Guili Xu

Nanjing University of Aeronautics and Astronautics

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About

Guili Xu is a leading researcher in unmanned aerial vehicle (UAV) navigation and autonomous systems, with a primary focus on path planning and visual-based state estimation. Their foundational work on "Path planning for indoor UAV based on Ant Colony Optimization" (2013, 43 citations) introduced a bio-inspired algorithm for optimal route generation in confined indoor environments, addressing a critical challenge in UAV autonomous navigation. This contribution has provided a robust framework for efficient, collision-free flight paths, influencing subsequent research in swarm robotics and indoor surveillance. More recently, Xu advanced the field of visual landing with their study "Pose and Velocity Estimation Algorithm for UAV in Visual Landing" (2020, 7 citations), which developed a high-speed, accurate state estimation method essential for precise landing maneuvers. By integrating computer vision techniques with real-time velocity and pose calculations, this work enhances the reliability of UAVs in GPS-denied scenarios. Xu’s research bridges theoretical optimization with practical application, making significant strides in enabling safer, more autonomous drone operations for logistics, inspection, and emergency response. Their contributions continue to shape the trajectory of intelligent aerial robotics.