Trevor Lynn Craig
Papers
1
Total Citations
8
H-Index
1
About
Dr. Trevor Lynn Craig is a pioneering researcher at the intersection of human-robot interaction and assistive technology, with a primary focus on gaze-based control systems. His most cited work, "Human gaze commands classification: A shape based approach to interfacing with robots" (2016, 8 citations), introduces a novel shape-based methodology for classifying human gaze patterns into actionable commands for robotic systems. This foundational contribution demonstrates how eye-tracking technology can transform visual sensory input into an output channel, enabling individuals with severe mobility impairments to command robots through natural gaze gestures. By developing algorithms that interpret the geometric shapes traced by eye movements, Craig has created a more intuitive and accessible interface for assistive robotics. His research addresses a critical need in human-robot collaboration, particularly for those who cannot use traditional input devices. The work has influenced subsequent studies in gaze-controlled interfaces and continues to inspire new approaches to non-verbal human-robot communication. Craig's innovative shape-based classification method represents a significant step toward making robotic assistance more responsive and user-friendly for individuals with profound physical limitations.
Research Focus
Key Achievements
Top Papers
- 1