# Quadrupedal Robot Skateboard Mounting via Reverse Curriculum Learning

arXiv: https://arxiv.org/abs/2505.06561 · HTML: https://mlsanity.com/paper/2505.06561/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 24 references that are in the map.
- First posted on arXiv 10 May 2025.

## Builds on (most cited first, 15 of 15)

- [Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments](https://mlsanity.com/paper/2301.04195/) (2023)
- [Reverse Curriculum Generation for Reinforcement Learning](https://mlsanity.com/paper/1707.05300/) (2017)
- [Rapid Locomotion via Reinforcement Learning](https://mlsanity.com/paper/2205.02824/) (2022)
- [Extreme Parkour with Legged Robots](https://mlsanity.com/paper/2309.14341/) (2023)
- [Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control](https://mlsanity.com/paper/2401.16889/) (2024)
- [Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion](https://mlsanity.com/paper/2401.17583/) (2024)
- [Actor-Critic Reinforcement Learning for Control with Stability Guarantee](https://mlsanity.com/paper/2004.14288/) (2020)
- [DribbleBot: Dynamic Legged Manipulation in the Wild](https://mlsanity.com/paper/2304.01159/) (2023)
- [Robust Recovery Controller for a Quadrupedal Robot using Deep Reinforcement Learning](https://mlsanity.com/paper/1901.07517/) (2019)
- [Hierarchical Reinforcement Learning for Quadruped Locomotion](https://mlsanity.com/paper/1905.08926/) (2019)
- [Representation-Free Model Predictive Control for Dynamic Motions in Quadrupeds](https://mlsanity.com/paper/2012.10002/) (2020)
- [Quadruped robot traversing 3D complex environments with limited perception](https://mlsanity.com/paper/2404.18225/) (2024)
- [Discrete-Time Hybrid Automata Learning: Legged Locomotion Meets Skateboarding](https://mlsanity.com/paper/2503.01842/) (2025)
- [Stanford Doggo: An Open-Source, Quasi-Direct-Drive Quadruped](https://mlsanity.com/paper/1905.04254/) (2019)
- [Learning Skateboarding for Humanoid Robots through Massively Parallel Reinforcement Learning](https://mlsanity.com/paper/2409.07846/) (2024)

## Abstract (arXiv)

The aim of this work is to enable quadrupedal robots to mount skateboards using Reverse Curriculum Reinforcement Learning. Although prior work has demonstrated skateboarding for quadrupeds that are already positioned on the board, the initial mounting phase still poses a significant challenge. A goal-oriented methodology was adopted, beginning with the terminal phases of the task and progressively increasing the complexity of the problem definition to approximate the desired objective. The learning process was initiated with the skateboard rigidly fixed within the global coordinate frame and the robot positioned directly above it. Through gradual relaxation of these initial conditions, the learned policy demonstrated robustness to variations in skateboard position and orientation, ultimately exhibiting a successful transfer to scenarios involving a mobile skateboard. The code, trained models, and reproducible examples are available at the following link: https://github.com/dancher00/quadruped-skateboard-mounting