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Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments
Population aging and pandemics have been shown to cause the isolation of elderly people in their houses, generating the need for a reliable assistive figure. Robotic assistants are the new frontier of innovation for domestic welfare, and elderly monitoring is one of the services a robot can handle f...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322347/ https://www.ncbi.nlm.nih.gov/pubmed/35890940 http://dx.doi.org/10.3390/s22145261 |
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author | Eirale, Andrea Martini, Mauro Tagliavini, Luigi Gandini, Dario Chiaberge, Marcello Quaglia, Giuseppe |
author_facet | Eirale, Andrea Martini, Mauro Tagliavini, Luigi Gandini, Dario Chiaberge, Marcello Quaglia, Giuseppe |
author_sort | Eirale, Andrea |
collection | PubMed |
description | Population aging and pandemics have been shown to cause the isolation of elderly people in their houses, generating the need for a reliable assistive figure. Robotic assistants are the new frontier of innovation for domestic welfare, and elderly monitoring is one of the services a robot can handle for collective well-being. Despite these emerging needs, in the actual landscape of robotic assistants, there are no platforms that successfully combine reliable mobility in cluttered domestic spaces with lightweight and offline Artificial Intelligence (AI) solutions for perception and interaction. In this work, we present Marvin, a novel assistive robotic platform we developed with a modular layer-based architecture, merging a flexible mechanical design with cutting-edge AI for perception and vocal control. We focus the design of Marvin on three target service functions: monitoring of elderly and reduced-mobility subjects, remote presence and connectivity, and night assistance. Compared to previous works, we propose a tiny omnidirectional platform, which enables agile mobility and effective obstacle avoidance. Moreover, we design a controllable positioning device, which easily allows the user to access the interface for connectivity and extends the visual range of the camera sensor. Nonetheless, we delicately consider the privacy issues arising from private data collection on cloud services, a critical aspect of commercial AI-based assistants. To this end, we demonstrate how lightweight deep learning solutions for visual perception and vocal command can be adopted, completely running offline on the embedded hardware of the robot. |
format | Online Article Text |
id | pubmed-9322347 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93223472022-07-27 Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments Eirale, Andrea Martini, Mauro Tagliavini, Luigi Gandini, Dario Chiaberge, Marcello Quaglia, Giuseppe Sensors (Basel) Article Population aging and pandemics have been shown to cause the isolation of elderly people in their houses, generating the need for a reliable assistive figure. Robotic assistants are the new frontier of innovation for domestic welfare, and elderly monitoring is one of the services a robot can handle for collective well-being. Despite these emerging needs, in the actual landscape of robotic assistants, there are no platforms that successfully combine reliable mobility in cluttered domestic spaces with lightweight and offline Artificial Intelligence (AI) solutions for perception and interaction. In this work, we present Marvin, a novel assistive robotic platform we developed with a modular layer-based architecture, merging a flexible mechanical design with cutting-edge AI for perception and vocal control. We focus the design of Marvin on three target service functions: monitoring of elderly and reduced-mobility subjects, remote presence and connectivity, and night assistance. Compared to previous works, we propose a tiny omnidirectional platform, which enables agile mobility and effective obstacle avoidance. Moreover, we design a controllable positioning device, which easily allows the user to access the interface for connectivity and extends the visual range of the camera sensor. Nonetheless, we delicately consider the privacy issues arising from private data collection on cloud services, a critical aspect of commercial AI-based assistants. To this end, we demonstrate how lightweight deep learning solutions for visual perception and vocal command can be adopted, completely running offline on the embedded hardware of the robot. MDPI 2022-07-14 /pmc/articles/PMC9322347/ /pubmed/35890940 http://dx.doi.org/10.3390/s22145261 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Eirale, Andrea Martini, Mauro Tagliavini, Luigi Gandini, Dario Chiaberge, Marcello Quaglia, Giuseppe Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments |
title | Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments |
title_full | Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments |
title_fullStr | Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments |
title_full_unstemmed | Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments |
title_short | Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments |
title_sort | marvin: an innovative omni-directional robotic assistant for domestic environments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322347/ https://www.ncbi.nlm.nih.gov/pubmed/35890940 http://dx.doi.org/10.3390/s22145261 |
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