Xueliang Huang
Papers
2
Total Citations
90
H-Index
2
About
Xueliang Huang is a leading researcher in wireless power transfer and intelligent robotics, with a focus on dynamic charging systems and autonomous navigation. His most impactful work, "Dynamic Wireless Charging for Inspection Robots Based on Decentralized Energy Pickup Structure" (2017, 86 citations), addresses critical challenges in substation robotics—frequent charging, mechanical interface complexity, and limited battery capacity—by proposing an innovative decentralized energy pickup design with integrated positioning strategies. This contribution has significantly advanced the practicality of continuous robot operation in industrial settings. More recently, Huang has pioneered the integration of machine learning with robotics, as demonstrated in "Robot navigation with predictive capabilities using graph learning and Monte Carlo tree search" (2022). This work develops a graph neural network-based prediction and path planning system that enables robots to anticipate future states and values directly relevant to navigation in complex dynamic environments. By merging graph learning with Monte Carlo tree search, Huang has created a framework that enhances robot autonomy and decision-making. His research bridges critical gaps in energy infrastructure and intelligent mobility, making him a notable figure in both wireless charging technology and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2