RoboVisAR : Immersive Authoring of Condition-based AR Robot Visualisations

Lade...
Vorschaubild
Dateien
Lunding_2-mgaacf00m4s78.pdf
Lunding_2-mgaacf00m4s78.pdfGröße: 17.42 MBDownloads: 26
Datum
2024
Autor:innen
Skovhus Lunding, Rasmus
Skovhus Lunding, Mille
Graves Petersen, Marianne
Grønbæk, Kaj
Suzuki, Ryo
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
ArXiv-ID
Internationale Patentnummer
Link zur Lizenz
oops
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Bookpart
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
GROLLMAN, Dan, ed., Elizabeth BROADBENT, ed.. HRI '24 : Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction. New York, NY: ACM, 2024, pp. 462-471. ISBN 979-8-4007-0322-5. Available under: doi: 10.1145/3610977.3634972
Zusammenfassung

We introduce RoboVisAR, an immersive augmented reality (AR) authoring tool for in-situ robot visualisations. AR robot visualisations, such as the robot's movement path, status, and safety zones, have been shown to benefit human-robot collaboration. However, their creation requires extensive skills in both robotics and AR programming. To address this, RoboVisAR allows users to create custom AR robot visualisations without programming. By recording an example robot behaviour, users can design, combine, and test visualisations in-situ within a mixed reality environment. RoboVisAR currently supports six types of visualisations (Path, Point of Interest, Safety Zone, Robot State, Message, Force/Torque) and four types of conditions for when they are displayed (Robot State, Proximity, Box, Force/Torque). With this tool, users can easily present different visualisations on demand and make them context-aware to avoid visual clutter. An expert user study with three participants suggests that users appreciate the customizability of the visualisations, which could easily be authored in less than ten minutes.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Konferenz
HRI '24 : ACM/IEEE International Conference on Human-Robot Interaction, 11. März 2024 - 15. März 2024, Boulder, CO, USA
Rezension
undefined / . - undefined, undefined
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Datensätze
Zitieren
ISO 690SKOVHUS LUNDING, Rasmus, Mille SKOVHUS LUNDING, Tiare FEUCHTNER, Marianne GRAVES PETERSEN, Kaj GRØNBÆK, Ryo SUZUKI, 2024. RoboVisAR : Immersive Authoring of Condition-based AR Robot Visualisations. HRI '24 : ACM/IEEE International Conference on Human-Robot Interaction. Boulder, CO, USA, 11. März 2024 - 15. März 2024. In: GROLLMAN, Dan, ed., Elizabeth BROADBENT, ed.. HRI '24 : Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction. New York, NY: ACM, 2024, pp. 462-471. ISBN 979-8-4007-0322-5. Available under: doi: 10.1145/3610977.3634972
BibTex
@inproceedings{SkovhusLunding2024-03-11RoboV-69712,
  year={2024},
  doi={10.1145/3610977.3634972},
  title={RoboVisAR : Immersive Authoring of Condition-based AR Robot Visualisations},
  isbn={979-8-4007-0322-5},
  publisher={ACM},
  address={New York, NY},
  booktitle={HRI '24 : Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction},
  pages={462--471},
  editor={Grollman, Dan and Broadbent, Elizabeth},
  author={Skovhus Lunding, Rasmus and Skovhus Lunding, Mille and Feuchtner, Tiare and Graves Petersen, Marianne and Grønbæk, Kaj and Suzuki, Ryo}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/69712">
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/69712/1/Lunding_2-mgaacf00m4s78.pdf"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2024-03-27T08:10:35Z</dcterms:available>
    <dc:contributor>Skovhus Lunding, Rasmus</dc:contributor>
    <dcterms:issued>2024-03-11</dcterms:issued>
    <dc:creator>Graves Petersen, Marianne</dc:creator>
    <dc:contributor>Grønbæk, Kaj</dc:contributor>
    <dc:contributor>Skovhus Lunding, Mille</dc:contributor>
    <dc:contributor>Suzuki, Ryo</dc:contributor>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/69712"/>
    <dc:language>eng</dc:language>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/69712/1/Lunding_2-mgaacf00m4s78.pdf"/>
    <dc:contributor>Feuchtner, Tiare</dc:contributor>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:abstract>We introduce RoboVisAR, an immersive augmented reality (AR) authoring tool for in-situ robot visualisations. AR robot visualisations, such as the robot's movement path, status, and safety zones, have been shown to benefit human-robot collaboration. However, their creation requires extensive skills in both robotics and AR programming. To address this, RoboVisAR allows users to create custom AR robot visualisations without programming. By recording an example robot behaviour, users can design, combine, and test visualisations in-situ within a mixed reality environment. RoboVisAR currently supports six types of visualisations (Path, Point of Interest, Safety Zone, Robot State, Message, Force/Torque) and four types of conditions for when they are displayed (Robot State, Proximity, Box, Force/Torque). With this tool, users can easily present different visualisations on demand and make them context-aware to avoid visual clutter. An expert user study with three participants suggests that users appreciate the customizability of the visualisations, which could easily be authored in less than ten minutes.</dcterms:abstract>
    <dc:creator>Grønbæk, Kaj</dc:creator>
    <dc:creator>Suzuki, Ryo</dc:creator>
    <dc:creator>Skovhus Lunding, Rasmus</dc:creator>
    <dc:contributor>Graves Petersen, Marianne</dc:contributor>
    <dc:creator>Skovhus Lunding, Mille</dc:creator>
    <dcterms:title>RoboVisAR : Immersive Authoring of Condition-based AR Robot Visualisations</dcterms:title>
    <dc:creator>Feuchtner, Tiare</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2024-03-27T08:10:35Z</dc:date>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
URL der Originalveröffentl.
Prüfdatum der URL
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Diese Publikation teilen