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XBot2D: towards a robotics hybrid cloud architecture for field robotics
Nowadays, robotics applications requiring the execution of complex tasks in real-world scenarios are still facing many challenges related to highly unstructured and dynamic environments in domains such as emergency response and search and rescue where robots have to operate for prolonged periods tra...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582978/ https://www.ncbi.nlm.nih.gov/pubmed/37860633 http://dx.doi.org/10.3389/frobt.2023.1168694 |
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author | Muratore, Luca Tsagarakis, Nikos |
author_facet | Muratore, Luca Tsagarakis, Nikos |
author_sort | Muratore, Luca |
collection | PubMed |
description | Nowadays, robotics applications requiring the execution of complex tasks in real-world scenarios are still facing many challenges related to highly unstructured and dynamic environments in domains such as emergency response and search and rescue where robots have to operate for prolonged periods trading off computational performance with increased power autonomy and vice versa. In particular, there is a crucial need for robots capable of adapting to such settings while at the same time providing robustness and extended power autonomy. A possible approach to overcome the conflicting demand of a computational performing system with the need for long power autonomy is represented by cloud robotics, which can boost the computational capabilities of the robot while reducing the energy consumption by exploiting the offload of resources to the cloud. Nevertheless, the communication constraint due to limited bandwidth, latency, and connectivity, typical of field robotics, makes cloud-enabled robotics solutions challenging to deploy in real-world applications. In this context, we designed and realized the XBot2D software architecture, which provides a hybrid cloud manager capable of dynamically and seamlessly allocating robotics skills to perform a distributed computation based on the current network condition and the required latency, and computational/energy resources of the robot in use. The proposed framework leverage on the two dimensions, i.e., 2D (local and cloud), in a transparent way for the user, providing support for Real-Time (RT) skills execution on the local robot, as well as machine learning and A.I. resources on the cloud with the possibility to automatically relocate the above based on the required performances and communication quality. XBot2D implementation and its functionalities are presented and validated in realistic tasks involving the CENTAURO robot and the Amazon Web Service Elastic Computing Cloud (AWS EC2) infrastructure with different network conditions. |
format | Online Article Text |
id | pubmed-10582978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105829782023-10-19 XBot2D: towards a robotics hybrid cloud architecture for field robotics Muratore, Luca Tsagarakis, Nikos Front Robot AI Robotics and AI Nowadays, robotics applications requiring the execution of complex tasks in real-world scenarios are still facing many challenges related to highly unstructured and dynamic environments in domains such as emergency response and search and rescue where robots have to operate for prolonged periods trading off computational performance with increased power autonomy and vice versa. In particular, there is a crucial need for robots capable of adapting to such settings while at the same time providing robustness and extended power autonomy. A possible approach to overcome the conflicting demand of a computational performing system with the need for long power autonomy is represented by cloud robotics, which can boost the computational capabilities of the robot while reducing the energy consumption by exploiting the offload of resources to the cloud. Nevertheless, the communication constraint due to limited bandwidth, latency, and connectivity, typical of field robotics, makes cloud-enabled robotics solutions challenging to deploy in real-world applications. In this context, we designed and realized the XBot2D software architecture, which provides a hybrid cloud manager capable of dynamically and seamlessly allocating robotics skills to perform a distributed computation based on the current network condition and the required latency, and computational/energy resources of the robot in use. The proposed framework leverage on the two dimensions, i.e., 2D (local and cloud), in a transparent way for the user, providing support for Real-Time (RT) skills execution on the local robot, as well as machine learning and A.I. resources on the cloud with the possibility to automatically relocate the above based on the required performances and communication quality. XBot2D implementation and its functionalities are presented and validated in realistic tasks involving the CENTAURO robot and the Amazon Web Service Elastic Computing Cloud (AWS EC2) infrastructure with different network conditions. Frontiers Media S.A. 2023-10-04 /pmc/articles/PMC10582978/ /pubmed/37860633 http://dx.doi.org/10.3389/frobt.2023.1168694 Text en Copyright © 2023 Muratore and Tsagarakis. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Robotics and AI Muratore, Luca Tsagarakis, Nikos XBot2D: towards a robotics hybrid cloud architecture for field robotics |
title | XBot2D: towards a robotics hybrid cloud architecture for field robotics |
title_full | XBot2D: towards a robotics hybrid cloud architecture for field robotics |
title_fullStr | XBot2D: towards a robotics hybrid cloud architecture for field robotics |
title_full_unstemmed | XBot2D: towards a robotics hybrid cloud architecture for field robotics |
title_short | XBot2D: towards a robotics hybrid cloud architecture for field robotics |
title_sort | xbot2d: towards a robotics hybrid cloud architecture for field robotics |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582978/ https://www.ncbi.nlm.nih.gov/pubmed/37860633 http://dx.doi.org/10.3389/frobt.2023.1168694 |
work_keys_str_mv | AT muratoreluca xbot2dtowardsaroboticshybridcloudarchitectureforfieldrobotics AT tsagarakisnikos xbot2dtowardsaroboticshybridcloudarchitectureforfieldrobotics |