Zi-Xu Yang

Zhengzhou University of Light Industry, Hefei University of Technology

Papers

Total Citations

H-Index

About

Zi-Xu Yang is a rising researcher in intelligent robotics and autonomous navigation, whose work focuses on overcoming fundamental limitations in path planning algorithms for mobile robots, UAVs, and industrial automation systems. Yang’s major contributions lie in enhancing the efficiency and robustness of swarm intelligence algorithms—particularly ant colony optimization and particle swarm optimization—for both 2D and 3D spatial environments. Their highly cited 2025 paper on an improved trimming ant colony optimization algorithm directly addresses the classic problems of slow convergence and local optima entrapment in dynamic settings, achieving a notable 5 citations shortly after publication. A subsequent 2025 study on 3D path planning using enhanced particle swarm optimization further demonstrates Yang’s ability to adapt classical methods for complex, real-world industrial Internet of Things (IIoT) applications, earning 2 citations. By systematically improving search efficiency and solution quality, Yang’s work provides practical, scalable solutions for autonomous systems operating in constrained or hazardous environments. Their research is particularly valuable for engineers and researchers developing next-generation mobile robots, drones, and automated guided vehicles, marking Yang as an emerging authority in computational intelligence for robotics.