Impact of Gaze-Based Interaction and Augmentation on Human-Robot Collaboration in Critical Tasks

TL;DR

This study investigates how gaze-based control and visual augmentation affect human-robot collaboration in search-and-rescue tasks, showing significant performance improvements and cognitive load reduction through foveated augmentation.

Contribution

It demonstrates the effectiveness of foveated visual augmentation and gaze analysis in enhancing task performance and understanding user intention in critical scenarios.

Findings

Foveated augmentation improves task performance.

Reduces cognitive load by 38%.

Shortens task time by over 60%.

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.