# Explosive Jumping with Rigid and Articulated Soft Quadrupeds via Example Guided Reinforcement Learning

arXiv: https://arxiv.org/abs/2503.16197 · HTML: https://mlsanity.com/paper/2503.16197/

## 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 15 of its 31 references that are in the map.
- First posted on arXiv 20 Mar 2025.

## 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, 15 of 15)

- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Learning Quadrupedal Locomotion over Challenging Terrain](https://mlsanity.com/paper/2010.11251/) (2020)
- [Sim-to-Real: Learning Agile Locomotion For Quadruped Robots](https://mlsanity.com/paper/1804.10332/) (2018)
- [Learning Agile Robotic Locomotion Skills by Imitating Animals](https://mlsanity.com/paper/2004.00784/) (2020)
- [DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills](https://mlsanity.com/paper/1804.02717/) (2018)
- [Learning Agile Skills via Adversarial Imitation of Rough Partial Demonstrations](https://mlsanity.com/paper/2206.11693/) (2022)
- [OPT-Mimic: Imitation of Optimized Trajectories for Dynamic Quadruped Behaviors](https://mlsanity.com/paper/2210.01247/) (2022)
- [Robust Quadruped Jumping via Deep Reinforcement Learning](https://mlsanity.com/paper/2011.07089/) (2020)
- [Curriculum-Based Reinforcement Learning for Quadrupedal Jumping: A Reference-free Design](https://mlsanity.com/paper/2401.16337/) (2024)
- [Learning-based Design and Control for Quadrupedal Robots with Parallel-Elastic Actuators](https://mlsanity.com/paper/2301.03509/) (2023)
- [Continuous Jumping for Legged Robots on Stepping Stones via Trajectory Optimization and Model Predictive Control](https://mlsanity.com/paper/2204.01147/) (2022)
- [Two-Stage Learning of Highly Dynamic Motions with Rigid and Articulated Soft Quadrupeds](https://mlsanity.com/paper/2309.09682/) (2023)
- [Kinodynamic Motion Planning for Multi-Legged Robot Jumping via Mixed-Integer Convex Program](https://mlsanity.com/paper/2011.01809/) (2020)
- [An Optimal Motion Planning Framework for Quadruped Jumping](https://mlsanity.com/paper/2207.12002/) (2022)
- [Oncilla robot: a versatile open-source quadruped research robot with compliant pantograph legs](https://mlsanity.com/paper/1803.06259/) (2018)

## Abstract (arXiv)

Achieving controlled jumping behaviour for a quadruped robot is a challenging task, especially when introducing passive compliance in mechanical design. This study addresses this challenge via imitation-based deep reinforcement learning with a progressive training process. To start, we learn the jumping skill by mimicking a coarse jumping example generated by model-based trajectory optimization. Subsequently, we generalize the learned policy to broader situations, including various distances in both forward and lateral directions, and then pursue robust jumping in unknown ground unevenness. In addition, without tuning the reward much, we learn the jumping policy for a quadruped with parallel elasticity. Results show that using the proposed method, i) the robot learns versatile jumps by learning only from a single demonstration, ii) the robot with parallel compliance reduces the landing error by 11.1%, saves energy cost by 15.2% and reduces the peak torque by 15.8%, compared to the rigid robot without parallel elasticity, iii) the robot can perform jumps of variable distances with robustness against ground unevenness (maximal 4cm height perturbations) using only proprioceptive perception.