Abstract
This paper presents a novel approach to unmanned aerial vehicle (UAV) control through electrooculography (EOG) based eye movement tracking. The research focuses on developing an interface that translates eye movements into UAV navigation commands, showcasing a unique integration of biometric technology in UAV (i.e., drone) control. To measure horizontal eye movements, we used EOG electrodes positioned near the person’s eyes. Using a thresholding algorithm, eye movements are categorized as right, left, or neutral, and then converted into control signals using a finite state machine. The control signals are then sent to the UAV via an internet connection. Our experimental results demonstrate precise and efficient UAV control through EOG-based eye tracking. This approach demonstrates a new direction in human-robot interaction, and it holds potential in assistive technology for individuals with mobility or communication challenges. This study establishes a foundation for future advancements in intuitive and accessible UAV control systems.
