遥操作
模块化设计
机器人
计算机科学
人工智能
移动机器人
遥控机器人学
立体视
计算机视觉
弹道
控制工程
机器人学
工程类
运动(物理)
质量(理念)
机器人控制
模拟
接口(物质)
人机交互
可视化
跟踪(教育)
系统体系结构
建筑
机器人运动学
作者
Zhigen Zhao,Liuchuan Yu,Ke Jing,Ning Yang
标识
DOI:10.1109/sii64115.2026.11404528
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 XRoboToolkit4, 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI