Patrick Fabiani
Papers
3
Total Citations
34
H-Index
3
About
Patrick Fabiani is a leading researcher in autonomous systems, with a focus on decision-making under uncertainty, unmanned aerial vehicle (UAV) navigation, and vision-based tracking. His work addresses critical challenges in enabling robots to operate effectively in complex, unpredictable environments. Fabiani’s major contributions include pioneering frameworks for stochastic planning in search and rescue missions, where he developed generic Dynamic Bayesian Networks (DBNs) to model large Markov Decision Processes, allowing rotorcraft to plan missions despite occlusions and localization uncertainties. His most cited paper, “Tracking an unpredictable target among occluding obstacles under localization uncertainties” (2002, 25 citations), laid foundational methods for robust target tracking in cluttered settings. Additionally, his 2010 work on “System Development and Flight Experiment of Vision-Based Simultaneous Navigation and Tracking” (4 citations) demonstrated a fully integrated UAV system capable of navigating and tracking ground targets without GPS, using onboard vision. This flight experiment showcased practical deployment of his theoretical advances. With a career spanning over two decades, Fabiani’s research has significantly influenced the fields of autonomous navigation, probabilistic robotics, and aerial robotics, providing essential tools for real-world applications in search and rescue, surveillance, and beyond.
Research Focus
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Top Papers
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