Livia Gregorin

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About

Livia Gregorin is a researcher whose work lies at the intersection of multi-robot systems, coordination algorithms, and evolutionary robotics. Her primary research focus is on solving the worst-case pursuit-evasion problem—a critical challenge in which a team of robots must guarantee the capture of evaders that are assumed to be arbitrarily fast and omniscient. This problem has direct applications in high-stakes domains such as search and rescue, surveillance, and security. Gregorin’s most cited work, "Heuristics for the Multi-Robot Worst-Case Pursuit-Evasion Problem" (2017, 10 citations), introduces novel heuristic strategies that enable robots with limited sensing and communication to coordinate effectively without prior knowledge of the environment. In a related study (2016, 3 citations), she applies evolutionary robotics to automatically generate and optimize robot behaviors for this adversarial scenario, demonstrating how artificial evolution can produce robust, scalable solutions. These contributions are notable for addressing the gap between theoretical worst-case guarantees and practical, real-world robot constraints. Gregorin’s research provides foundational insights for designing resilient multi-robot teams capable of operating under uncertainty, making her work a valuable reference for students and researchers in robotics, artificial intelligence, and autonomous systems.