Robot Manipulation from Diverse Demonstrations](https://mlsanity.com/paper/2608.06210/) (2026)
- [Constraint-Grounded Reinforcement Learning for Variable Impedance Control in Contact-Rich Robotic Insertion](https://mlsanity.com/paper/2609.13516/) (2026)
- [Learning Variable Impedance Control for Aerial Sliding on Uneven Heterogeneous Surfaces by Proprioceptive and Tactile Sensing](https://mlsanity.com/paper/2206.14122/) (2022)
- [A Coordinated Dual-Arm Framework for Delicate Snap-Fit Assemblies](https://mlsanity.com/paper/2511.18153/) (2025)
- [Generative Action-Chunk Sampling for Adaptive Stiffness Control in Physical Human-Robot Collaboration](https://mlsanity.com/paper/2608.25284/) (2026)
- [CompVLA: A Variable Compliance Vision-Language-Action Model for Contact-rich Manipulation](https://mlsanity.com/paper/2609.23614/) (2026)
- [Force-Modulated Dexterity: Unified Compliance for Contact-Rich Manipulation](https://mlsanity.com/paper/2610.17161/) (2026)

## Abstract (arXiv)

Robots that physically interact with their surroundings, in order to accomplish some tasks or assist humans in their activities, require to exploit contact forces in a safe and proficient manner. Impedance control is considered as a prominent approach in robotics to avoid large impact forces while operating in unstructured environments. In such environments, the conditions under which the interaction occurs may significantly vary during the task execution. This demands robots to be endowed with on-line adaptation capabilities to cope with sudden and unexpected changes in the environment. In this context, variable impedance control arises as a powerful tool to modulate the robot's behavior in response to variations in its surroundings. In this survey, we present the state-of-the-art of approaches devoted to variable impedance control from control and learning perspectives (separately and jointly). Moreover, we propose a new taxonomy for mechanical impedance based on variability, learning, and control. The objective of this survey is to put together the concepts and efforts that have been done so far in this field, and to describe advantages and disadvantages of each approach. The survey concludes with open issues in the field and an envisioned framework that may potentially solve them.