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This paper introduces KaRMA, a novel kinematic metric designed to evaluate the fine manipulation dexterity of robotic hands by simulating continuous rolling motions rather than relying on static workspace or manipulability proxies. By enforcing joint limits and collision constraints during a breadth-first search, the method effectively distinguishes between robotic hands that appear identical under traditional metrics while revealing critical trade-offs in translation and rotation capabilities. This advancement provides researchers with a more rigorous tool for benchmarking precision pinch tasks, which is essential for advancing soft manipulation and dexterous robotics research.
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KaRMA: A Kinematic Metric for Fine Manipulation Ability in Robotic Hands

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2605.15548v2 Announce Type: replace Abstract: Traditional robotic hand metrics focus on static properties such as workspace, manipulability, and grasp stability. However, these metrics do not directly measure dexterity under the standard definition in robotic manipulation: the ability to continuously change an object's pose within the hand while maintaining contact from an initial grasp. We introduce Kinematic Rolling Manipulation Ability (KaRMA), a kinematic-only metric for fine manipulation that quantifies reachable in-hand translation and reorientation of a spherical test object within a two-finger precision pinch through feasible rolling motions. KaRMA enforces joint limits, collision constraints, rolling contact, and antipodal force feasibility, then explores reachable in-hand object poses via breadth-first search over translation and rotation primitives. KaRMA reports three scores: translational coverage (KaRMA-T), rotational coverage (KaRMA-R), and sensitivity to the initial grasp (KaRMA-S). We evaluate KaRMA on 16 widely used robotic hands and compare against static baselines, showing that KaRMA separates hands that rank identically under static proxies, reveals translation-rotation tradeoffs invisible to existing baselines, and is qualitatively consistent with selected published task benchmarks where Jacobian-based metrics can be misleading. Code and interactive demos are available at https://martinpeticco.com/karma.

Abstract:Traditional robotic hand metrics focus on static properties such as workspace, manipulability, and grasp stability. However, these metrics do not directly measure dexterity under the standard definition in robotic manipulation: the ability to continuously change an object's pose within the hand while maintaining contact from an initial grasp. We introduce Kinematic Rolling Manipulation Ability (KaRMA), a kinematic-only metric for fine manipulation that quantifies reachable in-hand translation and reorientation of a spherical test object within a two-finger precision pinch through feasible rolling motions. KaRMA enforces joint limits, collision constraints, rolling contact, and antipodal force feasibility, then explores reachable in-hand object poses via breadth-first search over translation and rotation primitives. KaRMA reports three scores: translational coverage (KaRMA-T), rotational coverage (KaRMA-R), and sensitivity to the initial grasp (KaRMA-S). We evaluate KaRMA on 16 widely used robotic hands and compare against static baselines, showing that KaRMA separates hands that rank identically under static proxies, reveals translation-rotation tradeoffs invisible to existing baselines, and is qualitatively consistent with selected published task benchmarks where Jacobian-based metrics can be misleading. Code and interactive demos are available at this https URL.

Robotics (cs.RO)

arXiv:2605.15548 [cs.RO]

(or arXiv:2605.15548v2 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2605.15548 Focus to learn more arXiv-issued DOI via DataCite

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