用于5G连接无人自动驾驶车辆的CSI辅助边缘SLAM测试平台
CSI-Assisted Edge SLAM Testbed Platform for 5G Connected Unmanned Autonomous Vehicles
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中文总结 AI 辅助
本文针对5G连接无人自动驾驶车辆，设计实现CSI辅助边缘SLAM测试平台，集成UGV、ROS2框架及5G O-RAN系统，提供端到端跨层视角，分析相关通信传输并讨论CSI机制，揭示关键挑战，为6G机器人平台提供见解。
中文摘要 AI 辅助
从5G到6G的演进增强了对连接机器人技术的兴趣，移动机器人通过超可靠低延迟通信（URLLC）链路将计算密集型任务卸载到边缘服务器。同时定位与地图构建（SLAM）作为一项基础且高要求的机器人功能，越来越多地被考虑在移动边缘计算（MEC）框架内进行边缘部署。同时，集成传感与通信（ISAC）使诸如信道状态信息（CSI）等无线信道信息能作为基于无线电的SLAM中的一种额外传感方式。本文设计并实现了一个CSI辅助边缘SLAM测试平台，它集成了定制无人地面车辆（UGV）、基于ROS2的SLAM框架和5G开放式无线接入网（O-RAN）系统。所提出的架构提供了一个端到端、跨层的视角，用于ROS2传感器数据在5G上的流式传输，明确地实现了CSI的暴露并集成到SLAM管道中。我们分析了ROS2 DDS通信、RTPS分组化和5G用户平面传输，并讨论了通过O-RAN组件进行CSI提取和传递的机制。该平台实现了具有通信感知SLAM的实际实验，并揭示了与延迟、数据流、同步和跨系统集成相关的关键挑战，为未来支持6G的机器人平台提供了见解。
英文摘要
The evolution from 5G towards 6G reinforces interest in connected robotics, where mobile robots offload compute-intensive tasks to edge servers over ultra-reliable low-latency communication (URLLC) links. Simultaneous localization and mapping (SLAM), a fundamental yet demanding robotics function, is increasingly considered for edge deployment within mobile edge computing (MEC) frameworks. In parallel, integrated sensing and communications (ISAC) enables the use of radio channel information, such as channel state information (CSI), as an additional sensing modality in radio-based SLAM. In this paper, we design and implement a CSI-assisted Edge SLAM testbed integrating a custom unmanned ground vehicle (UGV), a ROS2-based SLAM framework, and a 5G Open Radio Access Network (O-RAN) system. The proposed architecture provides an end-to-end, cross-layer view of ROS2 sensor data streaming over 5G, explicitly enabling CSI exposure and integration into the SLAM pipeline. We analyze ROS2 DDS communication, RTPS packetization, and 5G user-plane transport, and discuss mechanisms for CSI extraction and delivery via O-RAN components. The platform enables realistic experimentation with communication-aware SLAM and reveals key challenges related to latency, data streaming, synchronization, and cross-system integration, providing insights for future 6G-enabled robotic platforms.
发表机构
- Faculty of Technical Sciences, University of Novi Sad, Serbia（技术科学学院，诺维萨德大学，塞尔维亚）
机构由 AI 辅助整理，请以论文原文为准。
