Xiaoyang Zhan
Papers
7
Total Citations
167
H-Index
4
About
Xiaoyang Zhan is an emerging researcher specializing in autonomous robotics, UAV navigation, and dynamic environment perception. His work sits at the intersection of computer vision, motion planning, and real-time obstacle avoidance, with a particular focus on enabling robots to operate safely and efficiently in complex, crowded environments. Zhan's most influential contributions center on dynamic object detection and tracking for autonomous systems. His 2023 paper on onboard dynamic-object detection and tracking for RGB-D camera-equipped robots has garnered 57 citations, establishing him as a notable voice in lightweight perception pipelines for indoor navigation. Complementing this, his work on gradient-based B-spline trajectory optimization for UAV navigation — cited 40 times — demonstrates his ability to bridge perception and planning, integrating multiple map representations to generate collision-free trajectories around moving obstacles. Beyond ground robots, Zhan has made meaningful contributions to UAV applications, including autonomous tunnel inspection in challenging construction environments and heuristic-based probabilistic roadmaps for dynamic exploration. His more recent research extends into semantic mapping through panoramic LiDAR-camera fusion, signaling a broadening research agenda. With over 160 cumulative citations concentrated in just a few years, Zhan's work is gaining rapid recognition within the robotics and autonomous systems community.
Research Focus
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Top Papers
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