DexTouch-WM: Learning Action-Conditioned Tactile World Models from Human Touch for Dexterous Robot Manipulation

arXiv:2609.20649 · cs.RO, cs.CV · Submitted 2026-09-17 · Read on arXiv

cs.RO, cs.CV

Submitted: 2026-09-17

Updated: 2026-09-18

Terminology

• World Model — 30× in this paper · explained in 7 episodes
• Consistency — 10× in this paper · explained in 3 episodes
• Alignment — 9× in this paper · explained in 1 episode
• Adaptation — 8× in this paper · explained in 1 episode
• Fidelity — 7× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Transformer — 4× in this paper · explained in 2 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Embeddings — 3× in this paper · explained in 2 episodes
• Joint Attention — 3× in this paper · explained in 2 episodes
• Tokenization — 3× in this paper · explained in 2 episodes
• Action-Conditioned Dynamics — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Flow Matching — 2× in this paper · explained in 8 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Reconstruction Error — 2× in this paper · explained in 2 episodes
• Semantic Alignment — 2× in this paper · explained in 3 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Action-Conditioned World Model — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes

Sources

• DexViTac: Collecting Human Visuo-Tactile-Kinematic Demonstrations for Contact-Rich Dexterous Manipulation
• GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation
• FeelWorld: Visuo-Tactile World Model for Hierarchical Contact Prediction and Planning
• WorldArena: A Unified Benchmark for Evaluating Perception and Functional Utility of Embodied World Models
• OPENTOUCH: Bringing Full-Hand Touch to Real-World Interaction
• Wan: Open and Advanced Large-Scale Video Generative Models
• FreeTacMan: Robot-free Visuo-Tactile Data Collection System for Contact-rich Manipulation
• FTP-1: A Generalist Foundation Tactile Policy Across Tactile Sensors for Contact-Rich Manipulation
• TouchWorld: A Predictive and Reactive Tactile Foundation Model for Dexterous Manipulation
• Touch in the Wild: Learning Fine-Grained Manipulation with a Portable Visuo-Tactile Gripper

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