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Adaptive assistive robotics: a framework for triadic collaboration between humans and robots
Robots and other assistive technologies have a huge potential to help society in domains ranging from factory work to healthcare. However, safe and effective control of robotic agents in these environments is complex, especially when it involves close interactions and multiple actors. We propose an...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300679/ https://www.ncbi.nlm.nih.gov/pubmed/37388317 http://dx.doi.org/10.1098/rsos.221617 |
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author | Gordon, Daniel F. N. Christou, Andreas Stouraitis, Theodoros Gienger, Michael Vijayakumar, Sethu |
author_facet | Gordon, Daniel F. N. Christou, Andreas Stouraitis, Theodoros Gienger, Michael Vijayakumar, Sethu |
author_sort | Gordon, Daniel F. N. |
collection | PubMed |
description | Robots and other assistive technologies have a huge potential to help society in domains ranging from factory work to healthcare. However, safe and effective control of robotic agents in these environments is complex, especially when it involves close interactions and multiple actors. We propose an effective framework for optimizing the behaviour of robots and complementary assistive technologies in systems comprising a mix of human and technological agents with numerous high-level goals. The framework uses a combination of detailed biomechanical modelling and weighted multi-objective optimization to allow for the fine tuning of robot behaviours depending on the specification of the task at hand. We illustrate our framework via two case studies across assisted living and rehabilitation scenarios, and conduct simulations and experiments of triadic collaboration in practice. Our results indicate a marked benefit to the triadic approach, showing the potential to improve outcome measures for human agents in robot-assisted tasks. |
format | Online Article Text |
id | pubmed-10300679 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-103006792023-06-29 Adaptive assistive robotics: a framework for triadic collaboration between humans and robots Gordon, Daniel F. N. Christou, Andreas Stouraitis, Theodoros Gienger, Michael Vijayakumar, Sethu R Soc Open Sci Computer Science and Artificial Intelligence Robots and other assistive technologies have a huge potential to help society in domains ranging from factory work to healthcare. However, safe and effective control of robotic agents in these environments is complex, especially when it involves close interactions and multiple actors. We propose an effective framework for optimizing the behaviour of robots and complementary assistive technologies in systems comprising a mix of human and technological agents with numerous high-level goals. The framework uses a combination of detailed biomechanical modelling and weighted multi-objective optimization to allow for the fine tuning of robot behaviours depending on the specification of the task at hand. We illustrate our framework via two case studies across assisted living and rehabilitation scenarios, and conduct simulations and experiments of triadic collaboration in practice. Our results indicate a marked benefit to the triadic approach, showing the potential to improve outcome measures for human agents in robot-assisted tasks. The Royal Society 2023-06-28 /pmc/articles/PMC10300679/ /pubmed/37388317 http://dx.doi.org/10.1098/rsos.221617 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Computer Science and Artificial Intelligence Gordon, Daniel F. N. Christou, Andreas Stouraitis, Theodoros Gienger, Michael Vijayakumar, Sethu Adaptive assistive robotics: a framework for triadic collaboration between humans and robots |
title | Adaptive assistive robotics: a framework for triadic collaboration between humans and robots |
title_full | Adaptive assistive robotics: a framework for triadic collaboration between humans and robots |
title_fullStr | Adaptive assistive robotics: a framework for triadic collaboration between humans and robots |
title_full_unstemmed | Adaptive assistive robotics: a framework for triadic collaboration between humans and robots |
title_short | Adaptive assistive robotics: a framework for triadic collaboration between humans and robots |
title_sort | adaptive assistive robotics: a framework for triadic collaboration between humans and robots |
topic | Computer Science and Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300679/ https://www.ncbi.nlm.nih.gov/pubmed/37388317 http://dx.doi.org/10.1098/rsos.221617 |
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