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Bench2Dex benchmark released for visuo-tactile bimanual manipulation

Researchers have introduced Bench2Dex, a new simulation benchmark designed to evaluate visuo-tactile bimanual manipulation capabilities across various dexterous hands. The benchmark features 26 bimanual tasks, including tool use and multi-stage manipulation, supported by approximately 1.3K human-teleoperated demonstrations. Bench2Dex aims to provide a consistent experimental setting for developing and studying visuo-tactile learning algorithms, acknowledging that simulated tactile data may differ from real-world sensor outputs. AI

IMPACT Provides a standardized platform for advancing research in visuo-tactile learning for robotic manipulation.

RANK_REASON The item describes a new benchmark for robotics research published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Bench2Dex benchmark released for visuo-tactile bimanual manipulation

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The item describes a new benchmark for robotics research published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Zhenjie Yang, Yideng Zhang, Dongjie Zhang, Chenyu Jiang, Xianshuai Liu, Yufeng Li, Zuhao Ge, Xingyu Jiao, Zheng Zhang, Kaiyu He, He Wang, Yuwen Zhong, Yi Deng, Muyun Jiang, Xianliang Huang, Haisheng Su, Donghang Zhang, Jian Zhang, Xue Yang, Hongyang Li, … ·

    Bench2Dex: Benchmarking Visuo-Tactile Bimanual Dexterous Manipulation Across Dexterous Hands

    arXiv:2609.15726v1 Announce Type: cross Abstract: 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 surf…