TL;DR
This paper introduces POMDAR, a standardized benchmark for evaluating anthropomorphic robotic hand dexterity through measurable task performance metrics in real-world and simulated environments.
Contribution
It formalizes dexterity as task throughput, providing a comprehensive, reproducible benchmark grounded in human motor control taxonomies for consistent comparison of robotic hands.
Findings
POMDAR enables objective evaluation of robotic hand dexterity.
The benchmark includes diverse manipulation configurations and metrics.
Open-source resources facilitate systematic advancement in robotic manipulation.
Abstract
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…
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