GuideWalk: Learning Unified Autonomous Navigation and Locomotion for Humanoid Robots across Versatile Terrains

arXiv:2606.10449 · cs.RO · Submitted 2026-06-09 · Read on arXiv

cs.RO

Submitted: 2026-06-09

Updated: 2026-09-19

Project page: https://guide-walk.github.io/GuideWalk

Terminology

• Reinforcement Learning — 17× in this paper · explained in 4 episodes
• Distillation — 14× in this paper · explained in 2 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Imitation Learning — 4× in this paper
• Behavior Cloning — 3× in this paper
• Consistency — 3× in this paper · explained in 3 episodes
• Actor — 2× in this paper · explained in 3 episodes
• Computational overhead — 2× in this paper · explained in 2 episodes
• Decoupling — 2× in this paper · explained in 2 episodes
• Dynamic Window Approach — 2× in this paper
• IEEE International Conference on Robotics and Automation — 2× in this paper
• Proximal Policy Optimization — 2× in this paper
• Proximity to Obstacles — 2× in this paper
• Reward Shaping — 2× in this paper · explained in 2 episodes
• Two-stage training — 2× in this paper · explained in 2 episodes
• Action Space — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Catastrophic Forgetting — 1× in this paper · explained in 5 episodes
• Convolutional Neural Network — 1× in this paper
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Field of View — 1× in this paper
• Imitation Learning (IL) — 1× in this paper · explained in 2 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Multi-Layer Perceptron — 1× in this paper
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• RL with Adversarial Motion Priors — 1× in this paper
• Redundancy — 1× in this paper · explained in 2 episodes
• Regret — 1× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Robot Operating System — 1× in this paper
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Sim-to-Real Gap — 1× in this paper · explained in 6 episodes
• Sim-to-Real Transfer — 1× in this paper · explained in 2 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Perceptive Humanoid Parkour: Chaining Dynamic Human Skills via Motion Matching
• OmniXtreme: Breaking the Generality Barrier in High-Dynamic Humanoid Control
• Hiking in the Wild: A Scalable Perceptive Parkour Framework for Humanoids
• Real-Time Navigation for Bipedal Robots in Dynamic Environments
• VB-Com: Learning Vision-Blind Composite Humanoid Locomotion Against Deficient Perception
• Gallant: Voxel Grid-based Humanoid Locomotion and Local-navigation across 3D Constrained Terrains
• FocusNav: Spatial Selective Attention with Waypoint Guidance for Humanoid Local Navigation
• Proximal Policy Optimization Algorithms
• Now You See That: Learning End-to-End Humanoid Locomotion from Raw Pixels

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