# Reinforcement Learning-Based Model Matching to Reduce the Sim-Real Gap in COBRA

arXiv: https://arxiv.org/abs/2406.13700 · HTML: https://mlsanity.com/paper/2406.13700/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in RL for robot locomotion and manipulation, one of 15 directions in Deep reinforcement learning methods.
- Builds on 20 of its 33 references that are in the map.
- First posted on arXiv 19 Jun 2024.

## Placed in

- Deep reinforcement learning methods / [RL for robot locomotion and manipulation](https://mlsanity.com/deeprl/rl-for-robot-locomotion-and-manipulation/)

## Builds on (most cited first, 20 of 20)

- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Learning Quadrupedal Locomotion over Challenging Terrain](https://mlsanity.com/paper/2010.11251/) (2020)
- [Residual Reinforcement Learning for Robot Control](https://mlsanity.com/paper/1812.03201/) (2018)
- [ANYmal Parkour: Learning Agile Navigation for Quadrupedal Robots](https://mlsanity.com/paper/2306.14874/) (2023)
- [Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots](https://mlsanity.com/paper/2103.14295/) (2021)
- [Sim-to-Real Transfer for Biped Locomotion](https://mlsanity.com/paper/1903.01390/) (2019)
- [Feedback Control of a Cassie Bipedal Robot: Walking, Standing, and Riding a Segway](https://mlsanity.com/paper/1809.07279/) (2018)
- [Fast Contact-Implicit Model-Predictive Control](https://mlsanity.com/paper/2107.05616/) (2021)
- [DeepCPG Policies for Robot Locomotion](https://mlsanity.com/paper/2302.13191/) (2023)
- [Traversing Steep and Granular Martian Analog Slopes With a Dynamic Quadrupedal Robot](https://mlsanity.com/paper/2106.01974/) (2021)
- [Optimization-free Ground Contact Force Constraint Satisfaction in Quadrupedal Locomotion](https://mlsanity.com/paper/2111.12557/) (2021)
- [Efficient Path Planning and Tracking for Multi-Modal Legged-Aerial Locomotion Using Integrated Probabilistic Road Maps (PRM) and Reference Governors (RG)](https://mlsanity.com/paper/2205.06392/) (2022)
- [A Letter on Progress Made on Husky Carbon: A Legged-Aerial, Multi-modal Platform](https://mlsanity.com/paper/2207.12254/) (2022)
- [Dynamic modeling of wing-assisted inclined running with a morphing multi-modal robot](https://mlsanity.com/paper/2311.09963/) (2023)
- [Quadrupedal Locomotion Control On Inclined Surfaces Using Collocation Method](https://mlsanity.com/paper/2312.08621/) (2023)
- [Learning to Locomote with Deep Neural-Network and CPG-based Control in a Soft Snake Robot](https://mlsanity.com/paper/2001.04059/) (2020)
- [Rough-Terrain Locomotion and Unilateral Contact Force Regulations With a Multi-Modal Legged Robot](https://mlsanity.com/paper/2103.15952/) (2021)
- [How Strong a Kick Should be to Topple Northeastern's Tumbling Robot?](https://mlsanity.com/paper/2311.14878/) (2023)
- [Hierarchical RL-Guided Large-scale Navigation of a Snake Robot](https://mlsanity.com/paper/2312.03223/) (2023)
- [Snake Robot with Tactile Perception Navigates on Large-scale Challenging Terrain](https://mlsanity.com/paper/2312.03225/) (2023)

## Abstract (arXiv)

This paper employs a reinforcement learning-based model identification method aimed at enhancing the accuracy of the dynamics for our snake robot, called COBRA. Leveraging gradient information and iterative optimization, the proposed approach refines the parameters of COBRA's dynamical model such as coefficient of friction and actuator parameters using experimental and simulated data. Experimental validation on the hardware platform demonstrates the efficacy of the proposed approach, highlighting its potential to address sim-to-real gap in robot implementation.