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Enhancing 5G-enabled robots autonomy by radio-aware semantic maps

  • Adrian Lendinez Ibanez
    ,
  • Lanfranco Zanzi
    ,
  • Sandra Moreno
    ,
  • Guillem Gari
    ,
  • Xi Li
    ,
  • Renxi Qiu
  • NEC Corporation
    ,
  • Robotnik Automation
    ,
  • i2CAT Foundation
    ,
  • ICREA
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

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.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 6267-6272 (6 pages)

Publication milestones

  • Published - 13/12/2023

Publication status

Published - 13/12/2023

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

Publication series

  • Publication series name: IEEE International Conference on Intelligent Robots and Systems
    ISSN (Print): 2153-0858
    ISSN (Electronic): 2153-0866

ISBN (Print)

9781665491907

ISBN (Electronic)

9781665491907

External Publication IDs

  • handle.net: 10547/626149
  • Scopus: 85182526124

Host publication title

2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023

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