Matteo Di Maio

Papers

Total Citations

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About

Matteo Di Maio is a researcher at the intersection of human-robot interaction, assistive robotics, and multimodal control systems. His work focuses on making robotic manipulation more intuitive and accessible, particularly for users with limited mobility or in complex operational environments. Di Maio’s most cited paper, “Hybrid Manual and Gaze-Based Interaction With a Robotic Arm” (2021), with 5 citations, introduces a novel approach that combines traditional manual input with gaze tracking to control robotic arms. This hybrid system reduces cognitive load and enhances precision, offering a more natural and comfortable interface for operators. By integrating eye-tracking technology into robotic control, Di Maio addresses a critical challenge in human-robot collaboration: the need for efficient, low-effort interaction in tasks ranging from industrial automation to assistive applications. His work contributes to the broader goal of democratizing robot control, making it accessible to non-experts and individuals with disabilities. Di Maio’s research is notable for its practical focus on user-centered design, bridging the gap between advanced robotics and real-world usability. His contributions are particularly relevant as robots become more prevalent in daily life, highlighting the importance of adaptive, multimodal interfaces for safe and effective human-robot teamwork.