Experimental Evaluation of Radio-aware Semantic Map with 5G-Enabled Mobile Robots
Adrian Lendinez Ibanez, Lanfranco Zanzi, Xi Li, Sandra Moreno, Guillem Garí, Christina C. Lessi, Vladimir Guroma, Renxi Qiu
Abstract
With the rapid development of 5G technology and the increasing demand for autonomous mobile robots, there is a trend to leverage the ultra-low latency, high data rates, and reliable wireless connectivity offered by 5G to improve the perception and navigation of robots in unknown environments. This paper presents a novel approach for creating and exploiting radio-aware semantic maps to empower 5G-enabled mobile robots operating within an unknown environment. The proposed solution allows for smart offloading of robotic applications and task processing onto the edge systems while facilitating real-time data exchange, and enables robots to gather environment data from both onboard sensors and the mobile network for more efficient robot operation and resource orchestration decisions. A radio-aware semantic mapping framework is introduced, which combines radio signal quality information with semantic mapping techniques to create a comprehensive understanding of the environment, which may evolve over time. The semantic map, enriched with radio quality measurement data, enables mobile robots to make timely informed decisions by considering real-time radio quality variations. Our experimental evaluation demonstrates the effectiveness of adopting radio semantic maps to enhance real-time robot operations on navigation and task offloading in unstructured environments.
BibTeX
@inproceedings{iros2025_experimentaleval,
title = {Experimental Evaluation of Radio-aware Semantic Map with 5G-Enabled Mobile Robots},
author = {Adrian Lendinez Ibanez and Lanfranco Zanzi and Xi Li and Sandra Moreno and Guillem Garí and Christina C. Lessi and Vladimir Guroma and Renxi Qiu and Xavier Costa-Pérez},
booktitle = {IROS 2025},
year = {2025}
}