Mengyu Ge
Papers
1
Total Citations
3
H-Index
1
About
Mengyu Ge is a researcher whose work focuses on the intersection of robotics, path planning, and algorithmic representation. Their most-cited paper, "A Novel Maze Representation Approach for Finding Filled Path of A Mobile Robot" (2019), introduces an innovative method for representing complex environments to enable more efficient navigation for autonomous mobile robots. This contribution addresses a fundamental challenge in robotics: how to translate physical spaces into computational models that allow robots to find optimal, collision-free paths. While their citation count (3) reflects a growing but early-stage impact, the work demonstrates a clear commitment to advancing practical solutions in mobile robot autonomy. Ge’s research is particularly valuable for students and engineers working on real-world robotic navigation, as it bridges theoretical representation with applied path-finding. Their approach offers a fresh perspective on maze-solving algorithms, potentially influencing future developments in warehouse automation, search-and-rescue robotics, and autonomous vehicles. As their work gains recognition, Mengyu Ge stands as an emerging voice in robotic path planning, contributing to the foundational tools that make smarter, more adaptable machines possible.
Research Focus
Key Achievements
Top Papers
- 1