发表机构
Stanford University; Columbia University（斯坦福大学; 哥伦比亚大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
DITTO-X是一种手无关的灵巧遥操作接口，通过关节力和指尖接触反馈及反向遥操作，提升演示质量和干预效率，驱动多款商用灵巧手。
AI 中文摘要
遥操作演示是机器人操作数据的主要来源，而遥操作干预是部署时纠正策略的主要机制。然而，大多数遥操作系统仅通过视觉闭环，并围绕平行夹爪构建，这限制了机器人能执行的任务以及操作者通过系统能表达的动作。这在共享自主中最为有害，操作者仅通过被遮挡的摄像头观察场景，必须在任务中途接管灵巧手，且往往手中已抓握物体。我们提出DITTO-X，一种与手无关的灵巧遥操作接口，它利用机器人手上已有的传感信息渲染关节级力和指尖接触事件，并驱动三款商用灵巧手（Sharpa、Wuji和Inspire），无需针对每只手重新设计。由于外骨骼是主动驱动的，DITTO-X还支持反向遥操作，即机器人在控制权转移前将操作者的手指反向驱动至自身构型，从而使人类进入回路时已与所继承的状态匹配。我们的结果表明，在常规数据收集和接触丰富操作任务的策略部署中的人工干预方面，DITTO-X相比商用手部追踪手套提高了演示质量和吞吐量。更多信息可在我们的网站找到：此https URL。
英文摘要
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/.
