mlsanityData to 14 Oct 2026

Quadruped Locomotion on Non-Rigid Terrain using Reinforcement Learning

arXiv 2107.02955 ↗First posted 7 Jul 2021cs.RO cs.AIcited by 2

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Abstract (arXiv)

Legged robots need to be capable of walking on diverse terrain conditions. In this paper, we present a novel reinforcement learning framework for learning locomotion on non-rigid dynamic terrains. Specifically, our framework can generate quadruped locomotion on flat elastic terrain that consists of a matrix of tiles moving up and down passively when pushed by the robot's feet. A trained robot with 55cm base length can walk on terrain that can sink up to 5cm. We propose a set of observation and reward terms that enable this locomotion; in which we found that it is crucial to include the end-effector history and end-effector velocity terms into observation. We show the effectiveness of our method by training the robot with various terrain conditions.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 26 of its 35 references that are in the map. First posted on arXiv 7 Jul 2021.

Builds on

26 of 35 references.

References · 26

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
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  4. 2020Learning Quadrupedal Locomotion over Challenging Terraincited by 604
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  9. 2018DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skillscited by 163
  10. 2018Learning to Walk via Deep Reinforcement Learningcited by 158
  11. 2020Learning to Walk in the Real World with Minimal Human Effortcited by 111
  12. 2019Data Efficient Reinforcement Learning for Legged Robotscited by 63
14 more
  1. 2018Learning Symmetric and Low-energy Locomotioncited by 61
  2. 2020ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skillscited by 54
  3. 2019DeepGait: Planning and Control of Quadrupedal Gaits using Deep Reinforcement Learningcited by 50
  4. 2018Feedback Control For Cassie With Deep Reinforcement Learningcited by 45
  5. 2019Robust Recovery Controller for a Quadrupedal Robot using Deep Reinforcement Learningcited by 32
  6. 2020Guided Constrained Policy Optimization for Dynamic Quadrupedal Robot Locomotioncited by 25
  7. 2017Whole-Body Nonlinear Model Predictive Control Through Contacts for Quadrupedscited by 20
  8. 2020Circus ANYmal: A Quadruped Learning Dexterous Manipulation with Its Limbscited by 16
  9. 2019Training in Task Space to Speed Up and Guide Reinforcement Learningcited by 7
  10. 2020CARL: Controllable Agent with Reinforcement Learning for Quadruped Locomotioncited by 7
  11. 2019STANCE: Locomotion Adaptation over Soft Terraincited by 4
  12. 2020Dynamic Legged Manipulation of a Ball Through Multi-Contact Optimizationcited by 4
  13. 2020Contact-Implicit Trajectory Optimization using an Analytically Solvable Contact Model for Locomotion on Variable Groundcited by 3
  14. 2020Dynamics and Domain Randomized Gait Modulation with Bezier Curves for Sim-to-Real Legged Locomotioncited by 3

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Citing papers per year: 2023: 1; 2024: 0; 2025: 1.

2 papers.

  1. 2023Efficient Reinforcement Learning for Jumping Monopodscited by 1
  2. 2025SATA: Safe and Adaptive Torque-Based Locomotion Policies Inspired by Animal Learningcited by 1