mlsanityData to 14 Oct 2026

Learning Skateboarding for Humanoid Robots through Massively Parallel Reinforcement Learning

arXiv 2409.07846 ↗First posted 12 Sep 2024cs.ROcited by 1

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

Abstract (arXiv)

Learning-based methods have proven useful at generating complex motions for robots, including humanoids. Reinforcement learning (RL) has been used to learn locomotion policies, some of which leverage a periodic reward formulation. This work extends the periodic reward formulation of locomotion to skateboarding for the REEM-C robot. Brax/MJX is used to implement the RL problem to achieve fast training. Initial results in simulation are presented with hardware experiments in progress.

Key facts. Cited by 1 paper 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 8 of its 12 references that are in the map. First posted on arXiv 12 Sep 2024.

Builds on

8 of 12 references.

References · 8

  1. 2021Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learningcited by 512
  2. 2021Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulationcited by 407
  3. 2020Sim-to-Real Learning of All Common Bipedal Gaits via Periodic Reward Compositioncited by 96
  4. 2023Barkour: Benchmarking Animal-level Agility with Quadruped Robotscited by 41
  5. 2021DeepWalk: Omnidirectional Bipedal Gait by Deep Reinforcement Learningcited by 21
  6. 2023Learning Bipedal Walking for Humanoids with Current Feedbackcited by 18
  7. 2022Learning Bipedal Walking On Planned Footsteps For Humanoid Robotscited by 12
  8. 2024Learning Velocity-based Humanoid Locomotion: Massively Parallel Learning with Brax and MJXcited by 2

Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.

  1. 2025Quadrupedal Robot Skateboard Mounting via Reverse Curriculum Learningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Reinforcement Learning-Based Control for an Inline Skating Humanoid Robot
  2. 2024Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control
  3. 2025Learning Sim-to-Real Humanoid Locomotion in 15 Minutes
  4. 2025Discrete-Time Hybrid Automata Learning: Legged Locomotion Meets Skateboarding
  5. 2025Taxonomy and Trends in Reinforcement Learning for Robotics and Control Systems: A Structured Review
  6. 2025Robot Trains Robot: Automatic Real-World Policy Adaptation and Learning for Humanoids
  7. 2025A Gait Driven Reinforcement Learning Framework for Humanoid Robots
  8. 2025Booster Gym: An End-to-End Reinforcement Learning Framework for Humanoid Robot Locomotion