mlsanityData to 14 Oct 2026

Curriculum-Based Reinforcement Learning for Quadrupedal Jumping: A Reference-free Design

arXiv 2401.16337 ↗First posted 29 Jan 2024cs.ROcited by 18

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

Abstract (arXiv)

Deep reinforcement learning (DRL) has emerged as a promising solution to mastering explosive and versatile quadrupedal jumping skills. However, current DRL-based frameworks usually rely on pre-existing reference trajectories obtained by capturing animal motions or transferring experience from existing controllers. This work aims to prove that learning dynamic jumping is possible without relying on imitating a reference trajectory by leveraging a curriculum design. Starting from a vertical in-place jump, we generalize the learned policy to forward and diagonal jumps and, finally, we learn to jump across obstacles. Conditioned on the desired landing location, orientation, and obstacle dimensions, the proposed approach yields a wide range of omnidirectional jumping motions in real-world experiments. Particularly we achieve a 90cm forward jump, exceeding all previous records for similar robots reported in the existing literature. Additionally, the robot can reliably execute continuous jumping on soft grassy grounds, which is especially remarkable as such conditions were not included in the training stage. A supplementary video can be found on: https://www.youtube.com/watch?v=nRaMCrwU5X8. The code associated with this work can be found on: https://github.com/Vassil17/Curriculum-Quadruped-Jumping-DRL.

Key facts. Cited by 18 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 25 of its 34 references that are in the map. First posted on arXiv 29 Jan 2024.

Builds on

25 of 34 references.

References · 25

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2020Learning Quadrupedal Locomotion over Challenging Terraincited by 604
  3. 2021Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learningcited by 512
  4. 2021RMA: Rapid Motor Adaptation for Legged Robotscited by 508
  5. 2019Learning agile and dynamic motor skills for legged robotscited by 504
  6. 2022Learning robust perceptive locomotion for quadrupedal robots in the wildcited by 382
  7. 2023Extreme Parkour with Legged Robotscited by 164
  8. 2023ANYmal Parkour: Learning Agile Navigation for Quadrupedal Robotscited by 152
  9. 2022Legged Locomotion in Challenging Terrains using Egocentric Visioncited by 151
  10. 2022Adversarial Motion Priors Make Good Substitutes for Complex Reward Functionscited by 89
  11. 2020ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skillscited by 54
  12. 2021Learning to Jump from Pixelscited by 45
13 more
  1. 2022Learning Agile Skills via Adversarial Imitation of Rough Partial Demonstrationscited by 45
  2. 2023Barkour: Benchmarking Animal-level Agility with Quadruped Robotscited by 41
  3. 2022Advanced Skills through Multiple Adversarial Motion Priors in Reinforcement Learningcited by 37
  4. 2022OPT-Mimic: Imitation of Optimized Trajectories for Dynamic Quadruped Behaviorscited by 35
  5. 2023Learning and Adapting Agile Locomotion Skills by Transferring Experiencecited by 33
  6. 2020Robust Quadruped Jumping via Deep Reinforcement Learningcited by 27
  7. 2021Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learningcited by 17
  8. 2021Discovering Diverse Athletic Jumping Strategiescited by 16
  9. 2023CAJun: Continuous Adaptive Jumping using a Learned Centroidal Controllercited by 15
  10. 2021Contact-timing and Trajectory Optimization for 3D Jumping on Quadruped Robotscited by 10
  11. 2023Continuous Versatile Jumping Using Learned Action Residualscited by 8
  12. 2023Two-Stage Learning of Highly Dynamic Motions with Rigid and Articulated Soft Quadrupedscited by 7
  13. 2022Dynamic Bipedal Maneuvers through Sim-to-Real Reinforcement Learningcited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 9; 2026: 8.

18 papers.

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  1. 2024Constrained Skill Discovery: Quadruped Locomotion with Unsupervised Reinforcement Learningcited by 6
  2. 2025Guided Reinforcement Learning for Omnidirectional 3D Jumping in Quadruped Robotscited by 4
  3. 2025GACL: Grounded Adaptive Curriculum Learning with Active Task and Performance Monitoringcited by 3
  4. 2025Jump-Start Reinforcement Learning with Self-Evolving Priors for Extreme Monopedal Locomotioncited by 1
  5. 2025Integrating Trajectory Optimization and Reinforcement Learning for Quadrupedal Jumping with Terrain-Adaptive Landingcited by 1
  6. 2025Towards Quadrupedal Jumping and Walking for Dynamic Locomotion using Reinforcement Learningcited by 1
  7. 2026EFGCL: Learning Dynamic Motion through Spotting-Inspired External Force Guided Curriculum Learningcited by 1
  8. 2026Trajectory-Level Automatic Curriculum Learning for Legged Locomotion on Unstructured Terraincited by 1
  9. 2026Active Curriculum Refinement for Reinforcement Learningcited by 1
  10. 2025Explosive Jumping with Rigid and Articulated Soft Quadrupeds via Example Guided Reinforcement Learningcited by 0
  11. 2025Symbolic Learning of Interpretable Reduced-Order Models for Jumping Quadruped Robotscited by 0
  12. 2025Acrobotics: A Generalist Approach to Quadrupedal Robots' Parkourcited by 0
6 more
  1. 2025GeCCo -- a Generalist Contact-Conditioned Policy for Loco-Manipulation Skills on Legged Robotscited by 0
  2. 2026Co-jump: Cooperative Jumping with Quadrupedal Robots via Multi-Agent Reinforcement Learningcited by 0
  3. 2026Towards Low-Gravity Planetary Exploration using Reinforcement Learning for Walking, Jumping, and In-flight Attitude Controlcited by 0
  4. 2026PPO-EAL: Exact Augmented Lagrangian Proximal Policy Optimization for Safe Robotic Controlcited by 0
  5. 2026WARL: Wrench-Augmented Reinforcement Learning for Task-Agnostic Learning in Legged Robotscited by 0
  6. 2026Bidirectional Voronoi-biased Exploration Curriculum for 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. 2026Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space ↗
  3. 2025Training Directional Locomotion for Quadrupedal Low-Cost Robotic Systems via Deep Reinforcement Learning
  4. 2022Human Motion Control of Quadrupedal Robots using Deep Reinforcement Learning
  5. 2025Reference Free Platform Adaptive Locomotion for Quadrupedal Robots using a Dynamics Conditioned Policy
  6. 2024Playful DoggyBot: Learning Agile and Precise Quadrupedal Locomotion
  7. 2024Impedance Matching: Enabling an RL-Based Running Jump in a Quadruped Robot
  8. 2025Quadruped Robot Simulation Using Deep Reinforcement Learning -- A step towards locomotion policy