Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

The effectiveness of dynamically processed incremental descriptions in human robot interaction

Wallbridge, Christopher D. ORCID: https://orcid.org/0000-0001-9468-122X, Smith, Alex, Giuliani, Manuel, Melhuish, Chris, Belpaeme, Tony and Lemaignan, Severin 2022. The effectiveness of dynamically processed incremental descriptions in human robot interaction. ACM Transactions on Human-Robot Interaction 11 (1) , 7. 10.1145/3481628

[thumbnail of 3481628.pdf]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

Download (7MB) | Preview

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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Psychology
Publisher: ACM
ISSN: 2573-9522
Funders: EPSRC
Date of First Compliant Deposit: 24 August 2021
Date of Acceptance: 15 July 2021
Last Modified: 18 May 2023 10:21
URI: https://orca.cardiff.ac.uk/id/eprint/143640

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics