Ying-qiao Chen
Papers
1
Total Citations
12
H-Index
1
About
Ying-qiao Chen is a leading researcher in mobile robotics and intelligent optimization algorithms, with a primary focus on path planning and swarm intelligence. Chen’s most influential work introduces an improved ant colony optimization (ACO) algorithm for mobile robot navigation, addressing key limitations of traditional ACO by employing two fuzzy controllers to dynamically optimize critical parameters (α, β, ρ). This innovation enhances convergence speed and solution quality. Additionally, Chen’s approach incorporates a dynamic searching window and chaos theory to diversify exploration, significantly improving path efficiency in complex environments. With 12 citations, this foundational paper has guided subsequent advances in autonomous navigation and metaheuristic optimization. Chen’s contributions are particularly notable for bridging fuzzy logic and swarm intelligence, offering a robust framework for real-time robotic applications. Their work continues to inspire researchers in robotics, artificial intelligence, and control systems, demonstrating a lasting impact on the development of adaptive, intelligent mobile systems.
Research Focus
Key Achievements
Top Papers
- 1