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Bench2Dex: Benchmarking Visuo-Tactile Bimanual Dexterous Manipulation Across Dexterous Hands — arXiv:2609.15726

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.15726
License (as archived): CC0-1.0
Archived: 2026-10-15T22:54:01.995Z
SHA-256 of the archived text: 2a25a6f7da2eac844287ae39d05748f522458302ba69a281efa987a0ef1022e3
Stable URL of this page: https://metraipolis.com/documento/dc_e50a4e574b95

How to cite

Bench2Dex: Benchmarking Visuo-Tactile Bimanual Dexterous Manipulation Across Dexterous Hands — arXiv:2609.15726 — arXiv (en), https://arxiv.org/abs/2609.15726 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_e50a4e574b95 (Metraipolis archive dc_e50a4e574b95, sha256 2a25a6f7da2eac844287ae39d05748f522458302ba69a281efa987a0ef1022e3)

BibTeX

@misc{dce50a4e574b95,
  title = {Bench2Dex: Benchmarking Visuo-Tactile Bimanual Dexterous Manipulation Across Dexterous Hands — arXiv:2609.15726},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.15726},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_e50a4e574b95; sha256 2a25a6f7da2eac844287ae39d05748f522458302ba69a281efa987a0ef1022e3},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.15726. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Tactile sensing provides contact information that can be difficult to infer from vision alone, but tactile hardware for dexterous hands has not converged to a common design. Dexterous hands differ in finger structure, contact surfaces, and sensor layouts, while simulated tactile signals still differ from measurements produced by physical sensors. These factors make it difficult to study visuo-tactile manipulation across diverse dexterous hands within a consistent experimental setting. We present Bench2Dex, a simulation benchmark for visuo-tactile bimanual manipulation across 12 dexterous hands. We adapt existing robot models with a shared simulated tactile interface that converts local contact geometry into image-like tactile observations. The interface provides a consistent observation format across different hand morphologies without attempting to reproduce the output of a specific physical tactile sensor. Bench2Dex includes 26 bimanual manipulation tasks that involve tool use, articulated-object interaction, and multi-stage manipulation, together with about 1.3K human-teleoperated demonstrations. The benchmark provides synchronized visual, tactile, proprioceptive, action, and object-state observations, together with executable task metrics. For robustness, we group seven perturbation types into invariance axis, where the correct action does not change, and equivariance axis, where the correct action changes together with the perturbation. We evaluate ACT, Diffusion Policy, pi0.5, and GR00T N1.5 on Bench2Dex and report their performance and failure modes. Bench2Dex is meant as a platform for studying visuo-tactile learning across dexterous hands. It does not assume that simulated tactile observations can replace real tactile sensing; it offers a shared setting for algorithm development while tactile hardware and simulation models are still evolving.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-15 in cs.AI).
Categorie arXiv: Robotics (cs.RO) ; Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV).
Pagina del lavoro: https://arxiv.org/abs/2609.15726 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-15T22:29:03.917Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-09-15?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).