WHED: A Wearable Hand Exoskeleton for Natural, High-Quality Demonstration Collection
Mingzhang Zhu, Alvin Zhu, Jose Victor S. H. Ramos, Beom Jun Kim, Yike Shi, Yufeng Wu, Ruochen Hou, Quanyou Wang, Eric Song, Tony Fan, Yuchen Cui, and Dennis W. Hong

TL;DR
WHED is a wearable hand exoskeleton designed to capture natural, high-fidelity demonstrations of dexterous manipulation in real-world settings, addressing challenges like occlusion and complex hand kinematics.
Contribution
The paper introduces WHED, a novel wearable exoskeleton system with a pose-tolerant thumb coupling and integrated sensing, enabling high-quality demonstration collection for dexterous manipulation.
Findings
Successfully captured natural manipulation demonstrations in real-world scenarios.
Demonstrated qualitative consistency between recorded demonstrations and replayed actions.
Enabled extended use through wearability-first design principles.
Abstract
Scalable learning of dexterous manipulation remains bottlenecked by the difficulty of collecting natural, high-fidelity human demonstrations of multi-finger hands due to occlusion, complex hand kinematics, and contact-rich interactions. We present WHED, a wearable hand-exoskeleton system designed for in-the-wild demonstration capture, guided by two principles: wearability-first operation for extended use and a pose-tolerant, free-to-move thumb coupling that preserves natural thumb behaviors while maintaining a consistent mapping to the target robot thumb degrees of freedom. WHED integrates a linkage-driven finger interface with passive fit accommodation, a modified passive hand with robust proprioceptive sensing, and an onboard sensing/power module. We also provide an end-to-end data pipeline that synchronizes joint encoders, AR-based end-effector pose, and wrist-mounted visual…
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Taxonomy
TopicsStroke Rehabilitation and Recovery · Robot Manipulation and Learning · Motor Control and Adaptation
