Date of Award

Spring 2026

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

Committee Director

Sampath Jayarathna

Committee Member

Faryaneh Poursardar

Committee Member

Vikas Ashok

Abstract

With drone usage increasing in recent years, many navigational control methods are being developed. One of these control methods is through eye movements. The problem with using eye movements as input is that all input can be valid input. Gaze gestures, which are point to point eye movements, are a way to mitigate this. Current work using gaze gestures for drone navigation focus on remote navigation. The user only interacts with the drone’s camera and is not required to look at the drone while in flight. While remote navigation is useful for flights where the operator cannot be in proximity to the drone, navigating the drone while in view of the operator is equally important. During remote navigation, the operator cannot see the drone’s surroundings outside of the drone’s camera. However, when the drone is in view of the operator, the operator simply looks at the drone to see its surroundings. Thus, having the drone in view of the operator provides more control. The operator can see where the drone is relative to external forces without the extra step of navigating the drone. In this work, we started a framework for proximity drone navigation using gaze gestures. We developed a Mixed Reality (MR) environment with a simulated drone overlaid on a world view. Using previous work with gaze gestures and gaze-based drone navigation, we created a total of eight gaze gestures to control a drone in view of the user. Although the current system has improvements, it has showed promising results for gaze gesture navigation centered around the drone in frame. System improvements have been noted, and a test plan has been developed.

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ISBN

9798197810601

ORCID

0000-0001-6635-538X

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Available for download on Wednesday, July 28, 2027

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