arXiv (OAI Expanded)
open access
Weave: Learning Whole-Body Dexterous Loco-Manipulation from Human-Object Interactions
Learning humanoid-object interaction requires coordinating whole-body balance, locomotion, and dexterous hand contact to control both robot and object motion. Human demonstrations provide examples of coordinated interaction, but transferring these behaviors to humanoid robots requires learning how t
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
- DexWeave: Learning Dexterous Humanoid Loco-Manipulation from Human Demonstrations#1128982
- DexTaG: Tactile-as-Guidance in Reinforcement Learning for Dexterous Manipulation#1118955
- Towards a General Humanoid Loco-Manipulation Model via Egocentric Whole-Body Human Data Pretraining#1155373
- WholeBodyWAM: Learning Whole-Body World Action Models with Scalable Motion Priors#1011891
- One Demonstration, Many Objects: Generalizing Manipulation via Local Contact Geometry#926242
Record · ID 1122695
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