LeVR让机器人用手操作更简单，一键收集专家示范数据。
LeVR: A Modular VR Teleoperation Framework for Imitation Learning in Dexterous Manipulation
- 用虚拟现实远程操控机械臂，直观高效采集操作数据。
- 构建100次专家示范数据集，成功微调顶尖视觉运动策略。
- 开源框架+真实机械臂，适合做灵巧操作研究的团队使用。
我们提出LeVR，一个模块化软件框架，旨在填补机器人模仿学习中的两个关键空白。首先，它提供稳健且直观的虚拟现实（VR）远程操控，用于搭配灵巧手的机械臂进行数据采集，解决了现有系统常见局限。其次，其原生集成强大的LeRobot模仿学习（IL）框架，可直接使用基于VR的示范数据，简化演示收集流程。为验证系统，我们发布LeFranX——Franka FER机械臂与RobotEra XHand的开源实现，支持从数据采集到真实世界策略部署的端到端工作流。通过收集100条专家示范数据，成功微调当前最先进的视觉运动策略。我们开源整个框架、实现及数据集，助力机器人模仿学习研究发展。
原文摘要 · Abstract (English)
We introduce LeVR, a modular software framework designed to bridge two critical gaps in robotic imitation learning. First, it provides robust and intuitive virtual reality (VR) teleoperation for data collection using robot arms paired with dexterous hands, addressing a common limitation in existing systems. Second, it natively integrates with the powerful LeRobot imitation learning (IL) framework, enabling the use of VR-based teleoperation data and streamlining the demonstration collection process. To demonstrate LeVR, we release LeFranX, an open-source implementation for the Franka FER arm and RobotEra XHand, two widely used research platforms. LeFranX delivers a seamless, end-to-end workflow from data collection to real-world policy deployment. We validate our system by collecting a public dataset of 100 expert demonstrations and use it to successfully fine-tune state-of-the-art visuomotor policies. We provide our open-source framework, implementation, and dataset to accelerate IL research for the robotics community.
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