# 从可穿戴界面到灵巧策略：接触转移与触觉表征

> 原文链接：https://robotics.hellobike.com/papers/2026-10-06-2610-08870
> 频道：papers | 更新日期：2026-10-06 | 标签：arxiv, cs.RO
> 核心摘要：研究两版 DexUMI-family 外骨骼界面几何对触觉记录与灵巧策略学习的影响，并在四项操作任务上验证。

# 从可穿戴界面到灵巧策略：接触转移与触觉表征

::: v-pre
> 原文链接：[From Wearable Interfaces to Dexterous Policies: Contact Shifts and Tactile Representations](https://arxiv.org/abs/2610.08870)（arXiv 2610.08870 · 发布日期：2026-10-06）

**From Wearable Interfaces to Dexterous Policies: Contact Shifts and Tactile Representations**

研究两版 DexUMI-family 外骨骼界面几何对触觉记录与灵巧策略学习的影响，并在四项操作任务上验证。

## 核心要点

- 可穿戴遥操作界面降低对目标机器人的依赖，但其几何会影响任务执行方式和触觉观测。
- 比较两版命令定义、映射流程和触觉模块类型相同、手侧几何不同的 DexUMI-family 外骨骼。
- 修订界面降低报告的体力需求，改善部分设备评分，并改变盖子旋拧与蛋盒打开中的接触记录。
- 修订界面示教训练的策略在两项任务上成功率更高，空间加力输入在四项任务上优于二值聚合。

**验证范围与局限**：验证范围为两版 DexUMI-family 外骨骼及盖子旋拧、蛋盒打开、USB 插入、焊接工具拾取放置任务。

## 英文摘要 (Abstract)

Unlike conventional teleoperation, wearable interfaces allow operators to collect dexterous demonstrations through their own hand motions while directly interacting with task objects. This direct interaction reduces dependence on the target robot during collection, but it also makes the collection hardware part of the physical process that generates each demonstration. Interface geometry can influence both how a task is performed and what tactile observations are recorded for learning. We study two versions of a DexUMI-family exoskeleton that share the same robot command definition, mapping procedure, and tactile module type but differ in hand-side geometry. The revised interface reduces reported physical demand, improves selected device ratings, enables tactile access in a precision grasp that is mechanically blocked by the baseline, and produces task-dependent changes in recorded contact. Lid twisting primarily exhibits a change in contact location, whereas egg carton opening primarily exhibits a change in contact occurrence. We then train matched policies using either a binary aggregate input or a spatial-plus-force input. On lid twisting and egg carton opening, policies trained on revised-interface demonstrations achieve higher success than those trained on baseline demonstrations, with a significant pooled interface effect. Across these and two additional tasks, USB insertion and soldering tool pick and place, the spatial-plus-force input likewise outperforms binary aggregation. These results show that wearable collection hardware is part of the data-generation process for robot learning. Such interfaces should therefore be evaluated not only through operator experience, but also through the tactile interactions they make recordable and the policy performance their demonstrations support.

作者：Ruitong Tian, Fang Xu, Noah B. Wilson, Xianyao Li, Eric Jing Du
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## 原始参考来源 (Sources)

- [arXiv 2610.08870：From Wearable Interfaces to Dexterous Policies: Contact Shifts and Tactile Representations](https://arxiv.org/abs/2610.08870)