XRoboToolKit-T：基于触觉感知的高稳定性和高精度遥操作，用于接触丰富的操作

中文摘要 AI 辅助

为接触丰富的操作任务收集高质量的机器人数据，对于使机器人获得现实世界技能至关重要。然而，现有的数据收集解决方案往往缺乏获取稳定且高频触觉反馈的能力，这限制了它们在接触丰富操作场景中的有效性。在这项工作中，我们提出了一种具有触觉驱动辅助的多功能遥操作系统，以实现高频且稳定的接触丰富操作。所提出的XRoboToolKit-T遥操作系统整合了一种触觉感知的力控制架构，旨在确保遥操作过程中接触丰富操作中稳定且精确的力控制。稳定器触觉模块快速分析法向力分布并推断伪剪切力，从而在操作过程中实现基于触觉的实时辅助。精炼器触觉模块集成了视觉-语言-动作模型，基于触觉传感数据和任务描述来预测和精炼操作动作。我们将所提出的遥操作系统应用于具有挑战性的接触丰富操作任务，包括抓取可变形的橡胶移液管进行液体转移，以及将医用注射器插入血管训练垫，以展示触觉感知力控制的有效性。此外，与最先进的无需触觉辅助的遥操作相比，该系统实现了更高的数据收集效率和更好的操作稳定性。

英文摘要

Collecting high-quality robot data for contact-rich manipulation tasks is essential for enabling robots to acquire real-world skills. However, existing data collection solutions often lack the capability to obtain stable and high-frequency tactile feedback, limiting their effectiveness in contact-rich manipulation scenarios. In this work, we propose a versatile teleoperation system with tactile-driven assistance to enable high-frequency and stable contact-rich manipulation. The proposed XRoboToolKit-T teleoperation system incorporates a tactile-informed force control architecture, designed to ensure both stable and precise force control in contact-rich manipulation during teleoperation. The stabilizer haptic module rapidly analyzes the normal force distribution and infers pseudo shear force, enabling real-time tactile-based assistance during manipulation. The refiner haptic module integrates a vision-language-action model to predict and refine manipulation actions based on tactile sensing data and task descriptions. We apply the proposed teleoperation system to challenging contact-rich manipulation tasks, including grasping a deformable rubber pipette for liquid transfer and inserting a medical syringe into a vascular training pad, to demonstrate the effectiveness of tactile-informed force control. Furthermore, the system achieves higher data collection efficiency and improved manipulation stability compared to state-of-the-art teleoperation without tactile assistance.

发表机构

• Rochester Institute of Technology（罗切斯特理工学院）
• TikTok Pico Lab（TikTok Pico 实验室）
• The Hong Kong University of Science and Technology, Guangzhou（香港科技大学（广州））

机构由 AI 辅助整理，请以论文原文为准。