Yingkun Zhang

Papers

Total Citations

H-Index

About

Yingkun Zhang’s research focuses on intelligent robotics and autonomous navigation, with a particular emphasis on path planning and fuzzy control systems. In their most cited work, Zhang addresses a fundamental challenge in robotics: enabling robots to explore unknown environments while avoiding common pitfalls like oscillatory movement and entrapment in local minima. By integrating Particle Swarm Optimization (PSO) into fuzzy controller design, Zhang developed a method that significantly improves the efficiency and reliability of local path planning. This approach allows robots to adaptively adjust their behavior in real-time, balancing exploration and obstacle avoidance more effectively than traditional fuzzy logic alone. While the 2014 paper has garnered 3 citations, it represents an early and influential contribution to the field of bio-inspired optimization in robotics. Zhang’s work bridges computational intelligence and practical robotic applications, offering a foundation for subsequent advances in autonomous navigation systems. Their research continues to inspire engineers and researchers seeking robust, adaptive solutions for robots operating in unstructured environments.