标题： XRoboToolkit：用于机器人远程操作的跨平台框架 显示英文标题

标题： XRoboToolkit: A Cross-Platform Framework for Robot Teleoperation

摘要： 视觉-语言-动作模型的快速发展催生了对大规模、高质量机器人演示数据集的迫切需求。 尽管远程操作是数据收集的主要方法，但当前的方法在可扩展性、复杂的设置流程和次优的数据质量方面存在不足。 本文介绍了XRoboToolkit，这是一个基于扩展现实的机器人远程操作跨平台框架，构建于OpenXR标准之上。 该系统具有低延迟的立体视觉反馈、基于优化的逆运动学以及对多种跟踪模式的支持，包括头部、控制器、手部和辅助运动跟踪器。 XRoboToolkit的模块化架构实现了在不同机器人平台和仿真环境之间的无缝集成，涵盖精密操作机械臂、移动机器人和灵巧的手部。 我们通过精密操作任务展示了该框架的有效性，并通过训练表现出强大自主性能的VLA模型来验证数据质量。 显示英文摘要

摘要： The rapid advancement of Vision-Language-Action models has created an urgent need for large-scale, high-quality robot demonstration datasets. Although teleoperation is the predominant method for data collection, current approaches suffer from limited scalability, complex setup procedures, and suboptimal data quality. This paper presents XRoboToolkit, a cross-platform framework for extended reality based robot teleoperation built on the OpenXR standard. The system features low-latency stereoscopic visual feedback, optimization-based inverse kinematics, and support for diverse tracking modalities including head, controller, hand, and auxiliary motion trackers. XRoboToolkit's modular architecture enables seamless integration across robotic platforms and simulation environments, spanning precision manipulators, mobile robots, and dexterous hands. We demonstrate the framework's effectiveness through precision manipulation tasks and validate data quality by training VLA models that exhibit robust autonomous performance.