Xuanang Lei
Papers
2
Total Citations
119
H-Index
2
About
Xuanang Lei is a robotics researcher specializing in safety-critical motion planning and control for autonomous mobile robots. His primary research areas include model predictive control (MPC), control barrier functions (CBFs), and real-time obstacle avoidance using LiDAR perception. Lei’s most notable contribution is the development of a Dynamic Control Barrier Function-based Model Predictive Control framework, which integrates point cloud processing with DBSCAN clustering and minimum bounding ellipses to safely navigate both static and dynamic obstacles. This work, published in 2023, has already garnered 117 citations, reflecting its significant impact on the field of safe autonomous navigation. By combining rigorous control theory with practical sensor data, Lei addresses a key challenge in robotics: ensuring safety without sacrificing efficiency. His approach enables mobile robots to operate reliably in cluttered, unpredictable environments, making it highly relevant for applications in warehouse logistics, service robotics, and autonomous driving. Lei’s research stands out for its elegant fusion of theoretical guarantees and real-world deployability, offering a robust solution for safety-critical systems.
Research Focus
Key Achievements
Top Papers
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