Xiaoxue Feng

Papers

Total Citations

H-Index

About

Xiaoxue Feng is a leading researcher in autonomous aerial robotics, with a primary focus on indoor localization and visual navigation for micro air vehicles (MAVs). Her work addresses the critical challenge of enabling unmanned aerial vehicles (UAVs) to operate reliably in GPS-denied environments. Feng’s most influential contribution, her 2018 paper on “Marker-Based Multi-Sensor Fusion Indoor Localization System for Micro Air Vehicles,” has garnered 39 citations and introduces a novel algorithm that fuses data from multiple sensors using ArUco markers. This system innovatively builds and corrects marker maps online through Grubbs criterion and K-mean clustering, preventing map distortion and ensuring robust, real-time positioning. Earlier, in 2016, Feng developed a new method for on-board UAV pose estimation using only a monocular camera, achieving 6D relative pose estimation in known environments. This work demonstrates her ability to create efficient, cost-effective solutions for visual navigation. Through these contributions, Feng has significantly advanced the practical deployment of autonomous drones in complex indoor settings, providing foundational techniques for reliable, marker-based localization that continue to influence the field of aerial robotics.