dc.identifier.uri |
http://dx.doi.org/10.15488/3517 |
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dc.identifier.uri |
https://www.repo.uni-hannover.de:443/handle/123456789/3547 |
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dc.contributor.author |
Kühn, Johannes
|
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dc.contributor.author |
Haddadin, Sami
|
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dc.date.accessioned |
2018-07-09T11:08:09Z |
|
dc.date.available |
2018-07-09T11:08:09Z |
|
dc.date.issued |
2016 |
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dc.identifier.citation |
Kuehn, J.; Haddadin, S.: An Artificial Robot Nervous System To Teach Robots How To Feel Pain And Reflexively React To Potentially Damaging Contacts. In: IEEE Robotics and Automation Letters 2 (2016), S. 72-79. DOI: https://doi.org/10.1109/LRA.2016.2536360 |
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dc.description.abstract |
In this letter, we introduce the concept of an artificial Robot Nervous System (aRNS) as a novel way of unifying multimodal physical stimuli sensation with robot pain-reflex movements. We focus on the formalization of robot pain, based on insights from human pain research, as an interpretation of tactile sensation. Specifically, pain signals are used to adapt the equilibrium position, stiffness, and feedforward torque of a pain-based impedance controller. The schemes are experimentally validated with the KUKA LWR4+ for simulated and real physical collisions using the BioTac sensor. |
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dc.description.sponsorship |
European Commission/H2020/688857/EU |
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dc.language.iso |
eng |
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dc.publisher |
Piscataway, NJ : Institute of Electrical and Electronics Engineers Inc. |
|
dc.relation |
info:eu-repo/grantAgreement/European Commission/H2020/688857/EU |
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dc.relation.ispartofseries |
IEEE Robotics and Automation Letters 2 (2016) |
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dc.rights |
Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. |
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dc.subject |
Physical Human-Robot Interaction |
eng |
dc.subject |
Compliance and Impedance Control |
eng |
dc.subject |
Biologically-Inspired Robots |
eng |
dc.subject |
Biomimetics |
eng |
dc.subject |
Force and Tactile Sensing |
eng |
dc.subject.ddc |
621,3 | Elektrotechnik, Elektronik
|
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dc.title |
An Artificial Robot Nervous System To Teach Robots How To Feel Pain And Reflexively React To Potentially Damaging Contacts |
eng |
dc.type |
Article |
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dc.type |
Text |
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dc.relation.issn |
2377-3766 |
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dc.relation.doi |
10.1109/LRA.2016.2536360 |
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dc.bibliographicCitation.firstPage |
72 |
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dc.bibliographicCitation.lastPage |
79 |
|
dc.description.version |
acceptedVersion |
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tib.accessRights |
frei zug�nglich |
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