Suzanne Dazo

Papers

Total Citations

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About

Suzanne Dazo’s research lies at the intersection of human-computer interaction, spatial cognition, and robotics, with a focus on bridging the gap between intuitive human sketches and machine-generated sensor maps. Her work addresses a fundamental challenge: how to make robotic mapping systems more accessible and interpretable for everyday users. In her most cited paper, “A Method for Establishing Correspondences Between Hand-Drawn and Sensor-Generated Maps” (2016, 4 citations), Dazo developed a simple yet effective algorithm that aligns hand-drawn floor plans with SLAM (Simultaneous Localization and Mapping) outputs, enabling users to overlay conceptual spaces—like kitchens or walkways—onto robotic maps. This contribution is critical for applications in assistive robotics, smart homes, and human-robot collaboration, where non-experts need to communicate spatial intent without technical expertise. Her follow-up work, “Sketched Floor Plans versus SLAM Maps: A Comparison” (2016, 2 citations), systematically evaluated the strengths and limitations of each mapping approach, laying groundwork for more user-friendly navigation systems. Though her citation counts are modest, Dazo’s research is notable for its innovative approach to democratizing robotic mapping, making her a pioneer in human-centered spatial computing.