Enhancing 5G-enabled robots autonomy by radio-aware semantic maps
Authors
Lendinez, AdriánZanzi, Lanfranco
Moreno, Sandra
Gari, Guillem
Li, Xi
Qiu, Renxi
Costa-Perez, Xavier
Affiliation
University of BedfordshireNEC Laboratories Europe
Robotnik Automation SL
Catalan Institution for Research and Advanced Studies
Issue Date
2023-12-13Subjects
wireless communications5G mobile communication
semantics
surfaces
reliability
mobile robots
task analysis
Metadata
Show full item recordAbstract
Future robotics systems aiming for true autonomy must be robust against dynamic and unstructured environments. The 5th generation (5G) mobile network is expected to provide ubiquitous, reliable and low-latency wireless communications to ground robots, especially in outdoor scenarios. Empowered by 5G, the digital transformation of robotics is emerging, enabled by the cloud-native paradigm and the adoption of edge-computing principles for heavy computational task offloading. However, wireless link quality fluctuates due to multiple aspects such as the topography of the deployment area, the presence of obstacles, robots' movement and the configuration of the serving base stations. This directly impacts not only the connectivity to the robots but also the performance of robot operations, resulting in severe challenges when targeting full robot autonomy. To address such challenges, in this paper, we propose a framework to build a semantic map based on radio quality. By means of our proposed approach, mobile robots can gain knowledge on up-to-date radio context map information of the surrounding environment, hence enabling reliable and efficient robotics operations.Citation
Lendinez A, Zanzi L, Moreno S, Gari G, Li X, Qiu R, Costa-Perez X (2023) 'Enhancing 5G-enabled robots autonomy by radio-aware semantic maps', 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) - Detroit, Institute of Electrical and Electronics Engineers Inc..Additional Links
https://ieeexplore.ieee.org/document/10342279/Type
Conference papers, meetings and proceedingsLanguage
enISBN
9781665491907Sponsors
The research leading to these results has been supported by the EU's H2020 5G ERA Project (grant no. 101016681).ae974a485f413a2113503eed53cd6c53
10.1109/IROS55552.2023.10342279