Xiaoming Huo
Papers
2
Total Citations
42
H-Index
2
About
Xiaoming Huo is a leading researcher in optimization, computational geometry, and path-planning algorithms, with a focus on developing efficient solutions for dynamic and constrained environments. His most-cited work, "Incremental Multi-Scale Search Algorithm for Dynamic Path Planning With Low Worst-Case Complexity" (2011, 38 citations), addresses fundamental challenges in transportation, VLSI design, and robot navigation by introducing a novel algorithm that efficiently handles changing edge costs in graphs with a single endpoint pair. This contribution is particularly notable for its low worst-case complexity, making it highly practical for real-time applications. Huo also explores path-planning under physical constraints, as seen in his work on solving shortest path problems with curvature constraints using beamlets (2011, 4 citations), which bridges computational geometry and robotics. While his citation counts reflect a focused, technical audience, his research has significant implications for autonomous systems and logistics. Huo’s work stands out for its rigorous theoretical foundations and practical relevance, offering valuable insights for students and researchers in robotics, operations research, and algorithm design.
Research Focus
Key Achievements
Top Papers
- 1
- 2Solving shortest path problems with curvature constraints using beamlets4 citations · 2011