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About

Seyed Fakoorian is a roboticist at the forefront of autonomous navigation in extreme environments, best known for his pivotal contributions to the DARPA Subterranean Challenge. His research focuses on robust state estimation, sensor fusion, and field-deployable autonomy for robots operating in GPS-denied, unstructured settings like tunnels and urban ruins. As a core member of TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), Fakoorian co-authored the seminal NeBula architecture, which secured Phase II victory in the DARPA challenge. The foundational NeBula paper (2021) has accumulated over 105 citations, while its follow-up detailing the winning solution (2022) has garnered 51 citations, underscoring the work’s impact on the field. Fakoorian also advanced state estimation theory with the ROSE framework (2023), introducing online covariance adaptation for robust localization, and developed a Maximum Correntropy Kalman Filter (2020) for orientation estimation using low-cost IMUs—a practical contribution to LiDAR-inertial odometry. His recent addendum to NeBula (2024) extends these solutions to larger-scale environments. Through his work, Fakoorian has helped push the boundaries of what autonomous robots can achieve in the world’s most challenging subterranean landscapes.