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dc.contributor.authorJocas, Men
dc.contributor.authorKurrek, Pen
dc.contributor.authorZoghlami, Fen
dc.contributor.authorGianni, Men
dc.contributor.authorSalehi, Ven
dc.date.accessioned2021-09-28T11:20:57Z
dc.date.issued2019-07-26en
dc.identifier.urihttp://hdl.handle.net/10026.1/17969
dc.description.abstract

<jats:title>Abstract</jats:title><jats:p>Robotic systems need to achieve a certain level of process safety during the performance of the task and at the same time ensure compliance with safety criteria for the expected behaviour. To achieve this, the system must be aware of the risks related to the performance of the task in order to be able to take these into account accordingly. Once the safety aspects have been learned from the system, the task performance must no longer influence them. To achieve this, we present a concept for the design of a neural network that combines these characteristics. This enables the learning of safe behaviour and the fixation of it. The subsequent training of the task execution no longer influences safety and achieves targeted results in comparison to a conventional neural network.</jats:p>

en
dc.format.extent2041 - 2050en
dc.language.isoenen
dc.publisherCambridge University Press (CUP)en
dc.titleAI-Based Learning Approach with Consideration of Safety Criteria on Example of a Depalletization Roboten
dc.typeConference Contribution
plymouth.issue1en
plymouth.volume1en
plymouth.journalProceedings of the Design Society: International Conference on Engineering Designen
dc.identifier.doi10.1017/dsi.2019.210en
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dcterms.dateAccepted2019-01-01en
dc.rights.embargodate2021-09-29
dc.identifier.eissn2220-4342en
dc.rights.embargoperiodNot knownen
rioxxterms.versionofrecord10.1017/dsi.2019.210en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2019-07-26en
rioxxterms.typeConference Paper/Proceeding/Abstracten


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