arXiv AI
Bench2Dex: Benchmarking Visuo-Tactile Bimanual Dexterous Manipulation Across Dexterous Hands
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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.