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Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics
Repetitive industrial tasks can be easily performed by traditional robotic systems. However, many other works require cognitive knowledge that only humans can provide. Human-Robot Collaboration (HRC) emerges as an ideal concept of co-working between a human operator and a robot, representing one of...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232712/ https://www.ncbi.nlm.nih.gov/pubmed/34203766 http://dx.doi.org/10.3390/s21124113 |
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author | Castro, Afonso Silva, Filipe Santos, Vitor |
author_facet | Castro, Afonso Silva, Filipe Santos, Vitor |
author_sort | Castro, Afonso |
collection | PubMed |
description | Repetitive industrial tasks can be easily performed by traditional robotic systems. However, many other works require cognitive knowledge that only humans can provide. Human-Robot Collaboration (HRC) emerges as an ideal concept of co-working between a human operator and a robot, representing one of the most significant subjects for human-life improvement.The ultimate goal is to achieve physical interaction, where handing over an object plays a crucial role for an effective task accomplishment. Considerable research work had been developed in this particular field in recent years, where several solutions were already proposed. Nonetheless, some particular issues regarding Human-Robot Collaboration still hold an open path to truly important research improvements. This paper provides a literature overview, defining the HRC concept, enumerating the distinct human-robot communication channels, and discussing the physical interaction that this collaboration entails. Moreover, future challenges for a natural and intuitive collaboration are exposed: the machine must behave like a human especially in the pre-grasping/grasping phases and the handover procedure should be fluent and bidirectional, for an articulated function development. These are the focus of the near future investigation aiming to shed light on the complex combination of predictive and reactive control mechanisms promoting coordination and understanding. Following recent progress in artificial intelligence, learning exploration stand as the key element to allow the generation of coordinated actions and their shaping by experience. |
format | Online Article Text |
id | pubmed-8232712 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82327122021-06-26 Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics Castro, Afonso Silva, Filipe Santos, Vitor Sensors (Basel) Article Repetitive industrial tasks can be easily performed by traditional robotic systems. However, many other works require cognitive knowledge that only humans can provide. Human-Robot Collaboration (HRC) emerges as an ideal concept of co-working between a human operator and a robot, representing one of the most significant subjects for human-life improvement.The ultimate goal is to achieve physical interaction, where handing over an object plays a crucial role for an effective task accomplishment. Considerable research work had been developed in this particular field in recent years, where several solutions were already proposed. Nonetheless, some particular issues regarding Human-Robot Collaboration still hold an open path to truly important research improvements. This paper provides a literature overview, defining the HRC concept, enumerating the distinct human-robot communication channels, and discussing the physical interaction that this collaboration entails. Moreover, future challenges for a natural and intuitive collaboration are exposed: the machine must behave like a human especially in the pre-grasping/grasping phases and the handover procedure should be fluent and bidirectional, for an articulated function development. These are the focus of the near future investigation aiming to shed light on the complex combination of predictive and reactive control mechanisms promoting coordination and understanding. Following recent progress in artificial intelligence, learning exploration stand as the key element to allow the generation of coordinated actions and their shaping by experience. MDPI 2021-06-15 /pmc/articles/PMC8232712/ /pubmed/34203766 http://dx.doi.org/10.3390/s21124113 Text en © 2021 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 Castro, Afonso Silva, Filipe Santos, Vitor Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics |
title | Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics |
title_full | Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics |
title_fullStr | Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics |
title_full_unstemmed | Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics |
title_short | Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics |
title_sort | trends of human-robot collaboration in industry contexts: handover, learning, and metrics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232712/ https://www.ncbi.nlm.nih.gov/pubmed/34203766 http://dx.doi.org/10.3390/s21124113 |
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