CSI Assisted Edge SLAM Testbed Platform for 5G Connected Unmanned Autonomous Vehicles

Jul 16, 2026

The evolution from 5G to 6G drives connected robotics, where mobile robots offload compute-intensive workloads to edge servers using URLLC links. The document presents a CSI-assisted Edge SLAM testbed that integrates a custom UGV, a ROS2-based SLAM stack, and a 5G O-RAN system. It offers an end-to-end cross-layer architecture for streaming ROS2 sensor data over 5G while exposing CSI to the SLAM pipeline, and analyzes ROS2–DDS, RTPS packetization, and 5G user-plane transport. Key findings address latency, streaming, synchronization, and cross-system integration challenges.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages6

Reading Time15 min

Introduction

Motivation and background

Edge SLAM and communication challenges

ISAC and CSI-assisted localization

Paper contributions and testbed design

CSI-Assisted Edge SLAM Testbed Platform for 5G Connected Unmanned Autonomous Vehicles Boris Radovanovic∗ , Sasa Talosi∗ , Srdjan Sobot∗ , Dejan Vukobratovic∗ ∗Faculty of Technical Sciences, University of Novi Sad, Serbia arXiv :2607 . 10394v 1 [ cs .NI] 11 Jul 2026 Abstract—The evolution from 5G towards 6G reinforces interest in connected robotics, where mobile robots offload computeintensive 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-toend, 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 communicationaware SLAM and reveals key challenges related to latency, data streaming, synchronization, and cross-system integration, providing insights for future 6G-enabled robotic platforms. Index Terms—5G/6G, SLAM, O-RAN, Channel State Information, Connected Robotics, Testbeds I. INTRODUCTION Connected robotics is one of the primary use cases for ultra-reliable and low-latency communication (URLLC) in 5G networks [1], and it continues to be a key driver in the evolution towards hyper-reliable low-latency communications (HRLLC) in 6G [2] . Recent studies have explored use case requirements, system architectures, and standardization efforts for 6G-enabled robotic systems [3]–[6] . While early work has often focused on tightly controlled environments or teleoperation-centric applications such as remote surgery [7], increasing attention is being directed towards mobile autonomous robots operating in dynamic and unstructured environments. In such settings, robots must continuously perceive, localize, and map their surroundings while meeting stringent latency and reliability constraints, motivating the offloading of compute-intensive perception and decision-making tasks to edge infrastructure over 5G/6G networks [3], [4] . Simultaneous localization and mapping (SLAM) represents a core building block of autonomous mobile robotics, enabling This research has been supported by the Ministry of Science, Technological Development and Innovation (Contract No. 451-03-34/2026-03/200156) and the Faculty of Technical Sciences, University of Novi Sad through project“Scientific and Artistic Research Work of Researchers in Teaching and Associate Positions at the Faculty of Technical Sciences, University of Novi Sad 2026”(No. 01-3609/1) . robots to estimate their pose while constructing a map of the environment from onboard sensor data. Modern SLAM pipelines, particularly those relying on high-rate visual or multi-modal sensing, impose significant computational and communication demands that can exceed the capabilities of resource-constrained robotic platforms. This has motivated the concept of Edge SLAM, where sensor data acquired on the robot is streamed over a 5G network to edge servers executing SLAM algorithms within a mobile edge computing (MEC) framework. While this paradigm offers the potential for enhanced performance and reduced onboard complexity, it introduces new challenges related to real-time data streaming, latency constraints, synchronization, and cross-layer interaction bet

FAQs

What problem does the CSI-assisted Edge SLAM testbed target?

It targets end-to-end integration challenges when deploying SLAM on edge infrastructure over 5G, especially the practical use of CSI as an additional sensing modality for localization and mapping.

How is CSI delivered to the SLAM pipeline in the proposed architecture?

CSI exposure is enabled through O-RAN components, using practical methods such as direct extraction at the O-DU with forwarding via a ZMQ–ROS2 bridge, plus RIC-assisted processing and controlled dissemination through xApps.

Which system layers and interfaces are analyzed to understand performance?

The document analyzes ROS2–DDS communication, RTPS packetization, and 5G user-plane transport, focusing on how these affect latency, reliability, and synchronization during real-time sensor data streaming.

Jul 16, 2026

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