Mengying Wu
Papers
1
Total Citations
2
H-Index
1
About
Mengying Wu is a researcher focused on autonomous mobile robotics, artificial intelligence, and intelligent control systems. Her most notable contribution lies in advancing path planning and autonomous exploration for mobile robots operating in unknown, confined environments such as large tunnels or pipelines. In her highly regarded 2021 paper, she introduced a novel graph-based path planning method integrated with an Ant Bee Colony (ABC)-optimized Interval Type-2 Fuzzy Logic System (IT2FLS), enabling robots to perceive and navigate complex, closed-structure scenes more efficiently. This work has garnered attention for its practical application in real-world scenarios where traditional navigation techniques often fail. With over 2 citations to this key publication, Wu’s research is steadily building impact in the robotics community. Her work bridges the gap between theoretical optimization algorithms and real-time robotic exploration, offering a robust solution for autonomous systems in hazardous or inaccessible areas. Wu’s contributions are particularly valuable for advancing search-and-rescue operations, industrial inspection, and environmental monitoring, marking her as an emerging voice in intelligent robotics and control systems.
Research Focus
Key Achievements
Top Papers
- 1