This research focuses on enhancing the user experience and control efficiency in remote robotic systems using virtual reality technology. We leverage advanced hand-tracking and eye-tracking methods to create an intuitive teleoperation framework, aimed at improving task accuracy and reducing operational complexity.

The system employs a “virtual hand” approach where the user’s hand movements, detected through a Meta Quest Pro, are directly translated into robot actions. To address mode-switching within a fully immersive environment, eye-tracking enables users to switch modes without disengaging their hands from control tasks.

A notable aspect is the integration of Catmull-Rom splines for smooth trajectory planning, allowing the robot to follow curved paths based on predefined control points. This improves path-following performance in confined or hazardous environments.

Validation experiments demonstrate that the system significantly reduces task execution time compared to traditional control methods, allowing a single operator to handle tasks that typically require multiple personnel.