arXiv (All)
open access
ForeTac: Predictive Contact Guidance for Generative Robot Policies
Visually similar actions can produce contact loss, jamming, slippage, or irreversible damage, while tactile feedback may arrive after a critical transition. Contact-rich manipulation therefore requires generative policies to anticipate and evaluate whether candidate actions will produce desirable co
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
- PSR: Predictive Sensorimotor Representation Learning for Contact-Rich Manipulation#1036143
- ContactWorld: What Representations Matter in Vision-Tactile World Models for Contact-Rich Manipulation#985130
- Contact Trajectory Prompting: In-Context Transfer of Contact-Rich Behaviors from a Single Demonstration#1344338
- ViTacWorld: Scaling Visuo-Tactile World Models for Contact-Rich Robot Manipulation#1118664
- TactileStep: Sole Tactile Learning for Regulating Foot-Terrain Interaction in Humanoid Locomotion#1076615
Record · ID 1343307
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