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About

Kay Smarsly is a pioneering researcher at the intersection of structural health monitoring (SHM), robotics, and smart infrastructure management. His work focuses on leveraging autonomous mobile systems — particularly quadruped robots — to revolutionize how civil infrastructure is assessed and maintained, a field where traditional approaches have long been constrained by manual, reactive processes. Smarsly's most influential contribution, "Mobile Structural Health Monitoring Based on Legged Robots" (2023, 16 citations), established a compelling framework for deploying agile robotic platforms within wireless sensor network-enabled SHM systems. Complementary work on quadruped robots (2022) and robotic fleets (2023) further demonstrates his commitment to translating theoretical advances into practical inspection tools for deteriorating infrastructure. His research on LIO-BIM — coupling lidar inertial odometry with building information modeling — reflects his broader ambition to integrate cutting-edge localization and digital twin technologies into autonomous inspection workflows. More recently, Smarsly has extended his vision to urban sewer systems through the KaSyTwin project, applying digital twin methodologies to address the inefficiencies of conventional maintenance. With dozens of citations accumulating across a compact but high-impact portfolio, Smarsly is rapidly establishing himself as a defining voice in intelligent, robot-assisted civil infrastructure management.