aiqbench analysis
This research advances robotic manipulation by introducing a real-time force regulation framework that maintains stable whole-hand grasps despite dynamic object motion and external disturbances. By leveraging geometric contact estimation and proprioception rather than relying on tactile sensors, the method achieves robust performance in both simulation and physical 27-DoF arm-hand systems. The work represents a significant step forward in machine learning for robotics (cs.RO) and systems control, focusing on actuation consistency and reactive grasping strategies.
Real-Time Force Regulation for Whole-Hand Dexterous Grasping
arXiv:2609.30082v1 Announce Type: new Abstract: Robust dexterous grasping requires maintaining physical stability despite contacts interactively evolving across the entire hand. A precomputed force distribution can easily fail under object motion, modeling errors, or external disturbances. In this paper, we present a framework for real-time force regulation over dynamically changing whole-hand contacts. Our method geometrically estimates contacts across all hand links using a tracked object model and proprioception, without requiring tactile sensing at those contacts. It repeatedly recomputes the desired contact-force distribution subject to friction constraints, actuator limits, and an actuation-consistency constraint motivated by classical whole-limb force analysis. We integrate this force-regulation controller with reactive reaching, enabling the hand to acquire a grasp, maintain it under disturbances, and regrasp after losing the object. Simulation experiments without gravity demonstrate improved grasp retention over fixed-allocation and fingertip-only execution under controlled perturbations, while real-world experiments on a 27-DoF arm-hand system demonstrate grasp maintenance and recovery under human-applied disturbances as contacts evolve across the whole hand. Project page: https://sangminkim-99.github.io/reactive-grasp-whole-hand/
Abstract:Robust dexterous grasping requires maintaining physical stability despite contacts interactively evolving across the entire hand. A precomputed force distribution can easily fail under object motion, modeling errors, or external disturbances. In this paper, we present a framework for real-time force regulation over dynamically changing whole-hand contacts. Our method geometrically estimates contacts across all hand links using a tracked object model and proprioception, without requiring tactile sensing at those contacts. It repeatedly recomputes the desired contact-force distribution subject to friction constraints, actuator limits, and an actuation-consistency constraint motivated by classical whole-limb force analysis. We integrate this force-regulation controller with reactive reaching, enabling the hand to acquire a grasp, maintain it under disturbances, and regrasp after losing the object. Simulation experiments without gravity demonstrate improved grasp retention over fixed-allocation and fingertip-only execution under controlled perturbations, while real-world experiments on a 27-DoF arm-hand system demonstrate grasp maintenance and recovery under human-applied disturbances as contacts evolve across the whole hand. Project page: this https URL
9 pages, 10 figures. Project page: this https URL
Robotics (cs.RO); Systems and Control (eess.SY)
arXiv:2609.30082 [cs.RO]
(or arXiv:2609.30082v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2609.30082 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 267 words
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