Xue Mei
Papers
2
Total Citations
88
H-Index
2
About
Xue Mei is a leading researcher in autonomous mobile robotics, with a primary focus on path planning and navigation in complex, dynamic environments. Her work addresses the critical challenge of enabling robots to compute safe, optimal paths under real-world constraints. In her highly cited 2019 paper (64 citations), she introduced the VD-CGT method, which ingeniously combines Voronoi diagrams with computational geometry to categorize and avoid moving obstacles based on their velocity and direction. This approach provides a robust solution for dynamic settings. Building on this, Mei developed the optimized RRT-A* (ORRT-A*) method (24 citations), which integrates morphological dilation to significantly improve path safety and computational efficiency in partially known environments. Her contributions are notable for bridging theoretical geometry with practical robotics, offering scalable algorithms that reduce time complexity while ensuring collision-free navigation. Through these works, Mei has established herself as a key innovator in intelligent motion planning, with her methods serving as foundational references for researchers and engineers developing autonomous systems in logistics, exploration, and service robotics.
Research Focus
Key Achievements
Top Papers
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