A VR teleoperation framework integrates GPU-accelerated inverse kinematics and trajectory optimization to generate collision-aware joint commands for a 7-DoF manipulator in real time across obstacle-free, static, and moving-obstacle scenarios.
BEAVR: Bimanual, multi-Embodiment, Accessible, Virtual Reality Teleoperation System for Robots
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abstract
\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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cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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A study on a Real-Time VR-Based Teleoperation Framework for Manipulator in Dynamic Environment
A VR teleoperation framework integrates GPU-accelerated inverse kinematics and trajectory optimization to generate collision-aware joint commands for a 7-DoF manipulator in real time across obstacle-free, static, and moving-obstacle scenarios.