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About

Federico Boniardi is a robotics researcher whose work centers on mobile robot navigation, localization, and human-robot interaction — particularly in challenging real-world indoor environments. He has made significant contributions to the problem of deploying robots without requiring costly, expertly-built maps, instead enabling navigation from more accessible representations such as architectural floor plans and hand-drawn sketches. His most cited work, "Robust LiDAR-based localization in architectural floor plans" (2017, 60 citations) and its follow-up pose graph-based system (2018, 57 citations), demonstrated that robots could reliably localize themselves using readily available CAD floor plans, dramatically reducing deployment barriers for service robots. Complementing this, his research on sketch-based navigation interfaces (2016, 52 citations) pioneered intuitive methods allowing non-expert users to guide robots through environments using hand-drawn maps — a genuinely novel human-centered approach to autonomous navigation. Boniardi's broader portfolio reflects a consistent commitment to making robot localization practical and accessible across diverse real-world scenarios, including work on topometric localization and deep learning-based room layout understanding. With over 200 cumulative citations, his research has meaningfully advanced the state of autonomous indoor navigation, with clear implications for service robotics and long-term robot deployment.