Tri-modal speed and separation monitoring technique using static-dynamic danger field implementation

Speed and Separation Monitoring (SSM) has become one of the recent methods to ensure safety in Human Robot Interactions (HRI). SSM maintains a safe separation distance between the robot and any human collaborator and issues a safety-rated halt to the robot when the set safe distance is violated. SSM...

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Main Authors: Andres, Charles Patrick C., Hernandez, Jason Patrick L., Baldelomar, Lourdes T., Martin, Christian Dior F., Cantor, John Paul S., Poblete, Joycelyn P., Raca, Jasmin D., Vicerra, Ryan Rhay P.
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Published: Animo Repository 2019
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/3465
https://animorepository.dlsu.edu.ph/context/faculty_research/article/4467/type/native/viewcontent/HNICEM.2018.8666305
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-44672021-09-09T03:10:11Z Tri-modal speed and separation monitoring technique using static-dynamic danger field implementation Andres, Charles Patrick C. Hernandez, Jason Patrick L. Baldelomar, Lourdes T. Martin, Christian Dior F. Cantor, John Paul S. Poblete, Joycelyn P. Raca, Jasmin D. Vicerra, Ryan Rhay P. Speed and Separation Monitoring (SSM) has become one of the recent methods to ensure safety in Human Robot Interactions (HRI). SSM maintains a safe separation distance between the robot and any human collaborator and issues a safety-rated halt to the robot when the set safe distance is violated. SSM could be classified into two: Static, which uses a predefined offline safeguard volume and Dynamic, which uses a more-fit online-calculated volume. A trade-off arises between the two as Static SSM is often over conservative and significantly affect the productivity of the system, while dynamic SSM may become less reliable in terms of safety performance as the maximum velocity of the robot is increased. These trends are confirmed through the system created in this study. To overcome the trade-off, this study proposes a combination of the two in a tri-modal SSM. Using the KUKA Robot AGILUS SIXX as arm manipulator, Microsoft Kinect as sensor, JOpenShowVar as middleware, and MATLAB R2013a for the user interface, the researchers were able to create a system that offers a better trade-off compared to its counterparts. The proposed system is reliably safe at higher speeds compared to the dynamic implementation but still significantly productive compared to the static implementation. © 2018 IEEE. 2019-03-12T07:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/3465 info:doi/10.1109/HNICEM.2018.8666305 https://animorepository.dlsu.edu.ph/context/faculty_research/article/4467/type/native/viewcontent/HNICEM.2018.8666305 Faculty Research Work Animo Repository Human-robot interaction Robots—Dynamics Manufacturing
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Human-robot interaction
Robots—Dynamics
Manufacturing
spellingShingle Human-robot interaction
Robots—Dynamics
Manufacturing
Andres, Charles Patrick C.
Hernandez, Jason Patrick L.
Baldelomar, Lourdes T.
Martin, Christian Dior F.
Cantor, John Paul S.
Poblete, Joycelyn P.
Raca, Jasmin D.
Vicerra, Ryan Rhay P.
Tri-modal speed and separation monitoring technique using static-dynamic danger field implementation
description Speed and Separation Monitoring (SSM) has become one of the recent methods to ensure safety in Human Robot Interactions (HRI). SSM maintains a safe separation distance between the robot and any human collaborator and issues a safety-rated halt to the robot when the set safe distance is violated. SSM could be classified into two: Static, which uses a predefined offline safeguard volume and Dynamic, which uses a more-fit online-calculated volume. A trade-off arises between the two as Static SSM is often over conservative and significantly affect the productivity of the system, while dynamic SSM may become less reliable in terms of safety performance as the maximum velocity of the robot is increased. These trends are confirmed through the system created in this study. To overcome the trade-off, this study proposes a combination of the two in a tri-modal SSM. Using the KUKA Robot AGILUS SIXX as arm manipulator, Microsoft Kinect as sensor, JOpenShowVar as middleware, and MATLAB R2013a for the user interface, the researchers were able to create a system that offers a better trade-off compared to its counterparts. The proposed system is reliably safe at higher speeds compared to the dynamic implementation but still significantly productive compared to the static implementation. © 2018 IEEE.
format text
author Andres, Charles Patrick C.
Hernandez, Jason Patrick L.
Baldelomar, Lourdes T.
Martin, Christian Dior F.
Cantor, John Paul S.
Poblete, Joycelyn P.
Raca, Jasmin D.
Vicerra, Ryan Rhay P.
author_facet Andres, Charles Patrick C.
Hernandez, Jason Patrick L.
Baldelomar, Lourdes T.
Martin, Christian Dior F.
Cantor, John Paul S.
Poblete, Joycelyn P.
Raca, Jasmin D.
Vicerra, Ryan Rhay P.
author_sort Andres, Charles Patrick C.
title Tri-modal speed and separation monitoring technique using static-dynamic danger field implementation
title_short Tri-modal speed and separation monitoring technique using static-dynamic danger field implementation
title_full Tri-modal speed and separation monitoring technique using static-dynamic danger field implementation
title_fullStr Tri-modal speed and separation monitoring technique using static-dynamic danger field implementation
title_full_unstemmed Tri-modal speed and separation monitoring technique using static-dynamic danger field implementation
title_sort tri-modal speed and separation monitoring technique using static-dynamic danger field implementation
publisher Animo Repository
publishDate 2019
url https://animorepository.dlsu.edu.ph/faculty_research/3465
https://animorepository.dlsu.edu.ph/context/faculty_research/article/4467/type/native/viewcontent/HNICEM.2018.8666305
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