Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
1 file | 7.41 MB
Add to list
  1. Search results
  2. The effectiveness of dynamically proc...

The effectiveness of dynamically processed incremental descriptions in human robot interaction

Christopher D. Wallbridge, Alex Smith, Manuel Giuliani, Chris Melhuish, Tony Belpaeme (UGent) and Séverin Lemaignan
(2022) ACM TRANSACTIONS ON HUMAN-ROBOT INTERACTION. 11(1).
Author
Organization
Project
Abstract
We explore the effectiveness of a dynamically processed incremental referring description system using under-specified ambiguous descriptions that are then built upon using linguistic repair statements, which we refer to as a dynamic system. We build a dynamically processed incremental referring description generation system that is able to provide contextual navigational statements to describe an object in a potential real-world situation of nuclear waste sorting and maintenance. In a study of 31 participants, we test the dynamic system in a case where a user is remote operating a robot to sort nuclear waste, with the robot assisting them in identifying the correct barrels to be removed. We compare these against a static non-ambiguous description given in the same scenario. As well as looking at efficiency with time and distance measurements, we also look at user preference. Results show that our dynamic system was a much more efficient method—taking only 62% of the time on average—for finding the correct barrel. Participants also favoured our dynamic system.
Keywords
Artificial Intelligence, Human-Computer Interaction, Human robot interaction, natural language, spatial referring expressions, dynamic description, ambiguous, machine learning, user study, robots for nuclear environments

Downloads

  • Download
    (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 7.41 MB

Citation

Please use this url to cite or link to this publication:

MLA
Wallbridge, Christopher D., et al. “The Effectiveness of Dynamically Processed Incremental Descriptions in Human Robot Interaction.” ACM TRANSACTIONS ON HUMAN-ROBOT INTERACTION, vol. 11, no. 1, 2022, doi:10.1145/3481628.
APA
Wallbridge, C. D., Smith, A., Giuliani, M., Melhuish, C., Belpaeme, T., & Lemaignan, S. (2022). The effectiveness of dynamically processed incremental descriptions in human robot interaction. ACM TRANSACTIONS ON HUMAN-ROBOT INTERACTION, 11(1). https://doi.org/10.1145/3481628
Chicago author-date
Wallbridge, Christopher D., Alex Smith, Manuel Giuliani, Chris Melhuish, Tony Belpaeme, and Séverin Lemaignan. 2022. “The Effectiveness of Dynamically Processed Incremental Descriptions in Human Robot Interaction.” ACM TRANSACTIONS ON HUMAN-ROBOT INTERACTION 11 (1). https://doi.org/10.1145/3481628.
Chicago author-date (all authors)
Wallbridge, Christopher D., Alex Smith, Manuel Giuliani, Chris Melhuish, Tony Belpaeme, and Séverin Lemaignan. 2022. “The Effectiveness of Dynamically Processed Incremental Descriptions in Human Robot Interaction.” ACM TRANSACTIONS ON HUMAN-ROBOT INTERACTION 11 (1). doi:10.1145/3481628.
Vancouver
1.
Wallbridge CD, Smith A, Giuliani M, Melhuish C, Belpaeme T, Lemaignan S. The effectiveness of dynamically processed incremental descriptions in human robot interaction. ACM TRANSACTIONS ON HUMAN-ROBOT INTERACTION. 2022;11(1).
IEEE
[1]
C. D. Wallbridge, A. Smith, M. Giuliani, C. Melhuish, T. Belpaeme, and S. Lemaignan, “The effectiveness of dynamically processed incremental descriptions in human robot interaction,” ACM TRANSACTIONS ON HUMAN-ROBOT INTERACTION, vol. 11, no. 1, 2022.
@article{8725061,
  abstract     = {{We explore the effectiveness of a dynamically processed incremental referring description system using under-specified ambiguous descriptions that are then built upon using linguistic repair statements, which we refer to as a dynamic system. We build a dynamically processed incremental referring description generation system that is able to provide contextual navigational statements to describe an object in a potential real-world situation of nuclear waste sorting and maintenance. In a study of 31 participants, we test the dynamic system in a case where a user is remote operating a robot to sort nuclear waste, with the robot assisting them in identifying the correct barrels to be removed. We compare these against a static non-ambiguous description given in the same scenario. As well as looking at efficiency with time and distance measurements, we also look at user preference. Results show that our dynamic system was a much more efficient method—taking only 62% of the time on average—for finding the correct barrel. Participants also favoured our dynamic system.}},
  articleno    = {{7}},
  author       = {{Wallbridge, Christopher D. and Smith, Alex and Giuliani, Manuel and Melhuish, Chris and Belpaeme, Tony and Lemaignan, Séverin}},
  issn         = {{2573-9522}},
  journal      = {{ACM TRANSACTIONS ON HUMAN-ROBOT INTERACTION}},
  keywords     = {{Artificial Intelligence,Human-Computer Interaction,Human robot interaction,natural language,spatial referring expressions,dynamic description,ambiguous,machine learning,user study,robots for nuclear environments}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{24}},
  title        = {{The effectiveness of dynamically processed incremental descriptions in human robot interaction}},
  url          = {{http://doi.org/10.1145/3481628}},
  volume       = {{11}},
  year         = {{2022}},
}
Altmetric
View in Altmetric