TacOT: Learning Contact-Rich Dexterous Manipulation from Human Demonstrations via Tactile-Guided Optimal Transport
cs.RO
Submitted: 2026-10-03
Updated: 2026-10-03
Comments: 9 pages, 8 figures
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Open X-Embodiment: Robotic Learning Datasets and RT-X Models
- VT-MUSE: Multimodal Unified Sequential Visuotactile Representation Learning for Manipulation
- TactAlign: Human-to-Robot Policy Transfer via Tactile Alignment
- UniTacHand: Unified Spatio-Tactile Representation for Human to Robotic Hand Skill Transfer
- Do as I Do: Dexterous Manipulation Data from Everyday Human Videos
- Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos
- Scalable Vision-Language-Action Model Pretraining for Robotic Manipulation with Real-Life Human Activity Videos
- Being-H0.5: Scaling Human-Centric Robot Learning for Cross-Embodiment Generalization
- DexHiL: A Human-in-the-Loop Framework for Vision-Language-Action Model Post-Training in Dexterous Manipulation
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