Yili Zhang

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About

Yili Zhang’s research lies at the intersection of human-computer interaction, spatial cognition, and mobile robotics, with a particular focus on how people create, interpret, and align hand-drawn maps with sensor-generated data. In their most cited work, “A Method for Establishing Correspondences Between Hand-Drawn and Sensor-Generated Maps” (2016, 4 citations), Zhang developed a simple yet elegant algorithm that allows users to overlay conceptual floor plans—sketched by hand—onto SLAM (Simultaneous Localization and Mapping) maps produced by robots. This contribution bridges the gap between intuitive human spatial reasoning and machine perception, enabling tasks like furniture arrangement or functional zone designation (e.g., kitchen, walkway) to be grounded in physical space. Building on this, Zhang’s follow-up study, “Sketched Floor Plans versus SLAM Maps: A Comparison” (2016, 2 citations), systematically evaluated the alignment process, highlighting practical challenges and solutions. Though early in their career, Zhang’s work has already influenced research in human-robot interaction and indoor mapping, offering a foundation for more intuitive interfaces between people and autonomous systems. Their contributions are particularly valuable for students and researchers exploring how to make robotic navigation more accessible and human-centered.