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arXiv 2609.31396cs.RO

增强现实人机协作接口:基于ROS 2的传感器流框架开发及SLAM算法验证

Augmented Reality Interfaces for Human-Robot Collaboration: Development of a ROS 2-Based Sensor Streaming Framework and Validation via SLAM Algorithms

Alessandro Rubert, Stefano Ghidoni, Matteo Terreran

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中文总结 AI 辅助

本文开发了连接Magic Leap 2与ROS 2的传感器流框架,经SLAM算法验证,实现稳定数据传输,支持人机协作中的实时交互与空间感知。

中文摘要 AI 辅助

近年来,人机协作(HRC)在工业4.0和协作机器人领域占据了核心地位,对通信渠道提出了越来越双向、直观和高效的要求。在此背景下,增强现实(AR)作为一种基础性使能技术应运而生,既能向操作员显示信息,又能收集周围环境的空间数据。本论文介绍了一个传感器流框架的开发,该框架将Magic Leap 2 AR头显与ROS 2(机器人操作系统)生态系统相连接。利用Unity开发环境和ROSTCP-Connector软件包,开发了一款头显机载应用程序,能够从集成传感器(位姿跟踪、摄像头和环境传感器)获取实时数据,并将其发布到专用的ROS 2主题上。为了测试所生成数据流的准确性、延迟和鲁棒性,该框架使用文献中已知的SLAM(同步定位与地图构建)算法进行了验证。实验结果表明,所提出的架构确保了稳定的数据传输,为安全的实时交互和共享空间感知奠定了基础,并为复杂HRC场景中机器人系统的控制与监督开辟了新的前景。

英文摘要

In recent years, Human-Robot Collaboration (HRC) has taken on a central role in Industry 4.0 and collaborative robotics, demanding communication channels that are increasingly bidirectional, intuitive, and efficient. In this context, Augmented Reality (AR) presents itself as a fundamental enabling technology, capable of both displaying information to the operator and gathering spatial data about the surrounding environment. This thesis presents the development of a sensor streaming framework that connects the Magic Leap 2 AR headset with the ROS 2 (Robot Operating System) ecosystem. Using the Unity development environment and the ROSTCP-Connector package, an on-board application for the headset was developed, capable of acquiring real-time data from the integrated sensors (pose tracking, cameras, and environmental sensors) and publishing it to dedicated ROS 2 topics. In order to test the accuracy, latency, and robustness of the generated data stream, the framework was validated using SLAM (Simultaneous Localization and Mapping) algorithms known in the literature. The experimental results demonstrate that the proposed architecture ensures stable data transmission, laying the groundwork for safe real-time interaction and shared spatial awareness, and opening up new perspectives for the control and supervision of robotic systems in complex HRC scenarios.

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