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Impact of gaze-based interaction and augmentation on human-robot collaboration in critical tasks

Jena, Ayesha LU orcid ; Reitmann, Stefan LU and Topp, Elin Anna LU orcid (2025) In Lecture Notes in Computer Science
Abstract
We present a user study analyzing head-gaze- based robot control and foveated visual augmentation in a simulated search-and-rescue task. Results show that foveated augmentation significantly improves task performance, reduces cognitive load by 38%, and shortens task time by over 60%. Head-gaze patterns analysed over both the entire task duration and shorter time segments show that near and far attention capture is essential to better understand user intention in critical scenarios. Our findings highlight the potential of foveation as an augmentation technique and the need to further study gaze measures to leverage them during critical tasks.
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Working paper/Preprint
publication status
epub
subject
in
Lecture Notes in Computer Science
pages
4 pages
publisher
Springer
project
Distributed Situation Awareness and Mixed-Initiative Interaction for Collaborative Robotics
Mixed - Initiative interaction for Collaborative Robotics
RobotLab LTH
WASP: Wallenberg AI, Autonomous Systems and Software Program at Lund University
language
English
LU publication?
yes
id
4a815052-7036-4f02-bf1b-4d1957e45bb0
date added to LUP
2025-12-18 19:51:21
date last changed
2026-01-07 08:08:58
@misc{4a815052-7036-4f02-bf1b-4d1957e45bb0,
  abstract     = {{We present a user study analyzing head-gaze- based robot control and foveated visual augmentation in a simulated search-and-rescue task. Results show that foveated augmentation significantly improves task performance, reduces cognitive load by 38%, and shortens task time by over 60%. Head-gaze patterns analysed over both the entire task duration and shorter time segments show that near and far attention capture is essential to better understand user intention in critical scenarios. Our findings highlight the potential of foveation as an augmentation technique and the need to further study gaze measures to leverage them during critical tasks.}},
  author       = {{Jena, Ayesha and Reitmann, Stefan and Topp, Elin Anna}},
  language     = {{eng}},
  note         = {{Preprint}},
  publisher    = {{Springer}},
  series       = {{Lecture Notes in Computer Science}},
  title        = {{Impact of gaze-based interaction and augmentation on human-robot collaboration in critical tasks}},
  year         = {{2025}},
}