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About

Teresa Seco is a robotics researcher whose work focuses on autonomous robot localization in GPS-denied, feature-sparse environments — particularly pipes and tunnels. Her research addresses one of the most persistent challenges in field robotics: enabling reliable robot navigation in constrained, visually impoverished settings where conventional sensor-based approaches fail due to poor visibility, irregular surfaces, and the absence of distinguishable landmarks. Seco's most significant contribution lies in pioneering the use of radiofrequency (RF) spatial fadings as a localization signal in these difficult environments. Her 2016 paper on particle filter-based RF fading localization inside pipes (10 citations) laid important groundwork, which she extended in a 2020 study that accumulated 20 citations — her most recognized work to date. She has further advanced the field by developing graph-based and discrete feature frameworks for tunnel localization, demonstrating a consistent evolution in methodological sophistication across her publications. Beyond pure localization, Seco has contributed to practical robotics applications, including a robotized dumper system for debris removal in tunnels under construction. Collectively, her body of work represents a focused and impactful effort to make autonomous robots viable in some of the most challenging real-world environments imaginable.