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No-code robotic programming for agile production: A new markerless-approach for multimodal natural interaction in a human-robot collaboration context

Industrial robots and cobots are widely deployed in most industrial sectors. However, robotic programming still needs a lot of time and effort in small batch sizes, and it demands specific expertise and special training, especially when various robotic platforms are required. Actual low-code or no-c...

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Autores principales: Halim, Jayanto, Eichler, Paul, Krusche, Sebastian, Bdiwi, Mohamad, Ihlenfeldt, Steffen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583918/
https://www.ncbi.nlm.nih.gov/pubmed/36274910
http://dx.doi.org/10.3389/frobt.2022.1001955
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author Halim, Jayanto
Eichler, Paul
Krusche, Sebastian
Bdiwi, Mohamad
Ihlenfeldt, Steffen
author_facet Halim, Jayanto
Eichler, Paul
Krusche, Sebastian
Bdiwi, Mohamad
Ihlenfeldt, Steffen
author_sort Halim, Jayanto
collection PubMed
description Industrial robots and cobots are widely deployed in most industrial sectors. However, robotic programming still needs a lot of time and effort in small batch sizes, and it demands specific expertise and special training, especially when various robotic platforms are required. Actual low-code or no-code robotic programming solutions are exorbitant and meager. This work proposes a novel approach for no-code robotic programming for end-users with adequate or no expertise in industrial robotic. The proposed method ensures intuitive and fast robotic programming by utilizing a finite state machine with three layers of natural interactions based on hand gesture, finger gesture, and voice recognition. The implemented system combines intelligent computer vision and voice control capabilities. Using a vision system, the human could transfer spatial information of a 3D point, lines, and trajectories using hand and finger gestures. The voice recognition system will assist the user in parametrizing robot parameters and interacting with the robot’s state machine. Furthermore, the proposed method will be validated and compared with state-of-the-art “Hand-Guiding” cobot devices within real-world experiments. The results obtained are auspicious, and indicate the capability of this novel approach for real-world deployment in an industrial context.
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spelling pubmed-95839182022-10-21 No-code robotic programming for agile production: A new markerless-approach for multimodal natural interaction in a human-robot collaboration context Halim, Jayanto Eichler, Paul Krusche, Sebastian Bdiwi, Mohamad Ihlenfeldt, Steffen Front Robot AI Robotics and AI Industrial robots and cobots are widely deployed in most industrial sectors. However, robotic programming still needs a lot of time and effort in small batch sizes, and it demands specific expertise and special training, especially when various robotic platforms are required. Actual low-code or no-code robotic programming solutions are exorbitant and meager. This work proposes a novel approach for no-code robotic programming for end-users with adequate or no expertise in industrial robotic. The proposed method ensures intuitive and fast robotic programming by utilizing a finite state machine with three layers of natural interactions based on hand gesture, finger gesture, and voice recognition. The implemented system combines intelligent computer vision and voice control capabilities. Using a vision system, the human could transfer spatial information of a 3D point, lines, and trajectories using hand and finger gestures. The voice recognition system will assist the user in parametrizing robot parameters and interacting with the robot’s state machine. Furthermore, the proposed method will be validated and compared with state-of-the-art “Hand-Guiding” cobot devices within real-world experiments. The results obtained are auspicious, and indicate the capability of this novel approach for real-world deployment in an industrial context. Frontiers Media S.A. 2022-10-04 /pmc/articles/PMC9583918/ /pubmed/36274910 http://dx.doi.org/10.3389/frobt.2022.1001955 Text en Copyright © 2022 Halim, Eichler, Krusche, Bdiwi and Ihlenfeldt. 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
Halim, Jayanto
Eichler, Paul
Krusche, Sebastian
Bdiwi, Mohamad
Ihlenfeldt, Steffen
No-code robotic programming for agile production: A new markerless-approach for multimodal natural interaction in a human-robot collaboration context
title No-code robotic programming for agile production: A new markerless-approach for multimodal natural interaction in a human-robot collaboration context
title_full No-code robotic programming for agile production: A new markerless-approach for multimodal natural interaction in a human-robot collaboration context
title_fullStr No-code robotic programming for agile production: A new markerless-approach for multimodal natural interaction in a human-robot collaboration context
title_full_unstemmed No-code robotic programming for agile production: A new markerless-approach for multimodal natural interaction in a human-robot collaboration context
title_short No-code robotic programming for agile production: A new markerless-approach for multimodal natural interaction in a human-robot collaboration context
title_sort no-code robotic programming for agile production: a new markerless-approach for multimodal natural interaction in a human-robot collaboration context
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583918/
https://www.ncbi.nlm.nih.gov/pubmed/36274910
http://dx.doi.org/10.3389/frobt.2022.1001955
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