mlsanityData to 14 Oct 2026

Isaac Sim-to-Real: Reinforcement Learning based Locomotion for Quadrupeds

arXiv 2607.18135 ↗First posted 20 Jul 2026cs.RO cs.LGcited by 2

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

Abstract (arXiv)

Learning-based approaches to locomotion have risen in popularity in recent years, showing the capability for complex legged locomotion and whole-body control. Reinforcement learning (RL), the primary learning-based approach for locomotion, often utilizes a high-performance simulation tool, providing a controlled and efficient training and development environment. However, policies that perform well in simulation frequently encounter unexpected challenges when deployed on a physical system, known as the sim-to-real gap. This work presents a robust RL locomotion framework capable of whole-body control. The proposed RL framework utilizes Nvidia's new set of simulation tools, Isaac Sim, and its companion RL framework, Isaac Lab, for training, achieving a zero-shot sim-to-real policy. The performance of our policy is validated on physical hardware using the Unitree Go1, with experimental results showing similar velocity tracking performance to the quadruped's integrated controller, with a greater ability to recover from large disturbances, and achieve linear velocities of 2.0 m/s and angular velocities of 1.8 rad/s.

Key facts. Cited by 2 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 23 of its 36 references that are in the map. First posted on arXiv 20 Jul 2026.

Builds on

23 of 36 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025Benchmarking Model Predictive Control and Reinforcement Learning Based Control for Legged Robot Locomotion in MuJoCo Simulation28 Jan
  2. 2024A Review of Nine Physics Engines for Reinforcement Learning Research11 Jul

Other references · 21

  1. 2016OpenAI Gymcited by 1,736
  2. 2021Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learningcited by 998
  3. 2021Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learningcited by 512
  4. 2019Learning agile and dynamic motor skills for legged robotscited by 504
  5. 2023Orbit: A Unified Simulation Framework for Interactive Robot Learning Environmentscited by 295
  6. 2022Walk These Ways: Tuning Robot Control for Generalization with Multiplicity of Behaviorcited by 138
  7. 2025MuJoCo Playgroundcited by 78
  8. 2021Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real Worldcited by 71
  9. 2021Learning to Jump from Pixelscited by 45
  10. 2022Learning Torque Control for Quadrupedal Locomotioncited by 29
  11. 2020Guided Constrained Policy Optimization for Dynamic Quadrupedal Robot Locomotioncited by 25
  12. 2022Learning Visual Locomotion with Cross-Modal Supervisioncited by 25
9 more
  1. 2021Robust High-speed Running for Quadruped Robots via Deep Reinforcement Learningcited by 22
  2. 2022Visual CPG-RL: Learning Central Pattern Generators for Visually-Guided Quadruped Locomotioncited by 14
  3. 2021Comparing Popular Simulation Environments in the Scope of Robotics and Reinforcement Learningcited by 12
  4. 2023SYNLOCO: Synthesizing Central Pattern Generator and Reinforcement Learning for Quadruped Locomotioncited by 6
  5. 2017Fast Trajectory Optimization for Legged Robots using Vertex-based ZMP Constraintscited by 5
  6. 2023Actuator-Constrained Reinforcement Learning for High-Speed Quadrupedal Locomotioncited by 5
  7. 2014Tools for dynamics simulation of robots: a survey based on user feedbackcited by 3
  8. 2023Manipulator as a Tail: Promoting Dynamic Stability for Legged Locomotioncited by 3
  9. 2023A Real-World Quadrupedal Locomotion Benchmark for Offline Reinforcement Learningcited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Towards Miniature Humanoid Tele-Loco-Manipulation Using Virtual Reality and Reinforcement Learningcited by 0
  2. 2026Loco-Loco-RL: Low-Cost Terrain Mapping for Humanoid Locomotion with Reinforcement Learningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Reinforcement Learning For Quadrupedal Locomotion: Current Advancements And Future Perspectives
  2. 2025Sim-to-Real Transfer for Mobile Robots with Reinforcement Learning: from NVIDIA Isaac Sim to Gazebo and Real ROS 2 Robots
  3. 2025A Framework for Deploying Learning-based Quadruped Loco-Manipulation ↗
  4. 2026Towards Torque-Driven Reinforcement Learning for Quadruped Locomotion
  5. 2025Sim-to-Real Transfer in Deep Reinforcement Learning for Bipedal Locomotion
  6. 2025Learning to Walk With Less: A Dyna-Style Approach to Quadrupedal Locomotion
  7. 2024Impedance Matching: Enabling an RL-Based Running Jump in a Quadruped Robot
  8. 2024MetaLoco: Universal Quadrupedal Locomotion with Meta-Reinforcement Learning and Motion Imitation