外观
论文arXiv 2608.186182 个月前
LabDex：面向实验室灵巧操作的层次化基准
原文链接：LabDex: A Hierarchical Benchmark for Dexterous Manipulation in Laboratories（arXiv 2608.18618 · 发布日期：2026-08-19）
LabDex: A Hierarchical Benchmark for Dexterous Manipulation in Laboratories
LabDex针对实验室灵巧操作评测不足，构建层次化真实数据集与基准，并在真实与仿真环境中验证。
核心要点
- 现有基准难以同时覆盖灵巧手使用、真实实验室交互和多阶段实验流程。
- LabDex按原子技能、组合技能和长时程实验构建层次化任务分类。
- 该框架统一真实与仿真平台，提供标准任务定义、演示和评估协议。
- 跨层级实验显示，其任务设计与演示数据可支持策略训练和系统评估。
验证范围与局限：验证范围为真实世界与仿真环境中的化学实验室灵巧操作任务。
英文摘要 (Abstract)
Autonomous laboratories hold great promise for accelerating scientific discovery. To achieve this vision, robots are supposed to dexterously manipulate diverse labware and instruments and execute long-horizon, state-dependent experimental procedures. Yet existing benchmarks do not jointly capture dexterous hand use, real-world laboratory interactions, and multi-stage experimental procedures, limiting systematic training and evaluation. To bridge this gap, we introduce LabDex, a large-scale real-world dataset and benchmark for dexterous manipulation in chemistry laboratories, organized around a hierarchical task taxonomy spanning atomic skills, compositional tasks, and long-horizon experiments. First, LabDex is cross-platform and, for the first time, unifies real-world and simulation platforms under a common framework, providing standardized task definitions, demonstrations, and evaluation protocols. Second, LabDex is large-scale and systematically organizes chemistry laboratory operations into three interconnected levels: Atomic Skills, which characterize fundamental dexterous manipulation capabilities; Compositional Skills; and Long-Horizon Laboratory Workflows. This hierarchical design not only supports the evaluation of end-task performance, but also enables the analysis of how fundamental dexterous skills compose and influence more complex laboratory operations. We conduct cross-level evaluations of representative robot learning methods in both real-world and simulation environments. The experimental results validate the effectiveness of the LabDex task design and demonstration data, and show that the benchmark supports the training and systematic evaluation of existing robotic policies across laboratory dexterous manipulation tasks at different levels, providing a foundation for further research and development of autonomous laboratory robots.
作者：Zhipeng Tang, Sihang Chen, Sha Zhang, Peihao Yang, Yan Liu, Wentao Zhao, Xinrui Liu, Rui Huang, Wensheng Du, Yuting Huang
来源
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