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About

Esra Kadioglu-Urtis is a robotics researcher whose work centers on multi-agent systems, pursuit-evasion dynamics, and the control of miniature mobile robots. Her most cited paper, "An approach to multi-agent pursuit evasion games using reinforcement learning" (2015, 36 citations), applies reinforcement learning to enable agents to learn optimal pursuit strategies through environmental interaction, advancing the field of autonomous robotics. Earlier foundational work includes "A method for transporting a team of miniature robots" (2004, 24 citations), which addresses coordinated transport of the University of Minnesota's Scout robots—tiny platforms designed for reconnaissance and surveillance. Kadioglu-Urtis also contributed to localization and tracking of these miniature robots using constant curvature dynamic contours (2003, 9 citations), a technique that effectively handles the rapid accelerations and jumps characteristic of Scout movement. Her work on "Visibility in motion" (2007, 3 citations) tackles the challenge of maintaining visual contact with a moving target from multiple angles using pursuit curves. Across these contributions, Kadioglu-Urtis has demonstrated a sustained focus on enabling small, agile robots to perceive, coordinate, and act in dynamic environments—key challenges in field robotics and autonomous systems.