Rommel Alonzo

The University of Texas at Arlington, Next Generation Technology (United States)

Papers

Total Citations

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About

Rommel Alonzo’s research lies at the intersection of human-robot interaction, assistive robotics, and multi-modal sensor integration, with a focus on making personal robots intuitive and effective in real-world environments. His most cited work, “Investigation of human-robot interface performance in household environments” (15 citations), addresses a critical challenge: enabling robots to navigate and assist in cluttered, dynamic homes without requiring exhaustive pre-programming. Alonzo’s contributions emphasize designing human-robot interfaces that adapt to unpredictable settings, improving robot autonomy and user trust. In his follow-up study, “Multi-modal sensor and HMI integration with applications in personal robotics” (7 citations), he explores combining vision, motion planning, and affordable sensors to create seamless, task-oriented assistance for individual users. By tackling the gap between controlled lab conditions and messy domestic spaces, Alonzo’s work has laid groundwork for more resilient, user-friendly assistive robots. His research is particularly valuable for students and engineers aiming to bridge robotics with everyday human needs, demonstrating that robust perception and adaptive interfaces are key to bringing personal robots out of the lab and into our homes.