F. Yegenoglu

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About

F. Yegenoglu is a pioneering researcher in autonomous robotics, with a career-spanning focus on motion planning, sensor-based control, and multirobot coordination under uncertainty. Yegenoglu’s most influential work, “Online path planning under uncertainty” (2003, 10 citations), introduced a novel algorithm for robot navigation in unstructured, dynamic environments, where sensory data is incomplete and must be actively refined during exploratory motion—a foundational contribution to adaptive, real-time planning. Earlier, Yegenoglu’s “Entropy-driven on-line control of autonomous robots” (1989, 9 citations) broke ground by applying information-theoretic principles to robot decision-making, enabling systems to autonomously reduce uncertainty through active sensing. In “Collision-free path planning for multirobot systems” (2003, 3 citations), Yegenoglu developed a real-time Newton-like iteration method to compute safe trajectories for multiple robots navigating cluttered, dynamic spaces, guiding them through velocity vector fields toward their targets. Though citation counts are modest, these works are recognized for their conceptual depth and early integration of entropy, uncertainty, and online adaptation—themes now central to modern robotics. Yegenoglu’s research remains a touchstone for students and engineers tackling autonomous navigation in unpredictable environments.