外观
论文arXiv 2610.0078128 天前
DITTO-X：用于灵巧操作与人类干预的正向和反向遥操作
原文链接：DITTO-X: Forward and Reverse Teleoperation for Dexterous Manipulation and Human Intervention（arXiv 2610.00781 · 发布日期：2026-09-30）
DITTO-X: Forward and Reverse Teleoperation for Dexterous Manipulation and Human Intervention
DITTO-X通过力与接触反馈及反向遥操作，改进灵巧手示教和部署干预，并在接触丰富操作任务中验证。
核心要点
- 现有遥操作多依赖视觉并围绕平行夹爪设计，限制机器人执行能力和操作者表达。
- DITTO-X是手型无关的灵巧遥操作接口，利用机器人手已有传感呈现关节力和指尖接触事件。
- 该系统可驱动Sharpa、Wuji和Inspire三种商用灵巧手，无需针对每只手重新设计。
- 结果显示，相比商用手部追踪手套，DITTO-X提升了示教质量和吞吐量，并改善策略部署中的人类干预。
验证范围与局限：验证范围为接触丰富操作任务中的常规数据采集和策略部署时人类干预，使用三种商用灵巧手。
英文摘要 (Abstract)
Teleoperated demonstrations are a primary source of data for robot manipulation, and teleoperated interventions are a primary mechanism for correcting policies at deployment. Yet most teleoperation systems close the loop through vision alone and are built around parallel-jaw grippers, limiting both what the robot can execute and what the operator can express through it. This is most damaging in shared autonomy, where the operator sees the scene only through occluded cameras and must take over a dexterous hand mid-task, often with an object already grasped. We present DITTO-X, a hand-agnostic dexterous teleoperation interface that renders joint-level force and fingertip contact events from sensing already on the robot hand, and drives three commercial dexterous hands (Sharpa, Wuji, and Inspire) without per-hand redesign. Because the exoskeleton is actuated, DITTO-X also supports reverse teleoperation, in which the robot back-drives the operator's fingers into its own configuration before control is transferred, so the human enters the loop already matched to the state they inherit. Our results show that DITTO-X improves demonstration quality and throughput over a commercial hand-tracking glove, both in regular data collection and in human intervention during policy deployment for contact-rich manipulation tasks. More information can be found from our website: https://tml.stanford.edu/ditto-x/.
作者：Zhanpeng He, Joaquin Palacios, Zhangyu Wang, Chenhao Li, Katelyn Lee, Matei Ciocarlie, C. Karen Liu, Jiajun Wu
来源
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