Saved in:
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.17908 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866908882885935104 |
|---|---|
| author | Zhu, Mingzhang Zhu, Alvin Ramos, Jose Victor S. H. Kim, Beom Jun Shi, Yike Wu, Yufeng Hou, Ruochen Wang, Quanyou Song, Eric Fan, Tony Cui, Yuchen Hong, Dennis W. |
| author_facet | Zhu, Mingzhang Zhu, Alvin Ramos, Jose Victor S. H. Kim, Beom Jun Shi, Yike Wu, Yufeng Hou, Ruochen Wang, Quanyou Song, Eric Fan, Tony Cui, Yuchen Hong, Dennis W. |
| contents | 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 observations, and supports post-processing for time alignment and replay. We demonstrate feasibility on representative grasping and manipulation sequences spanning precision pinch and full-hand enclosure grasps, and show qualitative consistency between collected demonstrations and replayed executions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_17908 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | WHED: A Wearable Hand Exoskeleton for Natural, High-Quality Demonstration Collection Zhu, Mingzhang Zhu, Alvin Ramos, Jose Victor S. H. Kim, Beom Jun Shi, Yike Wu, Yufeng Hou, Ruochen Wang, Quanyou Song, Eric Fan, Tony Cui, Yuchen Hong, Dennis W. Robotics 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 observations, and supports post-processing for time alignment and replay. We demonstrate feasibility on representative grasping and manipulation sequences spanning precision pinch and full-hand enclosure grasps, and show qualitative consistency between collected demonstrations and replayed executions. |
| title | WHED: A Wearable Hand Exoskeleton for Natural, High-Quality Demonstration Collection |
| topic | Robotics |
| url | https://arxiv.org/abs/2602.17908 |