Lanxiang Zheng
Papers
6
Total Citations
43
H-Index
4
About
Lanxiang Zheng is a rising star in multi-robot systems and autonomous navigation, whose work bridges aerial and ground robotics for safer, more efficient exploration. Zheng’s core research focuses on safe learning-based control, cooperative exploration, and perception under uncertainty. In a standout contribution, Zheng developed a safe learning control strategy for multiple UAVs operating under uncertain disturbances—such as trajectory conflicts and airflow interference—ensuring both accurate tracking and collision avoidance (18 citations). This work addresses a critical safety bottleneck in drone swarms. Zheng also introduced AAGE, an air-assisted ground robotic exploration framework that leverages a UAV’s wide aerial view to guide a UGV’s detailed mapping, dramatically boosting efficiency in large-scale unknown environments (8 citations). Further innovations include a real-time environment compression method inspired by JPEG, enabling multi-robot teams to share maps under limited bandwidth (8 citations), and VRExplorer, a view-region-based UAV exploration method for intricate spaces (5 citations). With additional work in panoramic visual-inertial odometry and bio-inspired spinal robots, Zheng’s research is shaping the future of resilient, cooperative autonomy.
Research Focus
Key Achievements
Top Papers
- 1Safe Learning-Based Control for Multiple UAVs Under Uncertain Disturbances18 citations · 2023
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