Assessing latency cascades: Quantify time-to-respond dynamics in human-robot collaboration for speed and separation monitoring

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dc.contributor.authorRinaldi, Alessandraen
dc.contributor.authorMenolotto, Matteoen
dc.contributor.authorKelly, Daviden
dc.contributor.authorTorres-Sanchez, Javieren
dc.contributor.authorO’Flynn, Brendanen
dc.contributor.authorChiaberge, Marcelloen
dc.contributor.funderEnterprise Irelanden
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderPolitecnico di Torinoen
dc.date.accessioned2025-01-20T10:23:13Z
dc.date.available2025-01-20T10:23:13Z
dc.date.issued2024-11-05en
dc.description.abstractAdvancements in sensing technology and artificial intelligence have revolutionized industrial settings by introducing robots that work alongside humans, enhancing productivity and flexibility. However, ensuring safety in human-robot interactions has become more challenging. Established safety standards emphasize risk assessment, protective measures, and real-time monitoring systems, where safety complexities arise from intricate industrial interactions. The study focuses on “Speed and Separation Monitoring” (SSM), a collaborative type defined by ISO/TS 15066. The research addresses unknowns within SSM, particularly on the parameter accounting for the robot system to respond to the operator’s presence, crucial for decision-making on speed and separation limits. A proximity sensor was utilized to assess the overall delay of a classic industrial network between the sensing node for the operator detection (AI-based vision system) and the triggering of the safety node to the robot. The methodology was tested on a cohort of 23 subjects and evaluated under various lighting conditions. The study identified bottlenecks and the impact of each subsystem composing typical industrial control networks, highlighting the need for precise methodologies to assess latency as a critical factor in safety and productivity as sensing technology, collaborative robots and safety networks keep evolving.en
dc.description.sponsorshipEnterprise Ireland and Science Foundation Ireland through (DTIF project SafetyBot DT20200274); Politecnico di Torino (Student Mobility Scholarship)en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRinaldi, A., Menolotto, M., Kelly, D., Torres-Sanchez, J., O’Flynn, B. and Chiaberge, M. (2024) 'Assessing latency cascades: Quantify time-to-respond dynamics in human-robot collaboration for speed and separation monitoring', 2024 Smart Systems Integration Conference and Exhibition (SSI), Hamburg, Germany, 16-18 April 2024, pp. 1-6. https://doi.org/10.1109/SSI63222.2024.10740517en
dc.identifier.doihttps://doi.org/10.1109/SSI63222.2024.10740517en
dc.identifier.endpage6en
dc.identifier.isbn979-8-3503-8878-7en
dc.identifier.isbn979-8-3503-8877-0en
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/16845
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.ispartof2024 Smart Systems Integration Conference and Exhibition (SSI), Hamburg, Germany, 16-18 April 2024en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres Programme::Phase 1/16/RC/3835/IE/VistaMilk Centre/en
dc.rights© 2024, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.subjectLatencyen
dc.subjectCollaborative roboticsen
dc.subjectSafetyen
dc.subjectSpeed and separation monitoringen
dc.titleAssessing latency cascades: Quantify time-to-respond dynamics in human-robot collaboration for speed and separation monitoringen
dc.typeConference itemen
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