Hugging Face Trending Papers
ProxiDex: Learning Dynamics-Guided Proximity Policy for Dexterous Manipulation
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arXiv AI
Sep 16
ProxiDex: Learning Dynamics-Guided Proximity Policy for Dexterous Manipulation
ProxiDex is a dynamics‑guided proximity policy framework for multi‑finger dexterous manipulation that treats hand‑object proximity as an interaction state. It reconstructs interaction point clouds, converts geometric distances into proximity cues, and learns action‑conditioned proximity dynamics using a coupled forward‑inverse design. The framework adaptively reweights proximity tokens across manipulation phases and employs dynamics‑consistency supervision to stabilize action generation, leading to improved success rates and robustness in both simulation and real‑world experiments.
arXiv AI
Jul 13
Tactile and Vision Conditioned Contact-Centric Control for Whole-Arm Manipulation
arXiv:2607. 09218v1 Announce Type: cross Abstract: Whole-arm manipulation involves direct contact with the environment while the robot completes a task by distributing contact across multiple links as contacts form, slide, and break.
arXiv AI
Oct 15
DexFLEX: Contact-Aware Foundation Controller for Command-Guided Dexterity
arXiv:2610.14372v1 Announce Type: cross Abstract: Dexterous robot hands can receive useful motion intent from teleoperation or learned policies, but successful execution also depends on contact decis...
arXiv AI
Sep 30
Unified Visual-Tactile-Action Modeling from Human Demonstrations for Dexterous Manipulation
arXiv:2609.34182v2 Announce Type: replace-cross Abstract: Dexterous manipulation requires tactile feedback. However, robot tactile demonstrations are difficult to scale,because dexterous-hand teleope...
arXiv Computer Vision
Oct 23
PiHand: Latent Hand-Object Interaction Priors for Physics-Based Policy Learning
PiHand is a physics‑based framework that learns latent hand‑object interaction priors for dexterous manipulation. It first trains expert policies to track motion capture demonstrations, then distills these into a goal‑conditioned VAE that captures coupled hand‑object motion. Using bounded residual exploration in this latent space, PiHand produces general tabletop manipulation policies that generalize to unseen objects and trajectories, outperforming baselines across multiple tasks.
arXiv AI
Jul 14
TACTIC: Tactile and Vision Conditioned Contact-Centric Control for Whole-Arm Manipulation
arXiv:2607. 09218v2 Announce Type: replace-cross Abstract: Whole-arm manipulation involves direct contact with the environment while the robot completes a task by distributing contact across multiple links as contacts form, slide, and break.