arXiv (All)
open access
TactileStep: Sole Tactile Learning for Regulating Foot-Terrain Interaction in Humanoid Locomotion
Humanoid parkour policies can traverse various terrains, but task completion may mask challenges of harsh landings, edge contacts, and unstable stance contacts. Humans naturally regulate foot-terrain interaction through tactile feedback, modulating contact compliance according to terrain stiffness.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- CMoE: Contrastive Mixture of Experts for Motion Control and Terrain Adaptation of Humanoid Robots#998124
- PSR: Predictive Sensorimotor Representation Learning for Contact-Rich Manipulation#1036143
- Machine Learning Electrostatic Interactions in Materials#922124
- Frequency-aware decomposition learning for sensorless wrench estimation in vibration-rich robotic contact#1155165
- ContactWorld: What Representations Matter in Vision-Tactile World Models for Contact-Rich Manipulation#985130
Record · ID 1076615
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive