Dexterity is a central yet ambiguously defined concept in the design and evaluation of anthropomorphic robotic hands. In practice, the term is often used inconsistently, with different systems evaluated under disparate criteria, making meaningful comparisons across designs difficult. This highlights the need for a unified, performance-based definition of dexterity grounded in measurable outcomes rather than proxy metrics. In this work, we introduce POMDAR, a comprehensive dexterity benchmark that formalizes dexterity as task performance across a structured set of manipulation and grasping motions. The benchmark was systematically derived from established taxonomies in human motor control. It is implemented in both real-world and simulation and includes four manipulation configurations: vertical and horizontal configurations, continuous rotation, and pure grasping. The task designs contain mechanical scaffolding to constrain task motion, suppress compensatory strategies, and enable metrics to be measured unambiguously. We define a quantitative scoring metric combining task correctness and execution speed, effectively measuring dexterity as throughput. This enables objective, reproducible, and interpretable evaluation across different hand designs. POMDAR provides an open-source, standardized, and taxonomy-grounded benchmark for consistent comparison and evaluation of anthropomorphic robot hands to facilitate a systematic advancement of dexterous manipulation platforms. CAD, simulation files, and evaluation videos are publicly available at https://srl-ethz.github.io/POMDAR/.

翻译：灵巧度是仿人灵巧手设计与评估中核心但定义模糊的概念。实践中，该术语常被不一致地使用，不同系统依据不同标准进行评估，导致不同设计之间难以进行有意义的比较。这凸显了对一种以可测量结果而非代理指标为基础的、统一的、基于绩效的灵巧度定义的需求。本文提出POMDAR，一个全面的灵巧度基准，它将灵巧度形式化为在一系列结构化的操作与抓取运动任务中的表现。该基准系统性地源于人类运动控制的既定分类学。它在现实世界与仿真环境中均实现，包含四种操作构型：垂直与水平构型、连续旋转以及纯抓取。任务设计包含机械约束结构，以限制任务运动、抑制补偿策略，并确保指标能被无歧义地测量。我们定义了一个结合任务正确性与执行速度的量化评分指标，有效将灵巧度作为吞吐量进行测量。这使得跨不同手部设计的客观、可重复、可解释的评估成为可能。POMDAR 提供一个开源的、标准化的、基于分类学的基准，用于仿人机器人手的一致性比较与评估，以促进灵巧操作平台的系统性进步。CAD文件、仿真文件及评估视频公开于 https://srl-ethz.github.io/POMDAR/。