用普通VR设备实现多机器人实时灵巧操控，支持数据记录与学习。
BEAVR: Bimanual, multi-Embodiment, Accessible, Virtual Reality Teleoperation System for Robots
- 基于VR的双臂操控系统，兼容7自由度机械臂到全身人形机器人。
- 延迟低于35毫秒，支持多机器人同步操作与多模态数据记录。
- 开源且适配主流视觉运动策略，适合机器人研发与教学使用。
BEAVR 是一个开源的、双臂的、多具身的虚拟现实（VR）遥操作系统，旨在统一异构机器人平台上的实时控制、数据记录与策略学习。该系统利用消费级VR硬件实现低延迟（≤35毫秒）、高精度的灵巧遥操作，支持从7-DoF机械臂到全尺寸人形机器人的模块化集成，并可直接以LeRobot数据集格式同步记录多模态操作数据。系统采用零拷贝流式架构与异步‘思考-执行’控制循环，优化了实时多机器人协同性能。我们在多种抓取与操纵任务上对BEAVR进行了基准测试，验证了其与ACT、DiffusionPolicy和SmolVLA等先进视觉运动策略的兼容性。所有代码公开，数据集已发布于Hugging Face。
原文摘要 · Abstract (English)
\textbf{BEAVR} is an open-source, bimanual, multi-embodiment Virtual Reality (VR) teleoperation system for robots, designed to unify real-time control, data recording, and policy learning across heterogeneous robotic platforms. BEAVR enables real-time, dexterous teleoperation using commodity VR hardware, supports modular integration with robots ranging from 7-DoF manipulators to full-body humanoids, and records synchronized multi-modal demonstrations directly in the LeRobot dataset schema. Our system features a zero-copy streaming architecture achieving $\leq$35\,ms latency, an asynchronous ``think--act'' control loop for scalable inference, and a flexible network API optimized for real-time, multi-robot operation. We benchmark BEAVR across diverse manipulation tasks and demonstrate its compatibility with leading visuomotor policies such as ACT, DiffusionPolicy, and SmolVLA. All code is publicly available, and datasets are released on Hugging Face\footnote{Code, datasets, and VR app available at https://github.com/ARCLab-MIT/BEAVR-Bot.
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