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Coordinating Shared Tasks in Human-Robot Collaboration by Commands

Human-robot collaboration is gaining more and more interest in industrial settings, as collaborative robots are considered safe and robot actions can be programmed easily by, for example, physical interaction. Despite this, robot programming mostly focuses on automated robot motions and interactive...

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Autores principales: Angleraud , Alexandre, Mehman Sefat, Amir, Netzev, Metodi, Pieters, Roel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8560701/
https://www.ncbi.nlm.nih.gov/pubmed/34738018
http://dx.doi.org/10.3389/frobt.2021.734548
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author Angleraud , Alexandre
Mehman Sefat, Amir
Netzev, Metodi
Pieters, Roel
author_facet Angleraud , Alexandre
Mehman Sefat, Amir
Netzev, Metodi
Pieters, Roel
author_sort Angleraud , Alexandre
collection PubMed
description Human-robot collaboration is gaining more and more interest in industrial settings, as collaborative robots are considered safe and robot actions can be programmed easily by, for example, physical interaction. Despite this, robot programming mostly focuses on automated robot motions and interactive tasks or coordination between human and robot still requires additional developments. For example, the selection of which tasks or actions a robot should do next might not be known beforehand or might change at the last moment. Within a human-robot collaborative setting, the coordination of complex shared tasks, is therefore more suited to a human, where a robot would act upon requested commands.In this work we explore the utilization of commands to coordinate a shared task between a human and a robot, in a shared work space. Based on a known set of higher-level actions (e.g., pick-and-placement, hand-over, kitting) and the commands that trigger them, both a speech-based and graphical command-based interface are developed to investigate its use. While speech-based interaction might be more intuitive for coordination, in industrial settings background sounds and noise might hinder its capabilities. The graphical command-based interface circumvents this, while still demonstrating the capabilities of coordination. The developed architecture follows a knowledge-based approach, where the actions available to the robot are checked at runtime whether they suit the task and the current state of the world. Experimental results on industrially relevant assembly, kitting and hand-over tasks in a laboratory setting demonstrate that graphical command-based and speech-based coordination with high-level commands is effective for collaboration between a human and a robot.
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spelling pubmed-85607012021-11-03 Coordinating Shared Tasks in Human-Robot Collaboration by Commands Angleraud , Alexandre Mehman Sefat, Amir Netzev, Metodi Pieters, Roel Front Robot AI Robotics and AI Human-robot collaboration is gaining more and more interest in industrial settings, as collaborative robots are considered safe and robot actions can be programmed easily by, for example, physical interaction. Despite this, robot programming mostly focuses on automated robot motions and interactive tasks or coordination between human and robot still requires additional developments. For example, the selection of which tasks or actions a robot should do next might not be known beforehand or might change at the last moment. Within a human-robot collaborative setting, the coordination of complex shared tasks, is therefore more suited to a human, where a robot would act upon requested commands.In this work we explore the utilization of commands to coordinate a shared task between a human and a robot, in a shared work space. Based on a known set of higher-level actions (e.g., pick-and-placement, hand-over, kitting) and the commands that trigger them, both a speech-based and graphical command-based interface are developed to investigate its use. While speech-based interaction might be more intuitive for coordination, in industrial settings background sounds and noise might hinder its capabilities. The graphical command-based interface circumvents this, while still demonstrating the capabilities of coordination. The developed architecture follows a knowledge-based approach, where the actions available to the robot are checked at runtime whether they suit the task and the current state of the world. Experimental results on industrially relevant assembly, kitting and hand-over tasks in a laboratory setting demonstrate that graphical command-based and speech-based coordination with high-level commands is effective for collaboration between a human and a robot. Frontiers Media S.A. 2021-10-19 /pmc/articles/PMC8560701/ /pubmed/34738018 http://dx.doi.org/10.3389/frobt.2021.734548 Text en Copyright © 2021 Angleraud , Mehman Sefat, Netzev and Pieters. 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
Angleraud , Alexandre
Mehman Sefat, Amir
Netzev, Metodi
Pieters, Roel
Coordinating Shared Tasks in Human-Robot Collaboration by Commands
title Coordinating Shared Tasks in Human-Robot Collaboration by Commands
title_full Coordinating Shared Tasks in Human-Robot Collaboration by Commands
title_fullStr Coordinating Shared Tasks in Human-Robot Collaboration by Commands
title_full_unstemmed Coordinating Shared Tasks in Human-Robot Collaboration by Commands
title_short Coordinating Shared Tasks in Human-Robot Collaboration by Commands
title_sort coordinating shared tasks in human-robot collaboration by commands
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8560701/
https://www.ncbi.nlm.nih.gov/pubmed/34738018
http://dx.doi.org/10.3389/frobt.2021.734548
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