Perceived Appropriateness

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

Zhou, Y. (TU Delft Internet of Things; TU Delft Industrial Design Engineering)

Industrial Design Engineering

2023

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.

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

http://resolver.tudelft.nl/uuid:51cb1c9e-69de-48da-8ff1-b86e897db2c3

https://doi.org/10.1145/3568294.3579984

IEEE

2023-09-13

978-1-4503-9970-8

HRI 2023 - Companion of the ACM/IEEE International Conference on Human-Robot Interaction

18th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2023, 2023-03-13 → 2023-03-16, Stockholm, Sweden

ACM/IEEE International Conference on Human-Robot Interaction, 2167-2148

Institutional Repository

conference paper

© 2023 Y. Zhou