mlsanityData to 14 Oct 2026

Learning-based legged locomotion; state of the art and future perspectives

arXiv 2406.01152 ↗First posted 3 Jun 2024cs.ROcited by 23

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Abstract (arXiv)

Legged locomotion holds the premise of universal mobility, a critical capability for many real-world robotic applications. Both model-based and learning-based approaches have advanced the field of legged locomotion in the past three decades. In recent years, however, a number of factors have dramatically accelerated progress in learning-based methods, including the rise of deep learning, rapid progress in simulating robotic systems, and the availability of high-performance and affordable hardware. This article aims to give a brief history of the field, to summarize recent efforts in learning locomotion skills for quadrupeds, and to provide researchers new to the area with an understanding of the key issues involved. With the recent proliferation of humanoid robots, we further outline the rapid rise of analogous methods for bipedal locomotion. We conclude with a discussion of open problems as well as related societal impact.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Jun 2024.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 12; 2026: 11.

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  1. 2025Being-0: A Humanoid Robotic Agent with Vision-Language Models and Modular Skillscited by 22
  2. 2025AMOR: Adaptive Character Control through Multi-Objective Reinforcement Learningcited by 9
  3. 2025UniConFlow: A Unified Constrained Flow-Matching Framework for Certified Motion Planningcited by 5
  4. 2025Forging Spatial Intelligence: A Roadmap of Multi-Modal Data Pre-Training for Autonomous Systemscited by 4
  5. 2025Benchmarking Model Predictive Control and Reinforcement Learning Based Control for Legged Robot Locomotion in MuJoCo Simulationcited by 3
  6. 2026Learning Hip Exoskeleton Control Policy via Predictive Neuromusculoskeletal Simulationcited by 2
  7. 2026Efficient and Versatile Quadrupedal Skating: Optimal Co-design via Reinforcement Learning and Bayesian Optimizationcited by 2
  8. 2025MASH: Cooperative-Heterogeneous Multi-Agent Reinforcement Learning for Single Humanoid Robot Locomotioncited by 1
  9. 2026TRANS: Terrain-aware Reinforcement Learning for Agile Navigation of Quadruped Robots under Social Interactionscited by 1
  10. 2026SLowRL: Safe Low-Rank Adaptation Reinforcement Learning for Locomotioncited by 1
  11. 2025CAIMAN: Causal Action Influence Detection for Sample-efficient Loco-manipulationcited by 0
  12. 2025Dynamic Legged Ball Manipulation on Rugged Terrains with Hierarchical Reinforcement Learningcited by 0
11 more
  1. 2025Physically Consistent Humanoid Loco-Manipulation using Latent Diffusion Modelscited by 0
  2. 2025Learning Impact-Rich Rotational Maneuvers via Centroidal Velocity Rewards and Sim-to-Real Techniques: A One-Leg Hopper Flip Case Studycited by 0
  3. 2025Whole-Body Constrained Learning for Legged Locomotion via Hierarchical Optimizationcited by 0
  4. 2025Dynamic Adaptive Legged Locomotion Policy via Decoupling Reaction Force Control and Gait Controlcited by 0
  5. 2026Predictive Style Matching: Natural and Robust Humanoid Locomotioncited by 0
  6. 2026Comparative Study on Agility, Efficiency, and Impact Absorption of Bipedal Robots with Active Toescited by 0
  7. 2026CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Liftscited by 0
  8. 2026SafeExplorer: An Unbiased Policy Gradient for Reinforcement Learning with Recovery Interventionscited by 0
  9. 2026WARL: Wrench-Augmented Reinforcement Learning for Task-Agnostic Learning in Legged Robotscited by 0
  10. 2026Bicycle Acrobatics with Reinforcement Learningcited by 0
  11. 2026FERPO: Forward Entropy-Regularized Policy Optimizationcited by 0