触觉反馈阵列手套：用于灵巧操作的触觉反馈手套
Feel Robot Feels: Tactile Feedback Array Glove for Dexterous Manipulation
AI总结：
本文提出TAG手套，通过高精度手部运动捕捉与高分辨率触觉反馈，实现灵巧操作的触觉闭环远程操控，提升接触几何和动态力的实时感知能力。
摘要：
远程操控是收集高质量、物理一致的机器人操作演示的关键方法。然而，灵巧操作的远程操控仍受限于：(i) 不准确的手-机器人运动映射，限制了远程操控的灵活性；(ii) 有限的触觉反馈，迫使视觉主导的交互并阻碍接触几何和力变化的感知。为了解决这些挑战，我们提出了TAG，一种低成本的手套系统，集成了精确的手部运动捕捉与高分辨率触觉反馈，实现了有效的触觉闭环灵巧远程操控。对于运动捕捉，TAG采用非接触式磁感应设计，提供无漂移、电磁鲁棒的21自由度关节跟踪，关节角度估计误差低于1度。同时，为恢复触觉感知，TAG在每个手指上配备了一个32个执行器的触觉阵列，位于紧凑的2厘米平方模块内，允许操作者通过空间激活模式直接感知机器人末端执行器的物理交互。通过现实世界的远程操控实验和用户研究，我们证明TAG能够可靠地实时感知接触几何和动态力，提高接触丰富远程操控任务的成功率，并增加基于学习的操控演示数据收集的可靠性。
英文摘要：
Teleoperation is a key approach for collecting high-quality, physically consistent demonstrations for robotic manipulation. However, teleoperation for dexterous manipulation remains constrained by: (i) inaccurate hand-robot motion mapping, which limits teleoperated dexterity, and (ii) limited tactile feedback that forces vision-dominated interaction and hinders perception of contact geometry and force variation. To address these challenges, we present TAG, a low-cost glove system that integrates precise hand motion capture with high-resolution tactile feedback, enabling effective tactile-in-the-loop dexterous teleoperation. For motion capture, TAG employs a non-contact magnetic sensing design that provides drift-free, electromagnetically robust 21-DoF joint tracking with joint angle estimation errors below 1 degree. Meanwhile, to restore tactile sensation, TAG equips each finger with a 32-actuator tactile array within a compact 2 cm^2 module, allowing operators to directly feel physical interactions at the robot end-effector through spatial activation patterns. Through real-world teleoperation experiments and user studies, we show that TAG enables reliable real-time perception of contact geometry and dynamic force, improves success rates in contact-rich teleoperation tasks, and increases the reliability of demonstration data collection for learning-based manipulation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
