TactileStep: Sole Tactile Learning for Regulating Foot-Terrain Interaction in Humanoid Locomotion

arXiv:2609.28959 · cs.RO · Submitted 2026-09-24 · Read on arXiv

cs.RO

Submitted: 2026-09-24

Updated: 2026-09-24

Project page: https://tactilestep.github.io

Terminology

• Actor — 15× in this paper · explained in 3 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Alignment — 7× in this paper · explained in 1 episode
• Reinforcement Learning — 7× in this paper · explained in 4 episodes
• Calibration — 4× in this paper · explained in 7 episodes
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• AdamW Optimizer — 2× in this paper · explained in 1 episode
• Proximal Policy Optimization — 2× in this paper
• Sim-to-Real Gap — 2× in this paper · explained in 6 episodes
• Sim-to-Real Transfer — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Action Space — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Closed-Loop Control — 1× in this paper · explained in 3 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• International Conference on Robotics and Automation — 1× in this paper
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Partially observable Markov decision process (POMDP) — 1× in this paper · explained in 2 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 4 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Reward Shaping — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• A Unified and General Humanoid Whole-Body Controller for Versatile Locomotion
• Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning
• Humanoid Parkour Learning
• BeamDojo: Learning Agile Humanoid Locomotion on Sparse Footholds
• Hiking in the Wild: A Scalable Perceptive Parkour Framework for Humanoids
• RPL: Learning Robust Humanoid Perceptive Locomotion on Challenging Terrains
• Perceptive Humanoid Parkour: Chaining Dynamic Human Skills via Motion Matching
• QuietWalk: Physics-Informed Reinforcement Learning for Ground Reaction Force-Aware Humanoid Locomotion Under Diverse Footwear
• TTT-Parkour: Rapid Test-Time Training for Perceptive Robot Parkour
• RMA: Rapid Motor Adaptation for Legged Robots
• The Static Center of Pressure Sensitivity: a further Criterion to assess Contact Stability and Balancing Controllers
• Rotating without Seeing: Towards In-hand Dexterity through Touch
• LocoTouch: Learning Dynamic Quadrupedal Transport with Tactile Sensing
• Proximal Policy Optimization Algorithms
• RobotKeyframing: Learning Locomotion with High-Level Objectives via Mixture of Dense and Sparse Rewards
• BeyondMimic: From Motion Tracking to Versatile Humanoid Control via Guided Diffusion
• WoCoCo: Learning Whole-Body Humanoid Control with Sequential Contacts
• Hold My Beer: Learning Gentle Humanoid Locomotion and End-Effector Stabilization Control
• Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning

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