Ye Zheng
Papers
1
Total Citations
2
H-Index
1
About
Ye Zheng is a rising researcher in mobile robotics, whose work centers on advancing path planning algorithms to improve the efficiency and safety of autonomous navigation in complex environments. Their most notable contribution is the development of the Grid-Optimized Genetic A* Algorithm (GO-GASA), a two-stage optimization framework that integrates grid optimization with genetic algorithms to enhance traditional A* pathfinding. This innovative approach addresses critical challenges in robotic motion planning, enabling more adaptive and computationally efficient routes. While still early in their career, with their flagship 2025 paper already garnering 2 citations, Zheng’s work demonstrates significant potential for real-world applications in automated warehouses, delivery robots, and exploration systems. By bridging evolutionary computation with classical search methods, they are contributing to the next generation of intelligent navigation systems. As the field of mobile robotics continues to expand, Ye Zheng’s research promises to play an important role in shaping how robots perceive and traverse their environments.
Research Focus
Key Achievements
Top Papers
- 1