Publications
Copyright information: personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the publisher.
AI-Driven Ground Robots: Mobile Edge Computing and mmWave Communications at Work
Publication type | Journal paper |
---|---|
Year of publication | 2024 |
Authors | Giuseppe Baruffa, Andrea Detti, Luca Rugini, Francesco Crocetti, Paolo Banelli, Gabriele Costante, and Paolo Valigi |
Title | AI-Driven Ground Robots: Mobile Edge Computing and mmWave Communications at Work |
Journal title | IEEE Open Journal of the Communications Society |
Volume | 5 |
Issue | |
Pages | 3104–3119 |
Editor | |
Publisher | IEEE |
Date | May 2024 |
Place | |
ISSN number | 2644-125X |
ISBN number | |
Key words | Robots, Microservice architectures ,Task analysis , Cloud computing , Millimeter wave communication , 5G mobile communication , Image edge detection |
Abstract | The seamless integration of multiple radio access technologies (multi-RAT) and cloud/edge resources is pivotal for advancing future networks, which seek to unify distributed and heterogeneous computing and communication resources into a cohesive continuum system, tailored for mobile applications. Many research projects and focused studies are proposing solutions in this area, the impact of which is undoubtedly increased by moving from theoretical and simulation studies to experimental validations. To this aim, this paper proposes a testbed architecture that combines contemporary communication and cloud technologies to provide microservice-based mobile applications with the ability to offload part of their tasks to cloud/edge data centers connected by multi-RAT cellular networks. The testbed leverages Kubernetes, Istio service mesh, OpenFlow, public 5G networks, and IEEE 802.11ad mmWave (60 GHz) Wi-Fi access points. The architecture is validated through a use case in which a ground robot autonomously follows a moving object by using an artificial intelligence-driven computer vision application. Computationally intensive navigation tasks are offloaded by the robot to microservice instances, which are executed on demand within cloud and edge data centers that the robot can exploit during its journey. The proposed testbed is flexible and can be reused to assess communication and cloud innovations focusing on multi-RAT cloud continuum scenarios. |
URL | https://ieeexplore.ieee.org/document/10527382 |
DOI | http://dx.doi.org/10.1109/OJCOMS.2024.3399015 |
Other information | |
Paper | (portable document format, 5253800 Bytes) |