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Titel: Evaluation of On-Robot Capacitive Proximity Sensors with Collision Experiments for Human-Robot Collaboration
Untertitel:
Kurzfassung:

A robot must comply with very restrictive safety standards in close human-robot collaboration applications. These standards limit the robot's performance because of speed reductions to avoid potentially large forces exerted on humans during collisions. On-robot capacitive proximity sensors (CPS) can serve as a solution to allow higher speeds and thus better productivity. They allow early reactive measures before contacts occur to reduce the forces during collisions. An open question on designing the systems is the selection of an adequate activation distance to trigger safety measures for a specific robot while considering latency and detection robustness. Furthermore, the systems' actual effectiveness of impact attenuation and performance gain has not been evaluated before. In this work, we define and conduct a unified test procedure based on collision experiments to determine these parameters and investigate the performance gain. Two capacitive proximity sensor systems are evaluated on this test strategy on two robots. A significant performance increase can be achieved, since a small detection distance doubles robot operation speed while maintaining the same contact force as without Capacitive Proximity Sensor (CPS). This work can serve as a reference guide for designing, configuring and implementing future on-robot CPS.

Schlagworte: Capacitive Proximity Sensors (CPS), Human-Robot Interaction (HRI), Safety in Human-Robot Collaboration (HRC)
Publikationstyp: Beitrag in Proceedings (Autorenschaft)
Erscheinungsdatum: 23.10.2022 (Print)
Erschienen in: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
zur Publikation
 ( IEEE; )
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Version: -
Seite: S. 6716 - 6723

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Erscheinungsdatum: 23.10.2022
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Erscheinungsdatum: 26.12.2022
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DOI: http://dx.doi.org/10.1109/iros47612.2022.9981490
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Open Access
  • Online verfügbar (nicht Open Access)

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Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Intelligente Systemtechnologien
Universitätsstraße 65-67
9020 Klagenfurt am Wörthersee
Österreich
   hubert.zangl@aau.at
http://www.uni-klu.ac.at/tewi/ict/sst/index.html
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AT - 9020  Klagenfurt am Wörthersee

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Sachgebiete
  • 202036 - Sensorik
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Peer Reviewed
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  • Science to Science (Qualitätsindikator: I)
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