This research focuses on enhancing the user experience and control efficiency in remote robotic systems using virtual reality (VR) 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 VR device (Meta Quest Pro), are directly translated into robot actions. This method allows users to control robotic manipulators intuitively, enhancing the precision and realism of remote operations. To address challenges such as mode-switching within a fully immersive environment, we introduce eye-tracking technology, enabling users to switch modes seamlessly without needing to disengage their hands from control tasks.
A notable aspect of our approach is the integration of Catmull-Rom splines for smooth trajectory planning, allowing the robot to follow curved paths based on predefined control points. This method improves path-following performance, making complex manipulations more feasible in confined or hazardous environments.
Through a series of validation experiments, we demonstrate that this VR-based teleoperation system significantly reduces task execution time compared to traditional control methods. The implementation of eye-tracking further simplifies system interaction, allowing a single operator to efficiently handle tasks that typically require multiple personnel.
In summary, this research sets the groundwork for the next generation of teleoperation systems, enhancing safety and efficiency in applications such as nuclear facility maintenance and hazardous environment handling. Our findings demonstrate the effectiveness of combining hand-tracking and eye-tracking technologies to achieve a more intuitive and productive user experience in remote robotic control.
This research focuses on enhancing the user experience and control efficiency in remote robotic systems using virtual reality (VR) 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 VR device (Meta Quest Pro), are directly translated into robot actions. This method allows users to control robotic manipulators intuitively, enhancing the precision and realism of remote operations. To address challenges such as mode-switching within a fully immersive environment, we introduce eye-tracking technology, enabling users to switch modes seamlessly without needing to disengage their hands from control tasks.
A notable aspect of our approach is the integration of Catmull-Rom splines for smooth trajectory planning, allowing the robot to follow curved paths based on predefined control points. This method improves path-following performance, making complex manipulations more feasible in confined or hazardous environments.
Through a series of validation experiments, we demonstrate that this VR-based teleoperation system significantly reduces task execution time compared to traditional control methods. The implementation of eye-tracking further simplifies system interaction, allowing a single operator to efficiently handle tasks that typically require multiple personnel.
In summary, this research sets the groundwork for the next generation of teleoperation systems, enhancing safety and efficiency in applications such as nuclear facility maintenance and hazardous environment handling. Our findings demonstrate the effectiveness of combining hand-tracking and eye-tracking technologies to achieve a more intuitive and productive user experience in remote robotic control.