发表机构
National Institute of Advanced Industrial Science and Technology (AIST)（独立行政法人产业技术综合研究所（AIST））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出TWINS触觉可穿戴同构臂联网系统，用于解决现有机器人难以完成身体表面接触操作的问题，通过采集演示数据训练模仿学习策略，实现了身体表面触觉引导的接触丰富操作。
AI 中文摘要
机器人操作学习的最新进展提升了真实世界演示数据采集的重要性。然而，现有机器人系统主要聚焦于末端执行器操作，难以教授和执行涉及手臂、胸部与身体表面接触的操作任务。本文提出TWINS（Tactile Wearable Isomorphic Arm Networked System），一款用于身体表面接触操作的机器人系统。TWINS由操作员穿戴的可穿戴双臂装置、具有相同关节配置和外部尺寸的同构机器人组成。嵌入胸部和手臂的分布式触觉传感器可同步测量身体表面接触与关节运动。利用可穿戴双臂装置，我们采集了4项涉及身体表面接触的操作任务演示数据，随后用采集到的演示数据训练模仿学习策略，并将其部署到同构机器人上，实现了由身体表面触觉观测引导的操作。实验结果表明，TWINS为涉及身体表面接触的操作提供了一套统一的机器人系统，支持演示、学习与执行全流程。
英文摘要
Recent advances in robot learning for manipulation have increased the importance of collecting real-world demonstration data. However, existing robotic systems primarily focus on end-effector manipulation, making it difficult to teach and execute manipulation tasks involving body-surface contact with the arms and chest. This paper presents TWINS (Tactile Wearable Isomorphic Arm Networked System), a robotic system for manipulation involving body-surface contact. TWINS consists of a Wearable Dual-Arm Device, which is worn by the operator, and an Isomorphic Robot with the same joint configuration and external dimensions. Distributed tactile sensors embedded in the chest and arms enable the measurement of body-surface contact synchronized with joint motion. Using the Wearable Dual-Arm Device, we collected demonstrations for four manipulation tasks involving body-surface contact. We then trained imitation learning policies using the collected demonstrations and deployed them on the Isomorphic Robot, enabling manipulation guided by body-surface tactile observations. Experimental results demonstrate that TWINS provides a unified robotic system for demonstration, learning, and execution of manipulation involving body-surface contact. https://mmurooka.github.io/twins-project-page/
