Perceived Appropriateness: A Novel View for Remediating Perceived Inappropriate Robot Navigation Behaviors

Yunzhong Zhou*

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

Robots navigating in social environments inevitably exhibit behavior perceived as inappropriate by people, which they will repeat unless they are aware of them; hindering their social acceptance. This highlights the importance of robots detecting and adapting to the perceived appropriateness of their behavior, in line with what we found in a systematic literature review. Therefore, we have conducted experiments (both outdoor and indoor) to understand the perceived appropriateness of robot social navigation behavior, based on which we collected a dataset and developed a machine learning model for detecting such perceived appropriateness. To investigate the usefulness of such information and inspire robot adaptive navigation behavior design, we will further conduct aWoZ study to understand how trained human operators adapt robot behavior to people's feedback. In all, this work will enable robots to better remediate their inappropriate behavior, thus improving their social acceptance.

Original languageEnglish
Title of host publicationHRI 2023 - Companion of the ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE
Pages781-783
Number of pages3
ISBN (Electronic)978-1-4503-9970-8
DOIs
Publication statusPublished - 2023
Event18th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2023 - Stockholm, Sweden
Duration: 13 Mar 202316 Mar 2023

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148

Conference

Conference18th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2023
Country/TerritorySweden
CityStockholm
Period13/03/2316/03/23

Keywords

  • Adaptive Behavior
  • Human-Robot Interaction
  • Perceived Appropriateness
  • Social Navigation
  • Social Signal Processing

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