kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Will You Participate? Exploring the Potential of Robotics Competitions on Human-Centric Topics
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0003-1804-6296
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Collaborative Autonomous Systems.ORCID iD: 0000-0002-5761-4105
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0003-0579-3372
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0003-2965-2953
2024 (English)In: Human-Computer Interaction - Thematic Area, HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Proceedings, Springer Nature , 2024, p. 240-255Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents findings from an exploratory needfinding study investigating the research current status and potential participation of the competitions on the robotics community towards four human-centric topics: safety, privacy, explainability, and federated learning. We conducted a survey with 34 participants across three distinguished European robotics consortia, nearly 60% of whom possessed over five years of research experience in robotics. Our qualitative and quantitative analysis revealed that current mainstream robotic researchers prioritize safety and explainability, expressing a greater willingness to invest in further research in these areas. Conversely, our results indicate that privacy and federated learning garner less attention and are perceived to have lower potential. Additionally, the study suggests a lack of enthusiasm within the robotics community for participating in competitions related to these topics. Based on these findings, we recommend targeting other communities, such as the machine learning community, for future competitions related to these four human-centric topics.

Place, publisher, year, edition, pages
Springer Nature , 2024. p. 240-255
Keywords [en]
explainability, federated learning, needfinding, privacy, Robotics, safety, survey
National Category
Computer Sciences Robotics and automation
Identifiers
URN: urn:nbn:se:kth:diva-350540DOI: 10.1007/978-3-031-60412-6_18ISI: 001283865000018Scopus ID: 2-s2.0-85195824006OAI: oai:DiVA.org:kth-350540DiVA, id: diva2:1884451
Conference
Human Computer Interaction thematic area of the 26th International Conference on Human-Computer Interaction, HCII 2024, Washington, United States of America, Jun 29 2024 - Jul 4 2024
Note

Part of ISBN 9783031604119

QC 20240716

Available from: 2024-07-16 Created: 2024-07-16 Last updated: 2025-02-05Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Zhang, YuchongVasco, MiguelBjörkman, MårtenKragic, Danica

Search in DiVA

By author/editor
Zhang, YuchongVasco, MiguelBjörkman, MårtenKragic, Danica
By organisation
Robotics, Perception and Learning, RPLCollaborative Autonomous Systems
Computer SciencesRobotics and automation

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 70 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf