Nathan Compan
Papers
1
Total Citations
2
H-Index
1
About
Nathan Compan is a researcher at the intersection of human-robot interaction and autonomous navigation, with a focused interest in how robots can safely and intuitively share physical spaces with people. His work addresses the critical challenge of robot navigation in confined environments, such as narrow corridors and doorways, where traditional path-planning algorithms often fail to account for human comfort and social norms. Compan’s most-cited study, "Evaluating the Impact of Time-to-Collision Constraint and Head Gaze on Usability for Robot Navigation in a Corridor," investigates how an anthropomorphic PR2 robot can adjust its behavior—specifically through gaze cues and collision timing—to improve user experience during close-proximity encounters. This research has garnered early attention with 2 citations, signaling its relevance to the growing field of socially-aware robotics. By blending engineering precision with insights from human psychology, Compan is helping to define the protocols for robots that must navigate alongside humans in tight, unpredictable spaces. His contributions are particularly valuable for the development of service robots in hospitals, offices, and homes, where trust and usability are paramount.
Research Focus
Key Achievements
Top Papers
- 1