Xiaolian Yang
Papers
1
Total Citations
62
H-Index
1
About
Xiaolian Yang is a leading researcher in robotics and autonomous navigation, specializing in path planning for dynamic and unknown environments. Their seminal work, "Conflict-based search with D* lite algorithm for robot path planning in unknown dynamic environments," published in 2022, has garnered 62 citations, establishing a foundational approach for safe and efficient multi-robot coordination. Yang's major contribution lies in integrating conflict-based search principles with the D* Lite algorithm, enabling robots to adaptively replan paths in real time while avoiding collisions in unpredictable settings. This hybrid methodology addresses critical challenges in warehouse automation, search-and-rescue missions, and autonomous driving. By bridging theoretical algorithm design with practical deployment, Yang's research has significantly advanced the field's ability to handle complex, real-world constraints. Their work is frequently cited by peers developing next-generation robotic systems, underscoring its lasting impact. Yang continues to push boundaries in intelligent motion planning, making them a pivotal figure for students and researchers exploring adaptive robotics and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1