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PREDICTOR: A Physical emulatoR enabling safEty anD ergonomICs evaluation and Training of physical human-rObot collaboRation

Safety and ergonomics of Physical Human-Robot Collaboration (PHRC) are crucial to make human-robot collaborative systems trustworthy and make a significant impact in real-world applications. One big obstacle to the development of relevant research is the lack of a general platform for evaluating the...

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Autores principales: Sunesson, Carl Emil, Schøn, Daniel Tofte, Hassø, Christopher Nybo Ploug, Chinello, Francesco, Fang, Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9968835/
https://www.ncbi.nlm.nih.gov/pubmed/36860936
http://dx.doi.org/10.3389/fnbot.2023.1080038
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author Sunesson, Carl Emil
Schøn, Daniel Tofte
Hassø, Christopher Nybo Ploug
Chinello, Francesco
Fang, Cheng
author_facet Sunesson, Carl Emil
Schøn, Daniel Tofte
Hassø, Christopher Nybo Ploug
Chinello, Francesco
Fang, Cheng
author_sort Sunesson, Carl Emil
collection PubMed
description Safety and ergonomics of Physical Human-Robot Collaboration (PHRC) are crucial to make human-robot collaborative systems trustworthy and make a significant impact in real-world applications. One big obstacle to the development of relevant research is the lack of a general platform for evaluating the safety and ergonomics of proposed PHRC systems. This paper aims to create a Physical emulatoR enabling safEty anD ergonomICs evaluation and Training of physical human-rObot collaboRation (PREDICTOR). PREDICTOR consists of a dual-arm robot system and a VR headset as its hardware and contains physical simulation, haptic rendering and visual rendering modules as its software. The dual-arm robot system is used as an integrated admittance-type haptic device, which senses the force/torque applied by a human operator as an input to drive the simulation of a PHRC system and constrains the handles' motion to match their virtual counterparts in the simulation. The motion of the PHRC system in the simulation is fed back to the operator through the VR headset. PREDICTOR combines haptics and VR to emulate PHRC tasks in a safe environment since the interactive forces are monitored to avoid any risky events. PREDICTOR also brings flexibility as different PHRC tasks can be easily set up by changing the PHRC system model and the robot controller in the simulation. The effectiveness and performance of PREDICTOR were evaluated by experiments.
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spelling pubmed-99688352023-02-28 PREDICTOR: A Physical emulatoR enabling safEty anD ergonomICs evaluation and Training of physical human-rObot collaboRation Sunesson, Carl Emil Schøn, Daniel Tofte Hassø, Christopher Nybo Ploug Chinello, Francesco Fang, Cheng Front Neurorobot Neuroscience Safety and ergonomics of Physical Human-Robot Collaboration (PHRC) are crucial to make human-robot collaborative systems trustworthy and make a significant impact in real-world applications. One big obstacle to the development of relevant research is the lack of a general platform for evaluating the safety and ergonomics of proposed PHRC systems. This paper aims to create a Physical emulatoR enabling safEty anD ergonomICs evaluation and Training of physical human-rObot collaboRation (PREDICTOR). PREDICTOR consists of a dual-arm robot system and a VR headset as its hardware and contains physical simulation, haptic rendering and visual rendering modules as its software. The dual-arm robot system is used as an integrated admittance-type haptic device, which senses the force/torque applied by a human operator as an input to drive the simulation of a PHRC system and constrains the handles' motion to match their virtual counterparts in the simulation. The motion of the PHRC system in the simulation is fed back to the operator through the VR headset. PREDICTOR combines haptics and VR to emulate PHRC tasks in a safe environment since the interactive forces are monitored to avoid any risky events. PREDICTOR also brings flexibility as different PHRC tasks can be easily set up by changing the PHRC system model and the robot controller in the simulation. The effectiveness and performance of PREDICTOR were evaluated by experiments. Frontiers Media S.A. 2023-02-13 /pmc/articles/PMC9968835/ /pubmed/36860936 http://dx.doi.org/10.3389/fnbot.2023.1080038 Text en Copyright © 2023 Sunesson, Schøn, Hassø, Chinello and Fang. 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 Neuroscience
Sunesson, Carl Emil
Schøn, Daniel Tofte
Hassø, Christopher Nybo Ploug
Chinello, Francesco
Fang, Cheng
PREDICTOR: A Physical emulatoR enabling safEty anD ergonomICs evaluation and Training of physical human-rObot collaboRation
title PREDICTOR: A Physical emulatoR enabling safEty anD ergonomICs evaluation and Training of physical human-rObot collaboRation
title_full PREDICTOR: A Physical emulatoR enabling safEty anD ergonomICs evaluation and Training of physical human-rObot collaboRation
title_fullStr PREDICTOR: A Physical emulatoR enabling safEty anD ergonomICs evaluation and Training of physical human-rObot collaboRation
title_full_unstemmed PREDICTOR: A Physical emulatoR enabling safEty anD ergonomICs evaluation and Training of physical human-rObot collaboRation
title_short PREDICTOR: A Physical emulatoR enabling safEty anD ergonomICs evaluation and Training of physical human-rObot collaboRation
title_sort predictor: a physical emulator enabling safety and ergonomics evaluation and training of physical human-robot collaboration
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9968835/
https://www.ncbi.nlm.nih.gov/pubmed/36860936
http://dx.doi.org/10.3389/fnbot.2023.1080038
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