Generate, Track, Improve: Perceptive Multi-Skill Humanoid Locomotion with RL-Fine-Tuned Motion Generators

arXiv:2609.31577 · cs.RO · Submitted 2026-09-25 · Read on arXiv

cs.RO

Submitted: 2026-09-25

Updated: 2026-09-25

Comments: 12 pages

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Flow Matching — 24× in this paper · explained in 8 episodes
• Consistency — 13× in this paper · explained in 3 episodes
• Reinforcement Learning — 12× in this paper · explained in 4 episodes
• Transformer — 9× in this paper · explained in 2 episodes
• Action Space — 4× in this paper · explained in 1 episode
• Distillation — 3× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Steering — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Flow Matching Model — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Lyapunov function — 1× in this paper · explained in 2 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Sim-to-Real Transfer — 1× in this paper · explained in 2 episodes

Sources

• Sim-to-Real Learning of All Common Bipedal Gaits via Periodic Reward Composition
• Chasing Autonomy: Dynamic Retargeting and Control Guided RL for Performant and Controllable Humanoid Running
• Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control
• Perceptive Humanoid Parkour: Chaining Dynamic Human Skills via Motion Matching
• PARC: Physics-based Augmentation with Reinforcement Learning for Character Controllers
• Humanoid Parkour Learning
• RPL: Learning Robust Humanoid Perceptive Locomotion on Challenging Terrains
• Learning Humanoid Locomotion with Perceptive Internal Model
• BeamDojo: Learning Agile Humanoid Locomotion on Sparse Footholds
• Walk the PLANC: Physics-Guided RL for Agile Humanoid Locomotion on Constrained Footholds
• MARCH: Model-Assisted Reinforcement Learning for the Perceptive Control of Humanoids over Sparse Footholds
• SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control
• UniTracker: Learning Universal Whole-Body Motion Tracker for Humanoid Robots
• Parkour in the Wild: Learning a General and Extensible Agile Locomotion Policy Using Multi-expert Distillation and RL Fine-tuning
• Diffuse-CLoC: Guided Diffusion for Physics-based Character Look-ahead Control
• Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning
• Proximal Policy Optimization Algorithms
• DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills
• BeyondMimic: From Motion Tracking to Versatile Humanoid Control via Guided Diffusion
• ZEST: Zero-shot Embodied Skill Transfer for Athletic Robot Control

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