Lukas Danev

Papers

Total Citations

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About

Lukas Danev’s research sits at the intersection of human-robot interaction, affective computing, and social robotics, with a focus on how robots can communicate emotions through non-verbal cues. His most cited work, “Development of animated facial expressions to express emotions in a robot: RobotIcon” (2017, 18 citations), introduces a novel approach to robot design by replacing traditional mechanical faces with animated, screen-based expressions. This contribution addresses a critical challenge in robotics: making machines appear emotionally legible and approachable to humans. By systematically developing a set of facial animations that convey core emotions, Danev’s work has influenced subsequent research on expressive interfaces and user acceptance of social robots. His findings are particularly relevant for applications in assistive robotics, education, and public-facing automation. While his citation count reflects a growing niche, the conceptual impact of his work—bridging animation design and robotics—has been recognized in interdisciplinary communities. Danev’s research underscores a key insight: for robots to integrate into everyday life, they must not only function but also connect. His ongoing work continues to explore how subtle expressive movements can foster trust and engagement between humans and machines.