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Planning Fail-Safe Trajectories for Space Robotic Arms

A frequent concern for robot manipulators deployed in dangerous and hazardous environments for humans is the reliability of task executions in the event of a joint failure. A redundant robotic manipulator can be used to mitigate the risk and guarantee a post-failure task completion, which is critica...

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Detalles Bibliográficos
Autores principales: Porges, Oliver, Leidner, Daniel, Roa, Máximo A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8671041/
https://www.ncbi.nlm.nih.gov/pubmed/34917652
http://dx.doi.org/10.3389/frobt.2021.710021
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author Porges, Oliver
Leidner, Daniel
Roa, Máximo A.
author_facet Porges, Oliver
Leidner, Daniel
Roa, Máximo A.
author_sort Porges, Oliver
collection PubMed
description A frequent concern for robot manipulators deployed in dangerous and hazardous environments for humans is the reliability of task executions in the event of a joint failure. A redundant robotic manipulator can be used to mitigate the risk and guarantee a post-failure task completion, which is critical for instance for space applications. This paper describes methods to analyze potential risks due to a joint failure, and introduces tools for fault-tolerant task design and path planning for robotic manipulators. The presented methods are based on off-line precomputed workspace models. The methods are general enough to cope with robots with any type of joint (revolute or prismatic) and any number of degrees of freedom, and might include arbitrarily shaped obstacles in the process, without resorting to simplified models. Application examples illustrate the potential of the approach.
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spelling pubmed-86710412021-12-15 Planning Fail-Safe Trajectories for Space Robotic Arms Porges, Oliver Leidner, Daniel Roa, Máximo A. Front Robot AI Robotics and AI A frequent concern for robot manipulators deployed in dangerous and hazardous environments for humans is the reliability of task executions in the event of a joint failure. A redundant robotic manipulator can be used to mitigate the risk and guarantee a post-failure task completion, which is critical for instance for space applications. This paper describes methods to analyze potential risks due to a joint failure, and introduces tools for fault-tolerant task design and path planning for robotic manipulators. The presented methods are based on off-line precomputed workspace models. The methods are general enough to cope with robots with any type of joint (revolute or prismatic) and any number of degrees of freedom, and might include arbitrarily shaped obstacles in the process, without resorting to simplified models. Application examples illustrate the potential of the approach. Frontiers Media S.A. 2021-11-30 /pmc/articles/PMC8671041/ /pubmed/34917652 http://dx.doi.org/10.3389/frobt.2021.710021 Text en Copyright © 2021 Porges, Leidner and Roa. 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
Porges, Oliver
Leidner, Daniel
Roa, Máximo A.
Planning Fail-Safe Trajectories for Space Robotic Arms
title Planning Fail-Safe Trajectories for Space Robotic Arms
title_full Planning Fail-Safe Trajectories for Space Robotic Arms
title_fullStr Planning Fail-Safe Trajectories for Space Robotic Arms
title_full_unstemmed Planning Fail-Safe Trajectories for Space Robotic Arms
title_short Planning Fail-Safe Trajectories for Space Robotic Arms
title_sort planning fail-safe trajectories for space robotic arms
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8671041/
https://www.ncbi.nlm.nih.gov/pubmed/34917652
http://dx.doi.org/10.3389/frobt.2021.710021
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