Zhefan Xu
Papers
10
Total Citations
192
H-Index
6
About
Zhefan Xu is a robotics researcher specializing in autonomous navigation, dynamic obstacle perception, and unmanned aerial vehicle (UAV) systems. His work sits at the intersection of computer vision, motion planning, and robot autonomy, with a particular focus on enabling robots to operate safely and efficiently in complex, crowded, and dynamic real-world environments. Xu's most impactful contributions center on RGB-D camera-based perception pipelines for detecting and tracking moving obstacles in real time, a challenge that has historically hindered robot deployment in human-populated spaces. His 2023 paper on onboard dynamic-object detection and tracking has garnered 57 citations, reflecting its significance to the field. Complementing this, his gradient-based B-spline trajectory optimization framework for UAV navigation in dynamic environments has attracted 40 citations, demonstrating both theoretical rigor and practical relevance. Beyond perception and planning, Xu has extended his research to inspection robotics in hazardous environments such as tunnel construction sites, as well as intent-prediction-driven control for navigating near human workers. His earlier work on frontier-based exploration and coordinated aerial-ground robot teams further illustrates the breadth of his contributions. Across his body of work, Xu has established himself as a rising voice in autonomous mobile robotics research.
Research Focus
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