Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

To ask or not to ask : a user annoyance aware preference elicitation framework for social robots

Tools
- Tools
+ Tools

Gucsi, Balint, Tarapore, Danesh S., Yeoh, William, Amato, Christopher and Tran-Thanh, Long (2020) To ask or not to ask : a user annoyance aware preference elicitation framework for social robots. In: International Conference on Intelligent Robots and Systems (IROS 2020), Las Vegas, Nevada, USA, 24-29 Oct 2020. Published in: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ISBN 9781728162133. ISSN 2153-0866. doi:10.1109/IROS45743.2020.9341607

[img]
Preview
PDF
WRAP-ask-user-annoyance-aware-social-robots-Tran-Thanh-2020 pdf.pdf - Accepted Version - Requires a PDF viewer.

Download (1783Kb) | Preview
Official URL: https://doi.org/10.1109/IROS45743.2020.9341607

Request Changes to record.

Abstract

In this paper we investigate how social robots can efficiently gather user preferences without exceeding the allowed user annoyance threshold. To do so, we use a Gazebo based simulated office environment with a TIAGo Steel robot. We then formulate the user annoyance aware preference elicitation problem as a combination of tensor completion and knapsack problems. We then test our approach on the aforementioned simulated environment and demonstrate that it can accurately estimate user preferences.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Human-robot interaction -- Social aspects, Artificial intelligence
Journal or Publication Title: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Publisher: IEEE
ISBN: 9781728162133
ISSN: 2153-0866
Official Date: 10 February 2020
Dates:
DateEvent
10 February 2020Published
30 June 2020Accepted
DOI: 10.1109/IROS45743.2020.9341607
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Conference Paper Type: Paper
Title of Event: International Conference on Intelligent Robots and Systems (IROS 2020)
Type of Event: Conference
Location of Event: Las Vegas, Nevada, USA
Date(s) of Event: 24-29 Oct 2020
Related URLs:
  • Publisher

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us